in 90 gettingstarted guide

Informatica 9 (Version 9.0)

Getting Started Guide

Informatica 9 Getting Started Guide

Version 9 .0

Copyright (c) 1998-2010 . All rights reserved.

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This product includes OSSP UUID software which is Copyright © 2002 Ralf S. Engelschall, Copyright © 2002 The OSSP ProjectCopyright © 2002 Cable & Wireless Deutschland. Permissions and limitations regarding this software are subject to terms available athttp://www.opensource.org/licenses/mit-license.php.

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This product includes software copyright © 2003-2006 Joe WaInes, 2006-2007 XStream Committers. All rights reserved. Permissions andlimitations regarding this software are subject to terms available at http://xstream.codehaus.org/license.html. This product includessoftware developed by the Indiana University Extreme! Lab. For further information please visit http://www.extreme.indiana.edu/.

This Software is protected by U.S. Patent Numbers 5,794,246; 6,014,670; 6,016,501; 6,029,178; 6,032,158; 6,035,307; 6,044,374;6,092,086; 6,208,990; 6,339,775; 6,640,226; 6,789,096; 6,820,077; 6,823,373; 6,850,947; 6,895,471; 7,117,215; 7,162,643; 7,254,590; 7,281,001; 7,421,458; and 7,584,422, international Patents and other Patents Pending..

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NOTICES

This Informatica product (the “Software”) includes certain drivers (the “DataDirect Drivers”) from DataDirect Technologies, an operating company of Progress SoftwareCorporation (“DataDirect”) which are subject to the following terms and conditions:

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Part Number: IN-GSG-90000-0002

Table of Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viiInformatica Resources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Informatica Customer Portal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Informatica Documentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Informatica Web Site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Informatica How-To Library. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Informatica Knowledge Base. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii

Informatica Multimedia Knowledge Base. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii

Informatica Global Customer Support. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii

Chapter 1: Getting Started Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1Informatica Domain Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Feature Availability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Introducing Informatica Administrator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Introducing Informatica Analyst. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Introducing Informatica Developer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Informatica Developer Welcome Page. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Cheat Sheets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Data Quality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Data Services. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

The Tutorial Story. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

The Tutorial Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Tutorial Prerequisites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Informatica Administrator Tutorial. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Informatica Analyst Tutorial. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Informatica Data Quality Tutorial. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Informatica Data Services Tutorial. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Part I: Getting Started with Informatica Administrator. . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Chapter 2: Lesson 1. Accessing Informatica Administrator. . . . . . . . . . . . . . . . . . . 13Accessing Informatica Administrator Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Task 1. Record Domain and User Account Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Informatica Domain Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Informatica Administrator User Account. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Task 2. Log In to Informatica Administrator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Accessing Informatica Administrator Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

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Chapter 3: Lesson 2. Creating Application Services. . . . . . . . . . . . . . . . . . . . . . . . . 16Creating Application Services Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Task 1. Create a Model Repository Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Task 2. Create Database Connections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Task 3. Create a Data Integration Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Task 4. Create an Analyst Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Creating Application Services Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Chapter 4: Lesson 3. Setting Up Informatica Users. . . . . . . . . . . . . . . . . . . . . . . . . . 23Setting Up Informatica Users Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Task 1. Create a User. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Task 2. Grant Privileges. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Task 3. Grant Permissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Setting Up Informatica Users Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Chapter 5: Lesson 4. Monitoring Jobs and Applications. . . . . . . . . . . . . . . . . . . . . . 27Monitoring Jobs and Applications Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Task 1. View Profile and Scorecard Jobs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Task 2. View Connections to an SQL Data Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Task 3. View Requests for an SQL Data Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Monitoring Jobs and Applications Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Part II: Getting Started with Informatica Analyst. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Chapter 6: Lesson 1. Setting Up Informatica Analyst. . . . . . . . . . . . . . . . . . . . . . . . 31Setting Up Informatica Analyst Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Task 1. Log In to Informatica Analyst. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Task 2. Create a Project. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Task 3. Create a Folder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Setting Up Informatica Analyst Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Chapter 7: Lesson 2. Creating Data Objects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Creating Data Objects Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Task 1. Create the Flat File Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Task 2. Preview the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Creating Data Objects Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Chapter 8: Lesson 3. Creating Quick Profiles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Creating Quick Profiles Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Task 1. Create and Run a Quick Profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Task 2. View the Profile Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Creating Quick Profiles Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

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Chapter 9: Lesson 4. Creating Custom Profiles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Creating Custom Profiles Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Task 1. Create a Custom Profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Task 2. Run the Profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Task 3. Drill Down on Profile Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Creating Custom Profiles Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Chapter 10: Lesson 5. Creating Expression Rules. . . . . . . . . . . . . . . . . . . . . . . . . . 43Creating Expression Rules Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Task 1. Create Expression Rules and Run the Profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Task 2. View the Expression Rule Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Task 3. Edit the Expression Rules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Creating Expression Rules Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Chapter 11: Lesson 6. Creating and Running Scorecards. . . . . . . . . . . . . . . . . . . . . 46Creating and Running Scorecards Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Task 1. Create a Scorecard from the Profile Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Task 2. Run the Scorecard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Task 3. View the Scorecard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Task 4. Edit the Scorecard. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Task 5. Configure Thresholds. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Task 6. View Score Trend Charts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Creating and Running Scorecards Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Chapter 12: Lesson 7. Creating Reference Tables from Profile Columns. . . . . . . . . 50Creating Reference Tables from Profile Columns Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Task 1. Create a Reference Table from Profile Columns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Task 2. Edit the Reference Table. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Creating Reference Tables from Profile Columns Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Chapter 13: Lesson 8. Creating Reference Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . 53Creating Reference Tables Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Task 1. Create a Reference Table. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Creating Reference Tables Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Part III: Getting Started with Informatica Developer (Data Quality). . . . . . . . . . . . . . . . 55

Chapter 14: Lesson 1. Setting Up Informatica Developer. . . . . . . . . . . . . . . . . . . . . 56Setting Up Informatica Developer Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Task 1. Start Informatica Developer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Task 2. Add a Domain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Task 3. Add a Model Repository. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

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Task 6. Select a Default Data Integration Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Setting Up Informatica Developer Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Chapter 15: Lesson 2. Importing Physical Data Objects. . . . . . . . . . . . . . . . . . . . . . 60Importing Physical Data Objects Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

Task 1. Import the Boston_Customers Flat File Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Task 2. Import the LA_Customers Flat File Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Task 3. Importing the All_Customers Flat File Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Importing Physical Data Objects Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Chapter 16: Lesson 3. Profiling Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Profiling Data Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Task 1. Perform a Join Analysis on Two Data Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Task 2. View Join Analysis Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Task 3. Run a Profile on a Data Source. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Task 4. View Column Profiling Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Profiling Data Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Chapter 17: Lesson 4. Parsing Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68Parsing Data Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Task 1. Create a Target Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Step 1. Create an LA_Customers_tgt Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Step 2. Configure Read and Write Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Step 3. Add Columns to the Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Task 2. Create a Mapping to Parse Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Step 1. Create a Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Step 2. Add Data Objects to the Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Step 3. Add a Parser Transformation to the Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . 72

Step 4. Configure the Parser Transformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

Task 3. Run a Profile on the Parser Transformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Task 4. Run the Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Task 5. View the Mapping Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Parsing Data Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Chapter 18: Lesson 5. Standardizing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Standardizing Data Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

Task 1. Create a Target Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Step 1. Create an All_Customers_Stdz_tgt Data Object. . . . . . . . . . . . . . . . . . . . . . . . . 76


Task 2. Create a Mapping to Standardize Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77


iv Table of Contents


Step 3. Add a Standardizer Transformation to the Mapping. . . . . . . . . . . . . . . . . . . . . . . 78

Step 4. Configure the Standardizer Transformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . 79



Standardizing Data Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Chapter 19: Lesson 6. Validating Address Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Validating Address Data Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Task 1. Create a Target Data Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Step 1. Create the All_Customers_av_tgt Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . 82


Step 3. Add Ports to the Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Task 2. Create a Mapping to Validate Addresses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84



Step 3. Add an Address Validator Transformation to the Mapping. . . . . . . . . . . . . . . . . . . 85

Task 3. Configure the Address Validator Transformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Step 1. Set the Default Address Reference Dataset. . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Step 2. Configure the Address Validator Transformation Input Ports. . . . . . . . . . . . . . . . . 85

Step 3. Configure the Address Validator Transformation Output Ports. . . . . . . . . . . . . . . . 86

Step 4. Connect Unused Data Source Ports to the Data Target. . . . . . . . . . . . . . . . . . . . 87



Validating Address Data Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Part IV: Getting Started with Informatica Developer (Data Services). . . . . . . . . . . . . . . 90

Chapter 20: Lesson 1. Setting Up Informatica Developer. . . . . . . . . . . . . . . . . . . . . 91Setting Up Informatica Developer Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

Task 1. Start Informatica Developer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Task 2. Add a Domain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Task 3. Add a Model Repository. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93



Task 6. Select a Default Data Integration Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Setting Up Informatica Developer Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Chapter 21: Lesson 2. Importing Physical Data Objects. . . . . . . . . . . . . . . . . . . . . . 95Importing Physical Data Objects Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Task 1. Import the Boston_Customers Flat File Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

Task 2. Import the LA_Customers Flat File Data Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

Importing Physical Data Objects Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

Table of Contents v

Chapter 22: Lesson 3. Creating a Logical View of Data. . . . . . . . . . . . . . . . . . . . . . . 98Creating a Logical View of Data Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

Task 1. Import a Logical Data Object Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Task 2. Create a Logical Data Object Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Step 1. Creating the Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Step 2. Adding Sources to the Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

Step 3. Adding an Expression Transformation to the Mapping. . . . . . . . . . . . . . . . . . . . 101

Step 4. Adding a Union Transformation to the Mapping. . . . . . . . . . . . . . . . . . . . . . . . . 102

Task 3. Run the Logical Data Object Mapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Creating a Logical View of Data Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

Chapter 23: Lesson 4. Creating a Virtual View of Data. . . . . . . . . . . . . . . . . . . . . . 104Creating a Virtual View of Data Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

Task 1. Create an SQL Data Service. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Task 2. Run an SQL Query to Preview Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Task 3. Create an Application. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Task 4. Deploy the Application. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Creating a Virtual View of Data Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Chapter 24: Lesson 5. Exporting a Mapping to PowerCenter. . . . . . . . . . . . . . . . . 108Exporting a Mapping to PowerCenter Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

Task 1. Export a Mapping to PowerCenter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

Exporting a Mapping to PowerCenter Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

Appendix A: Frequently Asked Questions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110Administrator FAQ. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

Informatica Developer FAQ. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Informatica Analyst FAQ. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

vi Table of Contents

PrefaceThe Informatica Getting Started Guide is written for data quality and data services developers and analysts. Itprovides a tutorial to help first-time users learn how to use Informatica Developer and Informatica Analyst. Thisguide assumes that you have an understanding of data quality concepts, flat file and relational database concepts,and the database engines in your environment.

Informatica Resources

Informatica Customer PortalAs an Informatica customer, you can access the Informatica Customer Portal site at http://my.informatica.com. Thesite contains product information, user group information, newsletters, access to the Informatica customer supportcase management system (ATLAS), the Informatica How-To Library, the Informatica Knowledge Base, theInformatica Multimedia Knowledge Base, Informatica Documentation Center, and access to the Informatica usercommunity.

Informatica DocumentationThe Informatica Documentation team takes every effort to create accurate, usable documentation. If you havequestions, comments, or ideas about this documentation, contact the Informatica Documentation team throughemail at [email protected]. We will use your feedback to improve our documentation. Let usknow if we can contact you regarding your comments.

The Documentation team updates documentation as needed. To get the latest documentation for your product,navigate to the Informatica Documentation Center from http://my.informatica.com.

Informatica Web SiteYou can access the Informatica corporate web site at http://www.informatica.com. The site contains informationabout Informatica, its background, upcoming events, and sales offices. You will also find product and partnerinformation. The services area of the site includes important information about technical support, training andeducation, and implementation services.

Informatica How-To LibraryAs an Informatica customer, you can access the Informatica How-To Library at http://my.informatica.com. The How-To Library is a collection of resources to help you learn more about Informatica products and features. It includesarticles and interactive demonstrations that provide solutions to common problems, compare features andbehaviors, and guide you through performing specific real-world tasks.

vii

http://my.informatica.com


http://www.informatica.com


Informatica Knowledge BaseAs an Informatica customer, you can access the Informatica Knowledge Base at http://my.informatica.com. Usethe Knowledge Base to search for documented solutions to known technical issues about Informatica products.You can also find answers to frequently asked questions, technical white papers, and technical tips. If you havequestions, comments, or ideas about the Knowledge Base, contact the Informatica Knowledge Base team throughemail at [email protected].

Informatica Multimedia Knowledge BaseAs an Informatica customer, you can access the Informatica Multimedia Knowledge Base at http://my.informatica.com. The Multimedia Knowledge Base is a collection of instructional multimedia files that helpyou learn about common concepts and guide you through performing specific tasks. If you have questions,comments, or ideas about the Multimedia Knowledge Base, contact the Informatica Knowledge Base team throughemail at [email protected].

Informatica Global Customer SupportYou can contact a Customer Support Center by telephone or through the WebSupport Service. WebSupportrequires a user name and password. You can request a user name and password at http://my.informatica.com.

Use the following telephone numbers to contact Informatica Global Customer Support:

North America / South America Europe / Middle East / Africa Asia / Australia

Toll Free+1 877 463 2435 Standard RateBrazil: +55 11 3523 7761Mexico: +52 55 1168 9763United States: +1 650 385 5800

Toll Free00 800 4632 4357 Standard RateBelgium: +32 15 281 702France: +33 1 41 38 92 26Germany: +49 1805 702 702Netherlands: +31 306 022 797Spain and Portugal: +34 93 480 3760United Kingdom: +44 1628 511 445

Toll FreeAustralia: 1 800 151 830Singapore: 001 800 4632 4357 Standard RateIndia: +91 80 4112 5738

viii Preface




C H A P T E R 1

Getting Started OverviewThis chapter includes the following topics:

¨ Informatica Domain Overview, 1

¨ Introducing Informatica Administrator, 4

¨ Introducing Informatica Analyst, 4

¨ Introducing Informatica Developer, 5

¨ The Tutorial Story, 7

¨ The Tutorial Structure, 8

Informatica Domain OverviewInformatica has a service-oriented architecture that provides the ability to scale services and to share resourcesacross multiple machines. The Informatica domain is the primary unit for management and administration ofservices.

Informatica contains the following components:

¨ Application clients. A group of clients that you use to access underlying Informatica functionality. Applicationclients make requests to the Service Manager or application services.

¨ Application services. A group of services that represent server-based functionality. An Informatica domain cancontain a subset of application services. You configure the application services that are required by theapplication clients that you use.

¨ Repositories. A group of relational databases that store metadata about objects and processes required tohandle user requests from application clients.

¨ Service Manager. A service that is built in to the domain to manage all domain operations. The ServiceManager runs the application services and performs domain functions including authentication, authorization,and logging.

You can log in to Informatica Administrator after you install Informatica 9.0. You use Informatica Administrator tomanage the domain and configure the required application services before you can access the remainingapplication clients.

The following figure shows the application services and the repositories that each application client uses in anInformatica domain:

1

The following table lists the application clients, not including Informatica Administrator, and the applicationservices and the repositories that the client requires:

Application Client Application Services Repositories

Data Analyzer Reporting Service Data Analyzer repository

Informatica Analyst - Analyst Service- Data Integration Service- Model Repository Service

Model repository

Informatica Developer - Analyst Service- Data Integration Service- Model Repository Service

Model repository

Metadata Manager - Metadata Manager Service- PowerCenter Integration Service- PowerCenter Repository Service

- Metadata Manager repository- PowerCenter repository

2 Chapter 1: Getting Started Overview

Application Client Application Services Repositories

PowerCenter Client - PowerCenter Integration Service- PowerCenter Repository Service

PowerCenter repository

Web Services Hub Console - PowerCenter Integration Service- PowerCenter Repository Service- Web Services Hub

PowerCenter repository

The following application services are not accessed by an Informatica application client:

¨ PowerExchange Listener Service. Manages the PowerExchange Listener for bulk data movement and changedata capture. The PowerCenter Integration Service connects to the PowerExchange Listener through theListener Service.

¨ PowerExchange Logger Service. Manages the PowerExchange Logger for Linux, UNIX, and Windows tocapture change data and write it to the PowerExchange Logger Log files. Change data can originate from DB2recovery logs, Oracle redo logs, a Microsoft SQL Server distribution database, or data sources on an i5/OS orz/OS system.

¨ SAP BW Service. Listens for RFC requests from SAP BI and requests that the PowerCenter Integration Servicerun workflows to extract from or load to SAP BI.

Feature AvailabilityInformatica 9.0 products use a common set of applications. The product features you can use depend on yourproduct license.

The following table describes the licensing options and the application features available with each option:

Licensing Option Informatica Developer Features Informatica Analyst Features

Data Explorer Advanced Edition - Profiling- Scorecarding

- Profiling- Scorecarding- Create and run profiling rules- Reference table management

Data Quality - Create and run mappings with alltransformations

- Create and run rules- Profiling- Scorecarding- Export objects to PowerCenter

- Profiling- Scorecarding- Reference table management- Create profiling rules- Run rules in profiles- Bad and duplicate record

management

Informatica Domain Overview 3

Licensing Option Informatica Developer Features Informatica Analyst Features

Data Services - Create logical data object models- Create and run mappings with Data

Services transformations- Create SQL data services- Export objects to PowerCenter

- Reference table management

Data Services and Profiling Option - Create logical data object models- Create and run mappings with Data

Services transformations- Create SQL data services- Export objects to PowerCenter- Create and run rules with Data Services

transformations- Profiling

- Reference table management

Note: Informatica Data Explorer Advanced Edition functionality is a subset of Informatica Data Quality functionality.

Introducing Informatica AdministratorInformatica Administrator (Administrator tool) is the administration tool you use to administer the Informaticadomain and Informatica security. Effective in version 9.0, the PowerCenter Administration Console is renamed toInformatica Administrator.

Use the Administrator tool to administer the Informatica domain and Informatica security. You can use theAdministrator tool to perform the following tasks:

¨ Domain administrative tasks. Manage logs, domain objects, and domain reports. Domain objects includeapplication services, nodes, grids, folders, database connection, applications, and licenses.

¨ Security administrative tasks. Manage users, groups, roles, and privileges.

Introducing Informatica AnalystInformatica Analyst is a web-based application client that analysts can use to analyze, cleanse, standardize,profile, and score data in an enterprise.

Business analysts and developers use Informatica Analyst for data-driven collaboration. You can perform columnand rule profiling, scorecarding, and bad record and duplicate record management. You can also managereference data and provide the data to developers in a data quality solution.

Use Informatica Analyst to accomplish the following tasks:

¨ Profile data. Create and run a profile to analyze the structure and content of enterprise data and identifystrengths and weaknesses. After you run a profile, you can selectively drill down to see the underlying rowsfrom the profile results. You can also add columns to scorecards and add column values to reference tables.

¨ Create rules in profiles. Create and apply rules within profiles. A rule is reusable business logic that definesconditions applied to data when you run a profile. Use rules to further validate the data in a profile and tomeasure data quality progress.


¨ Score data. Create scorecards to score the valid values for any column or the output of rules. Scorecardsdisplay the value frequency for columns in a profile as scores. Use scorecards to measure and visuallyrepresent data quality progress. You can also view trend charts to view the history of scores over time.

¨ Manage reference data. Create and update reference tables for use by analysts and developers to use in dataquality standardization and validation rules. Create, edit, and import data quality dictionary files as referencetables. Create reference tables to establish relationships between source data and valid and standard values.Developers use reference tables in standardization and lookup transformations in Informatica Developer.

¨ Manage bad records and duplicate records. Fix bad records and consolidate duplicate records.

Introducing Informatica DeveloperInformatica Developer is an application client that developers use to design and implement data quality and dataservices solutions.

The following figure shows the Developer tool:

The Developer tool includes an editor, in which you can edit objects. In this example, the editor shows theCustomer_Objects logical data object model. Depending on the object in the editor, the Developer tool displaysviews, such as the default view.

The Developer tool also includes the following views that appear independently of the objects in the editor:

¨ Object Explorer. Shows projects, folders, and the objects they contain.

¨ Outline. Shows dependent objects in an object.

¨ Properties. Shows object properties.

¨ Data Viewer. Shows the results of a mapping, data preview, or an SQL query.

¨ Validation Log. Shows object validation errors.

¨ Cheat Sheets. Shows cheat sheets.

You can hide any view and move any view to another location in the Developer tool. You can also display otherviews, such as the Search view. Click Window > Show View to select the views you want to display.

Introducing Informatica Developer 5

Informatica Developer Welcome PageThe first time you open the Developer tool, the Welcome page appears. Use the Welcome page to learn moreabout the Developer tool, set up the Developer tool, and to start working in the Developer tool.

The Welcome page displays the following options:

¨ Overview. Click the Overview button to get an overview of data quality and data services solutions.

¨ First Steps. Click the First Steps button to learn more about setting up the Developer tool.

¨ Tutorials. Click the Tutorials button to see tutorial lessons for data quality and data services solutions.

¨ Web Resources. Click the Web Resources button for a link to my.informatica.com. From my.informatica.com,you can access the Informatica How-To Library, which contains articles about the Developer tool, InformaticaData Quality, and Informatica Data Services.

¨ Workbench. Click the Workbench button to start working in the Developer tool.

Cheat SheetsThe Developer tool includes cheat sheets as part of the online help. A cheat sheet is a step-by-step guide thathelps you complete one or more tasks in the Developer tool.

After you complete a cheat sheet, you complete the tasks and see the results. For example, after you complete acheat sheet to import and preview a relational physical data object, you have imported a relational database tableand previewed the data in the Developer tool.

To access cheat sheets, click Help > Cheat Sheets .

Data QualityUse the data quality capabilities in the Developer tool to analyze the content and structure of your data andenhance the data in ways that meet your business needs.

Use the Developer tool to design and run processes that achieve the following objectives:

¨ Profile data. Profiling reveals the content and structure of your data. Profiling is a key step in any data project,as it can identify strengths and weaknesses in your data and help you define your project plan.

¨ Standardize data values. Standardize data to remove errors and inconsistencies that you find when you run aprofile. You can standardize variations in punctuation, formatting, and spelling. For example, you can ensurethat the city, state, and ZIP code values are consistent.

¨ Parse records. Parse data records to improve record structure and derive additional information from your data.You can split a single field of freeform data into fields that contain different information types. You can also addinformation to your records. For example, you can flag customer records as personal or business customers.

¨ Validate postal addresses. Address validation evaluates and enhances the accuracy and deliverability of yourpostal address data. Address validation corrects errors in addresses and completes partial addresses bycomparing address records against reference data from national postal carriers. Address validation can alsoadd postal information that speeds mail delivery and reduces mail costs.

¨ Find duplicate records. Duplicate record analysis compares a set of records against each other to find similaror matching values in selected data columns. You set the level of similarity that indicates a good matchbetween field values. You can also set the relative weight given to each column in match calculations. Forexample, you can prioritize surname information over forename information.


¨ Create reference data tables. Reference data tables are key elements in data standardization. Informaticaprovides a comprehensive set of reference data tables. You can create custom reference tables from columnsin your source data.

¨ Create and run data quality rules. Informatica provides pre-built rules that you can run or edit to suit yourproject objectives. You can create rules in the Developer tool.

¨ Collaborate with Informatica users. The rules and reference data tables you add to the Model repository areavailable to users in the Developer tool and the Analyst tool. Users can collaborate on projects, and differentusers can take ownership of objects at different stages of a project.

¨ Export mappings to PowerCenter. You can export mappings to PowerCenter to reuse the metadata for physicaldata integration or to create web services.

Data ServicesData services are a collection of reusable operations that you can run against sources to access, transform, anddeliver data.

Use the data services capabilities in the Developer tool to achieve the following objectives:

¨ Define logical views of data. A logical view of data describes the structure and use of data in an enterprise. Youcan create a logical data object model that shows what types of data your enterprise uses and how that data isstructured.

¨ Map logical models to data sources or targets. Create a mapping that links objects in a logical model to datasources or targets. You can link data from multiple, disparate sources to have a single view of the data. Youcan also load data that conforms to a model to multiple, disparate targets.

¨ Create virtual views of data. You can deploy a logical model to a virtual federated database. End users can runSQL queries against the virtual data without affecting the actual source data.

¨ Export mappings to PowerCenter. You can export mappings to PowerCenter to reuse the metadata for physicaldata integration or to create web services.

¨ Create and deploy mappings that end users can query. You can create mappings and deploy them so that endusers can query the mapping results.

¨ Profile data. If you use the Profiling Option, profile data to reveal the content and structure of your data.Profiling is a key step in any data project, as it can identify strengths and weaknesses in your data and helpyou define your project plan.

The Tutorial StoryHypoStores Corporation is a national retail organization with headquarters in Boston and stores in several states.It integrates operational data from stores nationwide with the data store at headquarters on regular basis. Itrecently opened a store in Los Angeles.

The headquarters includes a central ICC team of administrators, developers, and architects responsible forproviding a common data services layer for all composite and BI applications. The BI applications include a CRMsystem that contains the master customer data files used for billing and marketing.

The Tutorial Story 7

HypoStores Corporation must perform the following tasks to integrate data from the Los Angeles operation withdata at the Boston headquarters:

¨ Set up a single view of customer data from both locations.

¨ Create a virtual database to enable access to the customer data from both offices.

¨ Examine the Boston and Los Angeles data for data quality issues and resolve any issues that are identified.

¨ Check the Boston and Los Angeles customer data for duplicate records.

¨ Validate the accuracy of the postal address information in the data for CRM purposes.

The Tutorial StructureThe Getting Started Guide contains four tutorials that include lessons and tasks.

TutorialsThis guide contains four tutorials that are comprised of lessons and tasks. The administrator must complete theconfiguration lessons in the Administrator tutorial to set the environment for the other tutorials.

LessonsEach lesson introduces concepts that will help you understand the tasks to complete in the lesson. The lessonprovides business requirements from the overall story. The objectives for the lesson outline the tasks that you willcomplete to meet business requirements. Each lesson provides an estimated time for completion. When youcomplete the tasks in the lesson, you can review the lesson summary.

If the environment within the tool is not configured, the first lesson in each tutorial helps you do so.

TasksThe tasks provide step-by-step instructions. Complete all tasks in the order listed to complete the lesson.

Tutorial PrerequisitesBefore you can begin the tutorial lessons, the Informatica domain must be running with at least one node set up.

The installer includes tutorial files that you will use to complete the lessons. You can find all the files in both theclient and server installations:

¨ You can find the tutorial files in the following location in the Developer tool installation path:

<Informatica Installation Directory>\clients\DeveloperClient\Tutorials

¨ You can find the tutorial files in the following location in the services installation path:

<Informatica Installation Directory>\services\Tutorials

The following table lists the files that you need for the tutorial lessons:

File Name Tutorial

All_Customers.csv Data Quality, Data Services

Boston_Customers.csv Data Quality, Data Services


File Name Tutorial

Customer_Order.xsd Data Services

LA_customers.csv Analyst Tool, Data Quality, Data Services

The Validating Address Data lesson in the Data Quality tutorial reads address reference data for United Statesaddresses. For information on the address reference data available in your domain, contact an InformaticaAdministrator user.

Informatica Administrator TutorialDuring this tutorial, the administrator logs into the Administrator tool, creates application services, creates a user,and monitors jobs and applications on a Data Integration Service.

There are four lessons in this tutorial.

Lesson 1. Access Informatica AdministratorAn administrator logs into the Administrator tool. Set aside 5 to 10 minutes to complete this lesson.

Lesson 2. Create Application ServicesAn administrator creates application services. Set aside 10 to 15 minutes to complete this lesson.

Lesson 3. Set Up UsersAn administrator creates a user account for a developer or analyst. A developer or analyst needs to login to theDeveloper or Analyst tool. Set aside 5 to 10 minutes to complete this lesson.

Lesson 4. Monitor Jobs and ApplicationsAn administrator monitors the activity of jobs and applications that are running on a Data Integration Service. Setaside 5 to 10 minutes to complete this lesson.

Informatica Analyst TutorialDuring this tutorial, an analyst logs into the Analyst tool, creates projects and folders, creates profiles and rules,scores data, and creates reference tables.

The lessons you can perform depend on whether you have the Informatica Data Quality, Informatica DataExplorer, Informatica Data Services, or PowerCenter products.

The following table describes the lessons you can perform, depending on your product.

Lesson Description Product

Lesson 1. Setting up Informatica Analyst Log in to the Analyst tool and create aproject and folder for the tutoriallessons.

All

Lesson 2. Creating Data Objects Import a flat file as a data object andpreview the data.

Data QualityData Explorer

Lesson 3. Creating Quick Profiles Creating a quick profile to quickly getan idea of data quality.


The Tutorial Structure 9

Lesson Description Product

Lesson 4. Creating Custom Profiles Create a custom profile to configurecolumns, and sampling and drilldownoptions.


Lesson 5. Creating Expression Rules Create expression rules to modify andprofile column values.

Data Quality

Lesson 6. Creating and RunningScorecards

Create and run a scorecard to measuredata quality progress over time.


Lesson 7. Creating Reference Tablesfrom Profile Results

Create a reference table that you canuse to standardize source data.

Data QualityData ExplorerData Services

Lesson 8. Creating Reference Tables Create a reference table to establishrelationships between source data andvalid and standard values.

All

Note: This tutorial does not include lessons on bad record and consolidation record management.

Informatica Data Quality TutorialIn this tutorial, you use the Developer tool to perform several data quality operations.

Informatica Data Quality and Informatica Data Explorer users use the Developer tool to create and run profiles thatanalyze the content and structure of data.

Informatica Data Quality users use the Developer tool to design and run processes that enhance data quality.

Complete the following lessons in the data quality tutorial:

Lesson 1. Setting Up Informatica DeveloperCreate a connection to a Model repository that is managed by a Model Repository Service in a domain. Create aproject and folder to store work for the lessons in the tutorial. Select a default Data Integration Service.

Lesson 2. Importing Physical Data ObjectsYou will define data quality processes for the customer data files associated with these objects.

Lesson 3. Profiling DataProfiling reveals the content and structure of your data.

Profiling includes join analysis, a form of analysis that determines if a valid join is possible between two datacolumns.

Lesson 4. Parsing DataParsing enriches your data records and improves record structure. It can find useful information in your data andalso derive new information from current data.

Lesson 5. Standardizing DataStandardization removes data errors and inconsistencies found during profiling.

Lesson 6. Validating Address DataAddress validation evaluates the accuracy and deliverability of your postal addresses and fixes address errors andomissions in addresses.


Informatica Data Services TutorialIn this tutorial, a developer sets up the Developer tool and imports physical data objects. The developer creates alogical data model to combine data into a single view. The developer creates a virtual database that end users canquery. Finally, the developer exports a mapping to PowerCenter.

Complete the following lessons in the data services tutorial:

Lesson 1. Setting Up Informatica DeveloperCreate a connection to a Model repository that is managed by a Model Repository Service in a domain. Create aproject and folder to store work for the lessons in the tutorial. Select a default Data Integration Service.

Lesson 2. Importing Physical Data ObjectsImport flat file physical data objects.

Lesson 3. Creating a Logical View of DataImport a logical data object model and create a logical data object mapping.

Lesson 4. Creating a Virtual View of DataCreate an SQL data service that contains a virtual database. Add the SQL data service to an application anddeploy the application so that end users can query the virtual data.

Lesson 5. Exporting a Mapping to PowerCenterExport a mapping to a PowerCenter repository.

The Tutorial Structure 11

Part I: Getting Started withInformatica Administrator

This part contains the following chapters:

¨ Lesson 1. Accessing Informatica Administrator, 13

¨ Lesson 2. Creating Application Services, 16

¨ Lesson 3. Setting Up Informatica Users, 23

¨ Lesson 4. Monitoring Jobs and Applications, 27

12

C H A P T E R 2

Lesson 1. Accessing InformaticaAdministrator

This chapter includes the following topics:

¨ Accessing Informatica Administrator Overview, 13

¨ Task 1. Record Domain and User Account Information, 14

¨ Task 2. Log In to Informatica Administrator, 14

¨ Accessing Informatica Administrator Summary, 15

Accessing Informatica Administrator OverviewThe Administrator tool consolidates the administrative tasks for domain objects such as services, nodes, licenses,and grids. You manage the domain and the security of the domain through the Administrator tool.

ObjectivesIn this lesson, you complete the following tasks:

¨ Record the domain and the administrator user account information. The domain information provides addresscomponents of the Administrator tool URL, and the user account provides access to the Administrator tool.

¨ Log in to the Administrator tool. Lessons in this tutorial require that you can log in to the Administrator tool.

PrerequisitesBefore you start this lesson, verify the following prerequisites:

¨ The Informatica domain is running.

¨ The administrator or user who installed Informatica 9.0 has provided you with the domain connectivityinformation and an administrator user account.

TimingSet aside 5 to 10 minutes to complete this lesson.

13

Task 1. Record Domain and User Account InformationIn this task, you record the domain connection and user account information.

You need this information to access the Administrator tool.

Informatica Domain InformationIf you do not know the domain connectivity information, contact the person who installed Informatica 9.0.

Use the following table to record domain information:

Domain Information Values

Domain Name

Gateway Node Host Name

Informatica Administrator Port Number

Informatica Administrator User AccountUse an administrator user account to log in to the Administrator tool to complete the lessons in this tutorial.

The default administrator user name is Administrator. If you do not have the password for the defaultadministrator, ask for the password or for a user account with the administrator role.

Use the following table to record the user account information:

Account Information Values

Administrator Username

Administrator Password

Security Domain

Task 2. Log In to Informatica AdministratorIn this task, you log in to the Administrator tool.

1. Start Microsoft Internet Explorer or Mozilla Firefox.

2. In the Address field, enter the following URL for the Administrator tool login page:http://<master_gateway_node_host_name>:<Informatica_Administrator_port_number>/adminconsole

The Informatica Administrator login page appears.

14 Chapter 2: Lesson 1. Accessing Informatica Administrator

3. Enter the user name and password.

4. Select Native or the name of an LDAP security domain.

The Security Domain field appears when the Informatica domain contains an LDAP security domain.

5. Click Login.

Accessing Informatica Administrator SummaryIn this lesson, you learned the components of the Administrator tool and how to log in to the Administrator tool.

You recorded the domain connectivity and administrator user account information. You also logged into theAdministrator tool.

Use the administrator user account to complete lessons 2, 3, and 4 in this tutorial.

Accessing Informatica Administrator Summary 15

C H A P T E R 3

Lesson 2. Creating ApplicationServices


¨ Creating Application Services Overview, 16

¨ Task 1. Create a Model Repository Service, 17

¨ Task 2. Create Database Connections, 18

¨ Task 3. Create a Data Integration Service, 19

¨ Task 4. Create an Analyst Service, 20

¨ Creating Application Services Summary, 22

Creating Application Services OverviewUse the Administrator tool to create application services.

Application services provide server-based functionality. Create the following application services for use with theDeveloper and Analyst tools:

¨ Model Repository Service. The Model Repository Service manages the Model repository. The Developer tool,the Analyst tool, the Data Integration Service, and the Administrator tool store metadata in the Model repository.

¨ Data Integration Service. The Data Integration Service is an application service that performs data integrationtasks for Informatica Analyst, Informatica Developer, and external clients.

¨ Analyst Service. The Analyst Service is an application service that runs the Analyst tool. The Analyst Servicemanages the connections between service components and the users who access the Analyst tool.

A database connection is a domain object that contains database connectivity information. The Data IntegrationService connects to the database to process integration objects for the Developer tool and the Analyst tool.Integration objects include mappings, profiles, scorecards, and SQL data services.

StoryAn administrator at HypoStores needs to create application services. Developers, architects, and analysts needapplication services to use the Developer and Analyst tools.

16


¨ Create a Model Repository Service to store metadata.

¨ Create database connections to the profiling warehouse and the staging databases.

¨ Create a Data Integration Service to perform data integration tasks.

¨ Create an Analyst Service to run the Analyst tool.


¨ The database administrator has provided you with the Model repository database connectivity information. Youmust have the database connection information to create the Model Repository Service. All tutorials in thisguide require the Model repository database.

¨ The database administrator has provided you with the profiling warehouse database connectivity information.Use this information to create the database connection to the profiling warehouse. The tutorial for the Analysttool requires a profiling warehouse.

¨ The database administrator has provided you with the staging database connectivity information. Use thisinformation to create a database connection to the staging database. The Analyst Service uses a stagingdatabase. The tutorial for the Analyst tool requires a profiling warehouse.


Task 1. Create a Model Repository ServiceIn this task, you create a Model Repository Service for tutorials in this guide.

1. In the Administrator tool, click the Domain tab.

2. On the Navigator Actions menu, click New > Model Repository Service .

The New Model Repository Service - Step 1 of 2 dialog box appears.

3. Enter the following required information:

Property Description

Name Name of the Model Repository Service. The name is not case sensitive and mustless than 128 characters. The name cannot have leading spaces, trailing spaces,carriage returns, or tabs. The name cannot contain the following characters:

/ * ? < > " |

Location The folder where you want to create the service. If a folder is not specified, thedomain name appears in this field.

License License to assign to the Model Repository Service.

Node Node to run the Model Repository Service.

4. Click Next.

Task 1. Create a Model Repository Service 17

The New Model Repository Service - Step 2 of 2 dialog box appears.



Database Type Type of database.

Username Database user name.

Password Database user password.

Connection String The JDBC connect string used to connect to the Model repository database.- IBM DB2: jdbc:informatica:db2://<host name>:<port>;DatabaseName=<database

name>- Oracle: jdbc:informatica:oracle://<host_name>:<port>;SID=<database name>- Microsoft SQL Server: jdbc:informatica:sqlserver://<host

name>:<port>;DatabaseName=<database name>

Creation options Determines whether to create content in the repository. If the repository containscontent, do not create content. If the repository does not contain content, choose tocreate content.

6. Click Test Connection to verify connectivity.

7. Click Finish.

You have created a Model Repository Service.

8. On the Domain Actions menu, click Enable to make the Model Repository Service available.It may take a few minutes to enable the service.

Task 2. Create Database ConnectionsIn this task, you create database connections for the profiling warehouse database and the staging database.

1. In the Administrator tool header, click Manage > Database Connections .

2. Click New.

The New Database Connection dialog box appears.

3. Enter the required connection properties based on the database type:


Name Name of the connection. Connection names cannot havespaces and cannot be longer than 128 characters.

The name cannot have leading spaces, trailing spaces,carriage returns, or tabs. The name cannot contain thefollowing characters:

/ * ? < > " |

Database Type Type of database.

Username Database user password.

18 Chapter 3: Lesson 2. Creating Application Services


Password Password for the database user name.

Metadata Access: Connection String JDBC connection URL used to access metadata from thedatabase.- IBM DB2: jdbc:informatica:db2://<host

name>:<port>;DatabaseName=<database name>- Oracle: jdbc:informatica:oracle://

<host_name>:<port>;SID=<database name>- Microsoft SQL Server: jdbc:informatica:sqlserver://<host

name>:<port>;DatabaseName=<database name>Not applicable for ODBC.

Data Access: Connection String Connection string used to access data from the database.- IBM DB2: <database name>- Microsoft SQL Server: <server name>@<database

name>- ODBC: <data source name>- Oracle: <database name>.world from the TNSNAMES

entry.

Data Access: Code Page Code page used to read from a source database or write toa target database or target file.

4. Click Test Connection to verify metadata access connectivity.

5. Click OK.

6. Repeat steps 2 through 5 for each required database.

7. Click CloseYou created a database connection for the profiling warehouse and the staging database.

Task 3. Create a Data Integration ServiceIn this task, you create a Data Integration Service to process integration objects that users create in other tutoriallessons.


2. On the Navigator Actions menu, click New > Data Integration Service .

The New Data Integration Service - Step 1 of 2 dialog box appears.

Task 3. Create a Data Integration Service 19



Name Name of the Data Integration Service. The name is not case sensitive andmust less than 128 characters. The name cannot have leading or trailingspaces, carriage returns or tabs. The name cannot contain the followingcharacters:

/ * ? < > " |

Location The folder where you want to create the service. If a folder is notspecified, the domain name appears in this field.

License License to assign to the Data Integration Service.

Node Node on which the Data Integration Service will run.

HTTP Port Port number for the Data Integration Service.

Model Repository Service Model Repository Service that stores run-time metadata required to runthe mappings and SQL data services.

Username User name to access the Model Repository Service.

Use login information for yourself or for another administrator.

Password User password to access the Model Repository Service.


4. Click Next.

The New Data Integration Service - Step 2 of 2 dialog box appears.

5. To complete the Analyst tool lessons, click Select to choose a connection for a profiling warehouse database.

The Select Database Connections dialog box appears.

a. Select the connection to the profiling warehouse database.

b. Choose to use existing content or create content.

c. Click OK.

6. Click Finish.

You have created a Data Integration Service.

7. On the Domain tab Actions menu, click Enable to make the Data Integration Service available.

Task 4. Create an Analyst ServiceIn this task, you create an Analyst Service for the Analyst tool lessons.

1. In Informatica Administrator, click the Domain tab.

2. On the Domain tab Actions menu, click New > Analyst Service .




Name Name of the Analyst Service. The name is not case sensitive and mustless than 128 characters. The name cannot have leading spaces, trailingspaces, carriage returns, or tabs. The name cannot contain the followingcharacters:

/ * ? < > " |

Location Domain where the Analyst Service will run.

License License to assign to the Analyst Service.

Node Node on which the Analyst Service will run.

HTTP Port Port number for the Analyst Service.

Model Repository Service Model Repository Service to associate with the Analyst Service. TheAnalyst Service manages the connections to the Model Repository Servicefor the Analyst tool.

Username User name to access the Model Repository Service.


Password User password to access the Model Repository Service.


4. Click Next.

The Create New Analyst Service Step 2 of 3 dialog box appears.



Data Integration Service Data Integration Service name to associate with theAnalyst Service. The Analyst Service manages theconnection to a Data Integration Service for the Analysttool.

Flat File Cache Location Location of the flat file cache where the Analyst Servicestores uploaded flat files. When you import a referencetable or a flat file source, the Analyst Service uses the filesfrom this directory to create a reference table or a fileobject. Choose a path that is local to the Analyst Servicemachine. For example, <installation directory>\server\flatfilecache

If you configure a directory path that does not exist, theAnalyst Service creates it.

6. Click Select to select a staging database.

The Select Database Connections dialog box appears.

7. Select a database connection.

8. Choose to use existing content or create content.

Task 4. Create an Analyst Service 21

9. Click OK.

10. Click Next.

11. Click Finish.

You have created an Analyst Service.

12. On the Domain tab Actions menu, click Enable to make the Analyst Service available.

Creating Application Services SummaryIn this lesson, you learned why you create Model Repository Services, Data Integration Services, AnalystServices, and database connections. You also learned how to create application services and databaseconnections in the Administrator tool.

You created and started a Model Repository Service, a Data Integration Service, and an Analyst Service. You alsocreated database connections for the profiling warehouse and staging database.


C H A P T E R 4

Lesson 3. Setting Up InformaticaUsers


¨ Setting Up Informatica Users Overview, 23

¨ Task 1. Create a User, 24

¨ Task 2. Grant Privileges, 24

¨ Task 3. Grant Permissions, 25

¨ Setting Up Informatica Users Summary, 26

Setting Up Informatica Users OverviewYou need a user account to access the services and objects in the domain and to use the Developer and Analysttool. Users can perform tasks in Informatica client applications based on the privileges and permissions assignedto them.

To complete the Analyst tool and Developer tool tutorials in this guide, users requires privileges to do the followingtasks:

¨ Access the Analyst tool

¨ Create projects in the Analyst tool and the Developer tool

Users also require permissions to run a query against an SQL data service.

StoryAn administrator at HypoStores gets a user account request from a developer and an analyst. They both needaccess to the Developer and Analyst tools.


¨ Create users to log in to the Developer and Analyst tools.

¨ Grant user privileges to access the Analyst tool and to create projects in the Analyst and Developer tools.

¨ Grant permissions on an SQL data service. Users require permissions to run a query against an SQL dataservice.

Repeat the task for each user account that you need to create.

23


¨ You have completed lessons 1 and 2 in this tutorial.

¨ Before you can grant permissions, an application with an SQL Data Service must be deployed to a DataIntegration Service.


Task 1. Create a UserIn this task, you create user accounts that can be used to log in to application clients.

1. In the Administrator tool, click the Security tab.

2. On the Security tab Actions menu, click Create User.

3. Enter the following required fields:

Field Description

Login Name Login name for the user account.

The name is not case sensitive and cannot exceed 128 characters. It cannot include a tab,newline character, or the following special characters:

, + " \ < > ; / * % ?

The name can include an ASCII space character except for the first and last character. Allother space characters are not allowed.

Password Password for the user account.

Confirm Password Enter the password again to confirm. You must retype the password.

Full Name Full name for the user account.

4. Click OK.

5. Complete steps 1 through 4 for each user that you want to create.You created user accounts that can be used to log into application clients, such as the Administrator tool,Developer tool, or the Analyst tool.

Task 2. Grant PrivilegesIn this task, you grant user privileges that are necessary to access the Analyst tool and create projects in theAnalyst and Developer tools.

1. In the Administrator tool, click the Security tab.

2. In the Users section of the Navigator, select the user you created in “Task 1. Create a User” on page 24.

3. In the contents panel, click the Privileges tab.

24 Chapter 4: Lesson 3. Setting Up Informatica Users

4. Click Edit.

The Edit Roles and Privileges dialog box appears.

5. Select the Privileges tab.

6. Select the following privileges:

Privilege Name Location Description

License Access for InformaticaAnalyst

service name - AnalystTool >Analyst Tool Administration >License Access forInformatica Analyst

Required to access the Analyst tool.

MRS_CREATE_PROJECT service name - PRSService >Administration >MRS_CREATE_PROJECT

Required to create projects in the Developer tooland Analyst tool.

7. Click OK.Provide the user names to each user who will complete lessons in the Developer tool or the Analyst tool tutorials.

Task 3. Grant PermissionsIn this task, you grant permissions on an SQL data service to user.

To complete this task, a Data Integration Service must have an application with an SQL data service. The userwho completes lesson 4 in the Data Services tutorial needs this permission.


2. In the Navigator, select a Data Integration Service.

3. Click the Applications view.

4. In the contents panel, expand an application.

Objects within the application appear in the contents panel.

5. Click on an SQL data service.

The properties of the SQL Data Service appear in the details panel.

6. On the Domain tab Actions menu, click Stop SQL Data Service.

7. In the details panel, click the Permissions view.

8. Click Add Users.

9. In the Users section, select the user you created in “Task 1. Create a User” on page 24.

10. In the Permission section, select all the permission options.

11. Click OK.

Task 3. Grant Permissions 25

Setting Up Informatica Users SummaryIn this lesson, you learned that users can perform tasks in Informatica client applications based on their privilegesand permissions.

You created users and granted privileges and permissions.

26 Chapter 4: Lesson 3. Setting Up Informatica Users

C H A P T E R 5

Lesson 4. Monitoring Jobs andApplications


¨ Monitoring Jobs and Applications Overview, 27

¨ Task 1. View Profile and Scorecard Jobs, 28

¨ Task 2. View Connections to an SQL Data Service, 28

¨ Task 3. View Requests for an SQL Data Service, 29

¨ Monitoring Jobs and Applications Summary, 29

Monitoring Jobs and Applications OverviewUse the Monitoring tab to monitor jobs and applications that run on a Data Integration Service.

The Data Integration Service runs jobs and applications. A job is a profile, scorecard, mapping, SQL data service,preview or reference table process that is running or has previously run. An application is an object that containsone or more SQL data services, mappings, or data objects.

The Navigator displays a container for jobs and for each application that is deployed to the Data IntegrationService. Under each application is a container for SQL data services, deployed mappings, and data objects.

When you view jobs for a Data Integration Service, the contents panel displays information such as Job ID, State,and Elapsed Time.

An SQL data service connection is a connection from an external client. When you view connections to an SQLdata service, the contents panel displays information such as the connection ID, state, and elapsed time.

Each SQL data service connection can have multiple requests. When you view a request for an SQL data service,the contents panel displays information such as the request ID, state, and elapsed time.

StoryAn administrator at HypoStores wants to view the status of jobs and SQL data services running on a DataIntegration Service.

27

ObjectiveIn this lesson, you complete the following tasks:

¨ View running and previously run jobs for a Data Integration Service to check for failures.

¨ View connections to an SQL data service to check for active and timed out connections.

¨ View requests for an SQL data service to view running requests.

PrerequisitesBefore you start this lesson, verify the following prerequisite:

¨ Developers and analysts are running jobs and SQL data services on a Data Integration Service in the domain.


Task 1. View Profile and Scorecard JobsIn this task, you view jobs for profiles and scorecards that are running on a Data Integration Service.

To see profile and scorecard jobs, the Data Integration Service must be running profiles or scorecards.

1. In the Administrator tool, click the Monitoring tab.

2. In the Navigator, expand a Data Integration Service and then select Jobs.

The contents panel displays jobs for the selected Data Integration Service.

3. Select a job in the contents panel.

The details panel displays details on each job you select in the contents panel.

Task 2. View Connections to an SQL Data ServiceIn this task, you use the Monitoring tab to view connections to an SQL Data Service.


2. In the Navigator, expand a Data Integration Service.

A list of applications appears in the Navigator.

3. In the Navigator, expand an application under Data Integration Services, and then select SQL Data Services.

A list of SQL data services appears in the contents panel.

4. In the contents panel, select the name of the SQL data service.

The Properties view of the SQL data service displays in the contents panel.

5. In the contents panel, click the Connections view.

Connections to the SQL data service appear in the contents panel.

6. In the contents panel, select a connection to view connection properties in the details panel.

28 Chapter 5: Lesson 4. Monitoring Jobs and Applications

Task 3. View Requests for an SQL Data ServiceIn this task, you use the Monitoring tab to view requests for an SQL data service.


2. In the Navigator, expand a Data Integration Service.

A list of applications display in the contents panel.

3. In the Navigator, expand an application under the Data Integration Services and then select SQL DataServices.

A list of SQL data services appears in the contents panel.

4. In the contents panel, select the name of the SQL data service.

The Properties view of the SQL Data Service displays in the contents panel.

5. In the contents panel, click the Requests view.

Requests for the SQL Data Service appear in the contents panel.

6. In the contents panel, select a request to view request properties in the details panel.

Monitoring Jobs and Applications SummaryIn this lesson you learned that you can view jobs, SQL data service connections, and SQL data service requestsfor a Data Integration Service.

You viewed jobs that were running on a Data Integration Service. You also viewed connections and requests foran SQL data service.

Task 3. View Requests for an SQL Data Service 29

Part II: Getting Started withInformatica Analyst


¨ Lesson 1. Setting Up Informatica Analyst, 31

¨ Lesson 2. Creating Data Objects, 34

¨ Lesson 3. Creating Quick Profiles, 37

¨ Lesson 4. Creating Custom Profiles, 40

¨ Lesson 5. Creating Expression Rules, 43

¨ Lesson 6. Creating and Running Scorecards, 46

¨ Lesson 7. Creating Reference Tables from Profile Columns, 50

¨ Lesson 8. Creating Reference Tables, 53

30

C H A P T E R 6

Lesson 1. Setting Up InformaticaAnalyst


¨ Setting Up Informatica Analyst Overview, 31

¨ Task 1. Log In to Informatica Analyst, 32

¨ Task 2. Create a Project, 32

¨ Task 3. Create a Folder, 33

¨ Setting Up Informatica Analyst Summary, 33

Setting Up Informatica Analyst OverviewBefore you start the lessons in this tutorial, you must set up the Analyst tool. To set up the Analyst tool, log in tothe Analyst tool and create a project and a folder to store your work.

The Informatica domain is a collection of nodes and services that define the Informatica environment. Services inthe domain include the Analyst Service and the Model Repository Service. The Analyst Service runs the Analysttool, and the Model Repository Service manages the Model repository. When you work in the Analyst tool, theAnalyst tool stores the objects that you create in the Model repository.

You must create a project before you can create objects in the Analyst tool. A project contains objects in theAnalyst tool. A project can also contain folders that store related objects, such as objects that are part of the samebusiness requirement.


¨ Log in to the Analyst tool.

¨ Create a project to store the objects that you create in the Analyst tool.

¨ Create a folder in the project that can store related objects.

31


¨ An administrator has configured a Model Repository Service and an Analyst Service in the Administrator tool.

¨ You have the host name and port number for the Analyst tool.

¨ You have a user name and password to access the Analyst Service. You can get this information from anadministrator.


Task 1. Log In to Informatica AnalystLog in to the Analyst tool to begin the tutorial.

1. Start a Microsoft Internet Explorer or Mozilla Firefox browser.

2. In the Address field, enter the URL for Informatica Analyst:http[s]://<host name>:<port number>/AnalystTool

3. On the login page, enter the user name and password.

4. Select Native or the name of a specific security domain.

The Security Domain field appears when the Informatica domain contains an LDAP security domain. If you donot know the security domain that your user account belongs to, contact the Informatica domain administrator.

5. Click Login.

The welcome screen appears.

6. Click Close to exit the welcome screen and access the Analyst tool.

Task 2. Create a ProjectIn this task, you create a project to contain the objects that you create in the Analyst tool. Create a tutorial projectto contain the folder for the data quality project.

1. In the Analyst tool, select the Projects folder in the Project navigator.

The Project navigator is the left pane in the Analyst interface.

2. Click Actions > New Project in the Project navigator.

The New Project window appears.

3. Enter your name prefixed by "Tutorial_" as the name of the project.

4. Verify that Unshared is selected.

5. Click OK.

32 Chapter 6: Lesson 1. Setting Up Informatica Analyst

Task 3. Create a FolderIn this task, you create a folder to store related objects. You can create a folder in a project or another folder.Create a folder named Customers to store the objects related to the data quality project.

1. In the Project navigator, select the tutorial project.

2. Click Actions > New Folder

3. Enter Customers for the folder name.

4. Click OK.

The folder appears under the tutorial project.

Setting Up Informatica Analyst SummaryIn this lesson, you learned that the Analyst tool stores objects in projects and folders. A Model repository containsthe projects and folders. The Analyst Service runs the Analyst tool. The Model Repository Service manages theModel repository. The Analyst Service and the Model Repository Service are application services in theInformatica domain.

You logged in to the Analyst tool and created a project and a folder.

Now, you can use the Analyst tool to complete other lessons in this tutorial.

Task 3. Create a Folder 33

C H A P T E R 7

Lesson 2. Creating Data ObjectsThis chapter includes the following topics:

¨ Creating Data Objects Overview, 34

¨ Task 1. Create the Flat File Data Object, 35

¨ Task 2. Preview the Data, 35

¨ Creating Data Objects Summary, 36

Creating Data Objects OverviewIn the Analyst tool, a data object is a representation of data based on a flat file or relational database table. Youcreate a flat file or table object and then run a profile against the data in the flat file or relational database table.When you create a flat file data object in the Analyst tool, you can upload the file to the flat file cache on themachine that runs the Analyst tool or you can specify the network location where the flat file is stored.

StoryHypoStores keeps the Los Angeles customer data in flat files. HypoStores needs to profile and analyze the dataand perform data quality tasks.


1. Upload the flat file to the flat file cache location and create a data object.

2. Preview the data for the flat file data object.


¨ You have completed lesson 1 in this tutorial.

¨ You have the LA_Customers.csv flat file. You can download the file here (requires a my.informatica.comaccount).

TimingSet aside 5 to 10 minutes to complete this task.

34

https://my-prod.informatica.com/multimedia/onlinehelp/LA_Customers.csv

Task 1. Create the Flat File Data ObjectIn this task, you use the Add Flat File wizard to create a flat file data object from the LA customer data file.

1. In the Navigator, select the Customers folder in your tutorial project.

Note: You must select the project or folder where you want to create the flat file data object before you cancreate it.

2. Click Actions > New Flat File.

The Add Flat File wizard appears.

3. Select Browse and Upload and click Browse.

4. Browse to the location of LA_customers.csv and click Open.

5. Click Next.

6. Enter LA_Customers for the name of the flat file object and use the default value for the code page.

The Details panel shows the first 100 rows in the flat file.

7. Click Next.

8. Under Specify lines to import, select to import column names from the first non-blank line.

9. Click Show.

The details panel updates to show the column headings from the first row.

10. Click Next.

The Column Attributes panel shows the datatype, precision, scale, and format for each column.

11. For the CreateDate and MiscDate columns, click the Data Type cell and change the datatype to datetime.

12. Click Finish.

The data object appears in the folder contents for the Customers_LA folder.

Task 2. Preview the DataIn this task, you preview the data for the flat file data object to review the structure and content of the data.


The contents of the folder appear in the Content panel.

2. Click the LA_Customers data object.

The data object opens in a tab. The Analyst tool displays the first 100 rows of the flat file data object in theData preview view.

3. Click the Properties view for the flat file data object.

The Properties view displays the name, description, and location of the data object. It also displays thecolumns and column properties for the data object.

Task 1. Create the Flat File Data Object 35

Creating Data Objects SummaryIn this lesson, you learned that data objects are representations of data based on a flat file or a relationaldatabase source. You learned that you can create a flat file data object and preview the data in it.

You uploaded a flat file and created a flat file data object, previewed the data for the data object, and viewed theproperties for the data object.

After you create a data object, you create a quick profile for the data object in Lesson 3, and you create a customprofile for the data object in Lesson 4.

36 Chapter 7: Lesson 2. Creating Data Objects

C H A P T E R 8

Lesson 3. Creating Quick ProfilesThis chapter includes the following topics:

¨ Creating Quick Profiles Overview, 37

¨ Task 1. Create and Run a Quick Profile, 38

¨ Task 2. View the Profile Results, 38

¨ Creating Quick Profiles Summary, 39

Creating Quick Profiles OverviewA profile is the analysis of data quality based on the content and structure of data. A quick profile is a profile thatyou create with default options. Use a quick profile to get profile results without configuring all columns andoptions for a profile.

Create and run a quick profile to analyze the quality of the data when you start a data quality project. When youcreate a quick profile object, you select the data object and the data object columns that you want to analyze. Aquick profile skips the profile column and option configuration. The Analyst tool performs profiling on the stagedflat file for the flat file data object.

StoryHypoStores wants to incorporate data from the newly-acquired Los Angeles office into its data warehouse. Beforethe data can be incorporated into the data warehouse, it needs to be cleansed. You are the analyst who isresponsible for assessing the quality of the data and passing the information on to the developer who isresponsible for cleansing the data. You want to view the profile results quickly and get a basic idea of the dataquality.


1. Create and run a quick profile for the Customers_LA flat file data object.

2. View the profile results.




37

Task 1. Create and Run a Quick ProfileIn this task, you create a quick profile for all columns in the data object and use default sampling and drilldownoptions.


2. In the Contents panel, click to the right of the link for the Customers_LA data object.

Do not click the link for the object.

3. Click Actions > New Profile.

The New Profile wizard appears.

4. Select Quick Profile.

5. Click Save and Run to create and run the profile.

The Analyst tool creates the profile in the same project and folder as the data object.

The profile results for the quick profile appear in a new tab after you save and run the profile.

Task 2. View the Profile ResultsIn this task, you use Column Profiling view for the LA_Customers profile to get a quick overview of the profileresults.

The following table describes the information that appears for each column in a profile:


Name Name of the column in the profile.

Unique Values Number of unique values for the column, expressed as a number.

Unique % Percentage of unique values for the column.

Null Values Number of null values for the column.

Null % Percentage of column values that are null.

Inferred Data Type Datatype derived from the values for the column.

Preview Column values that appear when you drill down to individual rows.

1. Click the header for the Null Values column to sort the values.

Notice that the Address2, Address3, City2, CreateDate, and MiscDate columns have 100% null values.

In Lesson 4, you create a custom profile to exclude these columns.

2. Click the Full Name column. The values for the column appear in the Values view.

Notice that the first and last names do not appear in separate columns.

38 Chapter 8: Lesson 3. Creating Quick Profiles

In Lesson 5, you create a rule to separate the first and last names into separate columns.

3. Click the CustomerTier column.

Notice that the values for the CustomerTier are inconsistent.

In Lesson 6, you create a scorecard to score the CustomerTier values. In Lesson 7, you create a referencetable that a developer can use to standardize the CustomerTier values.

4. Click the State column and then click the Patterns view.

Notice that 483 columns have a pattern of XX, which indicate valid values. Seventeen values are not validbecause they do not match the valid pattern.

In Lesson 6, you create a scorecard to score the State values.

Creating Quick Profiles SummaryIn this lesson, you learned that a quick profile shows profile results without configuring all columns and rowsampling options for a profile. You learned that you create and run a quick profile to analyze the quality of the datawhen you start a data quality project. You also learned that the Analyst tool performs profiling on the staged flatfile for the flat file data object.

You created a quick profile and analyzed the profile results. You got more information about the columns in theprofile, including null values and datatypes. You also used the column values and patterns to identify data qualityissues.

After you analyze the results of a quick profile, you can complete the following tasks:

¨ Create a custom profile to exclude columns from the profile and only include the columns you are interested in.

¨ Create an expression rule to create virtual columns and profile them.

¨ Create a reference table to include valid values for a column.

Creating Quick Profiles Summary 39

C H A P T E R 9

Lesson 4. Creating Custom ProfilesThis chapter includes the following topics:

¨ Creating Custom Profiles Overview, 40

¨ Task 1. Create a Custom Profile, 41

¨ Task 2. Run the Profile, 41

¨ Task 3. Drill Down on Profile Results, 42

¨ Creating Custom Profiles Summary, 42

Creating Custom Profiles OverviewA profile is the analysis of data quality based on the content and structure of data. A custom profile is a profile thatyou create when you want to configure the columns, sampling options, and drilldown options for faster profiling.Configure sampling options to select the sample rows in the flat file. Configure drilldown options to drill down torecords in the profile results and drilldown to data rows in the source data or staged data.

You create and run a profile to analyze the quality of the data when you start a data quality project. When youcreate a profile object, you select the data object and the data object columns that you want to profile, configurethe sampling options, and configure the drilldown options.

StoryHypoStores needs to incorporate data from the newly-acquired Los Angeles office into its data warehouse.HypoStores wants to access the quality of the customer tier data in the LA customer data file. You are the analystwho is responsible for assessing the quality of the data and passing the information on to the developer who isresponsible for cleansing the data.


1. Create a custom profile for the flat file data object and exclude the columns with null values.

2. Run the profile to analyze the content and structure of the CustomerTier column.

3. Drill down into the rows for the profile results.


¨ You have completed lessons 1, 2, and 3 in this tutorial.


40

Task 1. Create a Custom ProfileIn this task, you use the New Profile wizard to create a custom profile. When you create a profile, you select thedata object and the columns that you want to profile. You also configure the sampling and drill down options.


2. Click Actions > New Profile.

The New Profile wizard appears and displays the option to create a custom profile.

3. Click Next.

4. Enter Profile_LA_Customers_Custom for the name.

5. Verify that the location in the Location panel. The location shows the tutorial project and the Customersfolder.

The Profiles panel shows the Profile_LA_Customers quick profile that you created in lesson 3.

6. Click Next.

7. In the Sources panel, select the LA_Customers data object.

The Columns panel shows the columns for the data object.

8. Click Next.

9. In the Columns panel, clear the Address2, Address3, City2, CreateDate, and MiscDate columns.

10. In the Sampling Options panel, select the All Rows option.

11. In the Drilldown Options panel, verify that Enable Row Drilldown is selected and select on staged data forthe Drilldown option.

12. Click Save.

The Analyst tool creates the profile and displays the profile in another tab.

Task 2. Run the ProfileIn this task, you run a profile to perform profiling on the data object and display the profile results. The Analyst toolperforms profiling on the staged flat file for the flat file data object.


2. In the contents panel, click the Profile_LA_Customers_Custom link.

The profile appears in a tab.

3. Click Actions > Run Profile.

The Column Profile window appears.

4. In the Columns panel, select Name to select all columns to profile.

5. In the Sampling Options panel, choose to include the default options.

6. In the Drilldown Options panel, choose to include the default options.

7. Click Run.

The Analyst tool performs profiling on the data object and displays the profile results.

Task 1. Create a Custom Profile 41

Task 3. Drill Down on Profile ResultsIn this task, you drill down on the CustomerTier column values to see the underlying rows in the data object for theprofile.


2. Click the Profile_LA_Customers_Custom profile.

The profile opens in a tab.

3. In the Column Profiling view, click the Preview header to clear all columns.

4. Select the CustomerTier, FullName, and Company columns.

5. In the Column Profiling view, select the CustomerTier column.

The values for the column appear in the Values view.

6. Use the shift key to select the Diamond, Ruby, Emerald, and Bronze values.

The rows for the columns with a value of Diamond, Ruby, Emerald, and Bronze appear in the Drilldownpanel. Only the selected columns appear in the Drilldown panel.

7. In the Column Profiling view, enable the preview option for the CustomerID column and select the Diamond,Ruby, Emerald, and Bronze values in the Values view.

The underlying rows in the Drilldown panel now include the CustomerID column. The title bar for theDrilldown panel shows the logic used for the underlying columns.

Creating Custom Profiles SummaryIn this lesson, you learned that you can configure the columns that get profiled and that you can configure thesampling and drilldown options. You learned that you can drill down to see the underlying rows for column valuesand that you can configure the columns that are included when you view the column values.

You created a custom profile that included the CustomerTier column, ran the profile, and drilled down to theunderlying rows for the CustomerTier column in the results.

Use the custom profile object to create an expression rule in lesson 5. If you have Data Quality or Data Explorer,you can create a scorecard in lesson 6.

42 Chapter 9: Lesson 4. Creating Custom Profiles

C H A P T E R 1 0

Lesson 5. Creating ExpressionRules


¨ Creating Expression Rules Overview, 43

¨ Task 1. Create Expression Rules and Run the Profile, 44

¨ Task 2. View the Expression Rule Output, 44

¨ Task 3. Edit the Expression Rules, 45

¨ Creating Expression Rules Summary, 45

Creating Expression Rules OverviewExpression rules use expression functions and source columns to define rule logic. You can create expressionrules and add them to a profile in the Analyst tool. An expression rule can be associated with one or more profiles.

The output of an expression rule is a virtual column in the profile. The Analyst tool profiles the virtual column whenyou run the profile.

You can use expression rules to validate source columns or create additional source columns based on the valueof the source columns.

StoryHypoStores wants to incorporate data from the newly-acquired Los Angeles office into its data warehouse.HypoStores wants to analyze the customer names and separate customer names into first name and last name.HypoStores wants to use expression rules to parse a column that contains first and last names into separatevirtual columns and then profile the columns. HypoStores also wants to make the rules available to other analystswho need to analyze the output of these rules.


1. Create expression rules to separate the FullName column into first name and last name columns. You createa rule that separates the first name from the full name. You create another rule that separates the last namefrom the first name. You create these rules for the Profile_LA_Customers_Custom profile.

2. Run the profile and view the output of the rules in the profile.

3. Edit the rules to make them usable for other Analyst tool users.

43


¨ You have completed Lessons 1, 2, 3, and 4.


Task 1. Create Expression Rules and Run the ProfileIn this task, you create two expression rules to parse the FullName column into two virtual columns namedFirstName and LastName. The FirstName and LastName columns are the rule names.

1. In the contents panel, click the Profile_LA_Customers_Custom profile to open it.


2. Click Actions > Add Rule.

The New Rule window appears.

3. Select Create new rule.

4. Click Next.

5. Enter FirstName for the rule name.

6. In the Expression panel, enter the following expression to separate the first name from the Name column:SUBSTR(FullName,1,INSTR(FullName,' ' ,-1,1 ) - 1)

7. Click Validate.

8. Click Save.

The Analyst tool creates the rule and displays it in the Column Profiling view.

9. Repeat steps 2 through 8 and create a rule named LastName and enter the following expression to separatethe last name from the Name column:

SUBSTR(FullName,INSTR(FullName,' ',-1,1),LENGTH(FullName))

Task 2. View the Expression Rule OutputIn this task, you view the output of expression rules that separated first and last names after running a profile.

1. In the contents panel, click Actions > Run Profile.

2. In the Column Profiling view, click Preview in the toolbar to clear all columns.

3. Select the FullName column and the FirstName and LastName rules.

4. Click the FirstName rule.

The values appear in the Values view.

5. Select any value in the Values view.

The values for the FullName column and the FirstName and LastName rules appear in the Drilldown panel.Notice that the FullName column is now separated into first and last names.

44 Chapter 10: Lesson 5. Creating Expression Rules

Task 3. Edit the Expression RulesIn this task, you make the expression rules reusable and available to all Analyst tool users.

1. In the Column Profiling view, select the FirstName rule.

2. Click Actions > Edit .

The Edit Rule window appears.

3. Select Save as a reusable rule in.

By default, the Analyst tool saves the rule in the current profile and folder.

4. Click Save.

5. Repeat steps 1 through 4.The FirstName and LastName rules can now be used by any Analyst tool user to split a column with first and lastnames into separate columns.

Creating Expression Rules SummaryIn this lesson, you learned that expression rules use expression functions and source columns to define rule logic.You learned that the output of an expression rule is a virtual column in the profile. The Analyst tool includes thevirtual column when you run the profile.

You created two expression rules, added them to a profile, and ran the profile. You viewed the output of the rulesand made them available to all Analyst tool users.

Task 3. Edit the Expression Rules 45

C H A P T E R 1 1

Lesson 6. Creating and RunningScorecards


¨ Creating and Running Scorecards Overview, 46

¨ Task 1. Create a Scorecard from the Profile Results, 47

¨ Task 2. Run the Scorecard, 48

¨ Task 3. View the Scorecard, 48

¨ Task 4. Edit the Scorecard, 48

¨ Task 5. Configure Thresholds, 49

¨ Task 6. View Score Trend Charts, 49

¨ Creating and Running Scorecards Summary, 49

Creating and Running Scorecards OverviewA scorecard is the graphical representation of valid values for a column or the output of a rule in profile results.Use scorecards to measure and monitor data quality progress over time.

To create a scorecard, you add columns from the profile to a scorecard and configure the score thresholds. To runa scorecard, you select the valid values for the column and run the scorecard to see the scores for the columns.

Scorecards display the value frequency for columns in a profile as scores. Scores reflect the percentage of validvalues for a column.

StoryHypoStores wants to incorporate data from the newly-acquired Los Angeles office into its data warehouse. Beforethey merge the data they want to make sure that the data in different customer tiers and states is analyzed fordata quality. You are the analyst who is responsible for monitoring the progress of performing the data qualityanalysis You want to create a scorecard from the customer tier and state profile columns, configure thresholds fordata quality, and view the score trend charts to determine how the scores improve over time.

46

ObjectivesIn this lesson, you will complete the following tasks:

1. Create a scorecard from the results of the Profile_LA_Customers_Custom profile to view the scores for theCustomerTier and State columns.

2. Run the scorecard to generate the scores for the CustomerTier and State columns.

3. View the scorecard to see the scores for each column.

4. Edit the scorecard to specify different valid values for the scores.

5. Configure score thresholds and run the scorecard.

6. View score trend charts to determine how scores improve over time.


¨ You have completed lessons 1 through 5 in this tutorial.

TimingSet aside 15 minutes to complete the tasks in this lesson.

Task 1. Create a Scorecard from the Profile ResultsIn this task, you create a scorecard from the Profile_LA_Customers_Custom profile to score the CustomerTier andState column values.

1. Open the Profile_LA_Customers_Custom profile.

2. Click Actions > Add to Scorecard.

The Add to Scorecard wizard appears.

3. Select the CustomerTier and the State columns to add to the scorecard.

4. Click Next.

5. Click New to create a scorecard.

The New Scorecard window appears.

6. Enter sc_LA_Customer for the scorecard name, and navigate to the Customers folder for the scorecardlocation.

7. Click OK and click Next.

8. Select the CustomerTier score in the Scores panel and select the Is Valid column for all values in the Scoreusing: Values panel.

9. Select the State score in the Scores panel and select the Is Valid column for those values that have twoletter state codes in the Score using: Values panel.

10. For each score in the Scores panel, accept the default settings for the score thresholds in Score Settingspanel.

11. Click Finish.

Task 1. Create a Scorecard from the Profile Results 47

Task 2. Run the ScorecardIn this task, you run the sc_LA_Customer scorecard to generate the scores for the CustomerTier and Statecolumns.

1. Click the sc_LA_Customer scorecard to open it.

The scorecard appears in a tab.

2. Click Actions > Run Scorecard.

The Scorecard view displays the scores for the CustomerTier and State columns.

Task 3. View the ScorecardIn this task, you view the sc_LA_Customer scorecard to see the scores for the CustomerTier and State columns.

1. Select the State column that contains the State score you want to view.

2. Click Actions > Show Rows.

The valid scores for the State column appear in the Valid view. Click Invalid to view the invalid scores for theState column. In the Scores panel, you can view the score name and score percentage. You can view thescore displayed as a bar, the data object of the score, and the source and source type of the score.

3. Repeat steps 2 through 3 for the CustomerTier column.

All scores for the CustomerTier column are valid.

Task 4. Edit the ScorecardIn this task, you will edit the sc_LA_Customer scorecard to specify the Ruby value as not valid for theCustomerTier score.

1. Click Actions > Edit.

The Edit Scorecard window appears.

2. Select the CustomerTier score in the Scores panel.

3. In the Score using: Values panel, clear Ruby from the Is Valid column.

Accept the default settings in the Score Settings panel.

4. Click Save to save the changes to the scorecard and run it.

5. View the CustomerTier score again.

48 Chapter 11: Lesson 6. Creating and Running Scorecards

Task 5. Configure ThresholdsIn this task, you configure thresholds for the State score in the sc_LA_Customer scorecard to determine theacceptable ranges for the data in the State column. Values with a two letter code, such as CA are acceptable, andcodes with more than two letters such as Calif are not acceptable.

1. In the Edit Scorecard window, select the State score in the Scores panel.

2. In the Score Settings panel, enter the following ranges for the Good and Unacceptable scores in SetCustom Thresholds for this Score: 90 to 100% Good; 0 to 50% Unacceptable. 51% to 89% are Acceptable.

The thresholds represent the lower bounds of the acceptable and good ranges.

3. Click Save to save the changes to the scorecard and run it.

In the Scores panel, view the changes to the score percentage and the score displayed as a bar for the Statescore.

Task 6. View Score Trend ChartsIn this task, you view the trend chart for the State score. You can view trend charts to monitor scores over time.


2. Click the sc_LA_Customer scorecard to open it.

The scorecard appears in a tab.

3. In the Scorecard view, select the State score.

4. Click Actions > Show Trend Chart.

The Trend Chart Detail window appears. You can view the Good, Acceptable, and Unacceptable thresholdsfor the score. The thresholds change each time you run the scorecard after editing the values for scores in thescorecard.

Creating and Running Scorecards SummaryIn this lesson, you learned that you can create a scorecard from the results of a profile. A scorecard contains thecolumns from a profile. You learned that you can run a scorecard to generate scores for columns. You edited ascorecard to configure valid values and set thresholds for scores. You also learned how to view the score trendchart.

You created a scorecard from the CustomerTier and State columns in a profile to analyze data quality for thecustomer tier and state columns. You ran the scorecard to generate scores for each column. You edited thescorecard to specify different valid values for scores. You configured thresholds for a score and viewed the scoretrend chart.

Task 5. Configure Thresholds 49

C H A P T E R 1 2

Lesson 7. Creating ReferenceTables from Profile Columns


¨ Creating Reference Tables from Profile Columns Overview, 50

¨ Task 1. Create a Reference Table from Profile Columns, 51

¨ Task 2. Edit the Reference Table, 52

¨ Creating Reference Tables from Profile Columns Summary, 52

Creating Reference Tables from Profile ColumnsOverview

A reference table contains reference data that you can use to standardize source data. Reference data caninclude valid and standard values. Create reference tables to establish relationships between source data valuesand the valid and standard values.

You can create a reference table from the results of a profile. After you create a reference table, you can edit thereference table to add columns or rows and add or edit standard and valid values. You can view the changesmade to a reference table in an audit trail.

StoryHypoStores wants to profile the data to uncover anomalies and standardize the data with valid values. You are theanalyst who is responsible for standardizing the valid values in the data. You want to create a reference tablebased on valid values from profile columns.


1. Create a reference table from the CustomerTier column in the Profile_LA_Customers_Custom profile byselecting valid values for columns.

2. Edit the reference table to configure different valid values for columns.


¨ You have completed lessons 1 through 6 in this tutorial.

50


Task 1. Create a Reference Table from Profile ColumnsIn this task, you create a reference table and add the CustomerTier column from theProfile_LA_Customers_Custom profile to the reference table.

1. Click the Profile_LA_Customers_Custom profile.


2. In the Column Profiling view, select the CustomerTier column that you want to add to the reference table.

You can drill down on the value and pattern frequencies for the CustomerTier column to inspect records thathave non-standard customer category values.

3. In the Values view, select the valid customer tier values you want to add. Use the CONTROL or SHIFT keysto select the following multiple values: Diamond, Gold, Silver, Bronze, Emerald.

4. Click Actions > Add to Reference Table.

The New Reference Table wizard appears.

5. Select the option to Create a new reference table.

6. Click Next.

7. Enter Reftab_CustTier_HypoStores as the table name.

8. Enter a description and set 0 as the default value.

The Analyst tool uses the default value for any table record that does not contain a value.

9. Click Next.

10. In the Column Attributes panel, configure the following column properties for the CustomerTier column:


Name CustomerTier

Datatype String

Precision 10

Scale 0

Description Reference customer tier values

11. Optionally, choose to create a description column for rows in the reference table. Enter the name andprecision for the column.

12. Preview the CustomerTier column values in the Preview panel.

13. Click Next.

The Reftab_CustomerTier_HypoStores reference table name appears. You can enter an optional description.

14. In the Save in panel, select your tutorial project where you want to create the reference table.

The Reference Tables: panel lists the reference tables in the location you select.

Task 1. Create a Reference Table from Profile Columns 51

15. Enter an optional audit note.

16. Click Finish.

Task 2. Edit the Reference TableIn this task, you edit the Reftab_CustomerTier_HypoStores table to add alternate values for the customer tiers.


2. Click the Reftab_CustomerTier_HypoStores reference table.

The reference table opens in a tab.

3. To edit a row, select the row and click Actions > Edit or click the Edit icon.

The Edit Row window appears. Optionally, select multiple rows to add the same alternate value to each row.

4. Enter the following alternate values for the Diamond, Emerald, Gold, Silver, and Bronze rows: 1, 2, 3, 4, 5.

Enter an optional audit note.

5. Click Apply to apply the changes.

Creating Reference Tables from Profile ColumnsSummary

In this lesson, you learned how to create reference tables from the results of a profile to configure valid values forsource data.

You created a reference table from a profile column by selecting valid values for columns. You edited thereference table to configure different valid values for columns.

52 Chapter 12: Lesson 7. Creating Reference Tables from Profile Columns

C H A P T E R 1 3

Lesson 8. Creating ReferenceTables


¨ Creating Reference Tables Overview, 53

¨ Task 1. Create a Reference Table, 54

¨ Creating Reference Tables Summary, 54

Creating Reference Tables OverviewA reference table contains reference data that you can use to standardize source data. Reference data caninclude valid and standard values. Create reference tables to establish relationships between the source datavalues and the valid and standard values.

You can manually create a reference table using the reference table editor. Use the reference table to define andstandardize the source data. You can share the reference table with a developer to use in Standardizer andLookup transformations in the Developer tool.

StoryHypoStores wants to standardize data with valid values. You are the analyst who is responsible for standardizingthe valid values in the data. You want to create a reference table to define standard customer tier codes thatreference the LA customer data. You can then share the reference table with a developer.

ObjectivesIn this lesson, you complete the following task:

¨ Create a reference table using the reference table editor to define standard customer tier codes that referencethe LA customer data.



TimingSet aside 10 minutes to complete the task in this lesson.

53

Task 1. Create a Reference TableIn this task, you will create the Reftab_CustomerTier_Codes reference table to standardize the valid values for thecustomer tier data.

1. in the Navigator, select the Customer folder in your tutorial project where you want to create the referencetable.

2. Click Actions > New Reference Table.

The New Reference Table wizard appears.

3. Select the option to Use the reference table editor.

4. Click Next.

5. Enter the Reftab_CustomerTier_Codes as the table name and enter an optional description and set thedefault value of 0.

The Analyst tool uses the default value for any table record that does not contain a value.

6. For each column you want to include in the reference table, click the Add New Column icon and configurethe column properties for each column.

Add the following column names: CustomerID, CustomerTier, and Status. You can reorder the columns ordelete columns.

7. Click Finish.

8. Open the Reftab_CustomerTier_Codes reference table and click Actions > Add Row to populate eachreference table column with four values.

CustomerID = LA1, LA2, LA3, LA4

CustomerTier = 1, 2, 3, 4, 5.

Status= Active, Inactive

Creating Reference Tables SummaryIn this lesson, you learned how to create reference tables using the reference table editor to create standard validvalues to use with source data.

You created a reference table using the reference table editor to standardize the customer tier values for the LAcustomer data.

54 Chapter 13: Lesson 8. Creating Reference Tables

Part III: Getting Started withInformatica Developer (DataQuality)


¨ Lesson 1. Setting Up Informatica Developer, 56

¨ Lesson 2. Importing Physical Data Objects, 60

¨ Lesson 3. Profiling Data, 64

¨ Lesson 4. Parsing Data, 68

¨ Lesson 5. Standardizing Data , 75

¨ Lesson 6. Validating Address Data, 81

55

C H A P T E R 1 4

Lesson 1. Setting Up InformaticaDeveloper


¨ Setting Up Informatica Developer Overview, 56

¨ Task 1. Start Informatica Developer, 57

¨ Task 2. Add a Domain, 57

¨ Task 3. Add a Model Repository, 58



¨ Task 6. Select a Default Data Integration Service, 59

¨ Setting Up Informatica Developer Summary, 59

Setting Up Informatica Developer OverviewBefore you start the lessons in this tutorial, you must start and set up the Developer tool. To set up the Developertool, you add a domain. You add a Model repository that is in the domain, and you create a project and folder tostore your work. You also select a default Data Integration Service.

The Informatica domain is a collection of nodes and services that define the Informatica environment. Services inthe domain include the Model Repository Service and the Data Integration Service.

The Model Repository Service manages the Model repository. The Model repository is a relational database thatstores the metadata for projects that you create in the Developer tool. A project stores objects that you create inthe Developer tool. A project can also contain folders that store related objects, such as objects that are part of thesame business requirement.

The Data Integration Service performs data integration tasks in the Developer tool.


¨ Start the Developer tool and go to the Developer tool workbench.

¨ Add a domain in the Developer tool.

¨ Add a Model repository so that you can create a project.

¨ Create a project to store the objects that you create in the Developer tool.

56


¨ Select a default Data Integration Service to perform data integration tasks.


¨ You have installed the Developer tool.

¨ You have a domain name, host name, and port number to connect to a domain. You can get this informationfrom a domain administrator.

¨ A domain administrator has configured a Model Repository Service in the Administrator tool.

¨ You have a user name and password to access the Model Repository Service. You can get this informationfrom a domain administrator.

¨ A domain administrator has configured a Data Integration Service.

¨ The Data Integration Service is running.

TimingSet aside 5 to 10 minutes to complete the tasks in this lesson.

Task 1. Start Informatica DeveloperStart the Developer tool to begin the tutorial.

1. Select Start > Programs > Informatica [version] > Client > Developer Client > Launch InformaticaDeveloper from the Windows Start menu.

The Welcome page of the Developer tool appears.

2. Click the Workbench button.

The Developer tool workbench appears.

Task 2. Add a DomainIn this task, you add a domain in the Developer tool to access a Model repository.

1. Click Window > Preferences .

The Preferences dialog box appears.

2. Select Informatica > Domains .

3. Click Add.

The New Domain dialog box appears.

4. Enter the domain name, host name, and port number.

5. Click Finish.

6. Click OK.

Task 1. Start Informatica Developer 57

Task 3. Add a Model RepositoryIn this task, you add the Model repository that you want to use to store projects and folders.

1. Click File > Connect to Repository .

The Connect to Repository dialog box appears.

2. Click Browse to select a Model Repository Service.

3. Click OK.

4. Click Next.

5. Enter your user name and password.

6. Click Finish.

The Model repository appears in the Object Explorer view.

Task 4. Create a ProjectIn this task, you create a project to store objects that you create in the Developer tool. You can create one projectfor all tutorials in this guide.

1. In the Object Explorer view, select a Model Repository Service.

2. Click File > New > Project .

The New Project dialog box appears.


4. Click Finish.

The project appears under the Model Repository Service in the Object Explorer view.

Task 5. Create a FolderIn this task, you create a folder to store related objects. You can create one folder for all tutorials in this guide.

1. In the Object Explorer view, select the project that you want to add the folder to.

2. Click File > New > Folder .

3. Enter a name for the folder.

4. Click Finish.

The Developer tool adds the folder under the project in the Object Explorer view. Expand the project to seethe folder.

58 Chapter 14: Lesson 1. Setting Up Informatica Developer

Task 6. Select a Default Data Integration ServiceIn this task, you select a default Data Integration Service so you can run mappings and preview data.



2. Select Informatica > Data Integration Services .

3. Expand the domain.

4. Select a Data Integration Service.

5. Click Set as Default.

6. Click OK.

Setting Up Informatica Developer SummaryIn this lesson, you learned that the Informatica domain includes the Model Repository Service and Data IntegrationService. The Model Repository Service manages the Model repository. A Model repository contains projects andfolders. The Data Integration Service performs data integration tasks.

You started the Developer tool and set up the Developer tool. You added a domain to the Developer tool, added aModel repository, and created a project and folder. You also selected a default Data Integration Service.

Now, you can use the Developer tool to complete other lessons in this tutorial.

Task 6. Select a Default Data Integration Service 59

C H A P T E R 1 5

Lesson 2. Importing Physical DataObjects


¨ Importing Physical Data Objects Overview, 60

¨ Task 1. Import the Boston_Customers Flat File Data Object, 61

¨ Task 2. Import the LA_Customers Flat File Data Object, 61

¨ Task 3. Importing the All_Customers Flat File Data Object, 62

¨ Importing Physical Data Objects Summary, 63

Importing Physical Data Objects OverviewA physical data object is a representation of data based on a flat file or relational database table. You can import aflat file or relational database table as a physical data object to use as a source or target in a mapping.

StoryHypoStores Corporation stores customer data from the Los Angeles office and Boston office in flat files. You wantto work with this customer data in the Developer tool. To do this, you need to import each flat file as a physicaldata object.

ObjectivesIn this lesson, you import flat files as physical data objects. You also set the source file directory so that the DataIntegration Service can read the source data from the correct directory.




60

Task 1. Import the Boston_Customers Flat File DataObject

In this task, you import a physical data object from a file that contains customer data from the Boston office.

1. In the Object Explorer view, select the tutorial project.

2. Click File > New > Data Object .

The New dialog box appears.

3. Select Physical Data Objects > Flat File Data Object and click Next.

The New Flat File Data Object dialog box appears.

4. Select Create from an Existing Flat File.

5. Click Browse and navigate to Boston_Customers.csv in the following directory: <Informatica InstallationDirectory>\clients\DeveloperClient\Tutorial

6. Click Open.

The wizard names the data object Boston_Customers.

7. Click Next.

8. Verify that the code page is MS Windows Latin 1 (ANSI), superset of Latin 1.

9. Verify that the format is delimited.

10. Click Next.

11. Verify that the delimiter is set to comma.

12. Select Import Field Names from First Line.

13. Click Finish.

The Boston_Customers physical data object appears under Physical Data Objects in the tutorial project.

14. Click the Read view.

15. Click the Runtime tab on the Properties view.

16. Set the Source File Directory to the following directory on the Data Integration Service machine: \Informatica\9.0\server\Tutorial

17. Click File > Save .

Task 2. Import the LA_Customers Flat File Data ObjectIn this task, you import a physical data object from a flat file that contains customer data from the Los Angelesoffice.






Task 1. Import the Boston_Customers Flat File Data Object 61


5. Click Browse and navigate to LA_Customers.csv in the following directory: <Informatica Installation Directory>\clients\DeveloperClient\Tutorial

6. Click Open.

The wizard names the data object LA_Customers.

7. Click Next.



10. Click Next.



13. Click Finish.

The LA_Customers physical data object appears under Physical Data Objects in the tutorial project.





Task 3. Importing the All_Customers Flat File DataObject

In this task, you import a physical data object from a flat file that combines the customer order data from the LosAngeles and Boston offices.





The New Flat File Data Source dialog box appears.


5. Click Browse and navigate to All_Customers.csv in the following directory: <Informatica Installation Directory>\clients\DeveloperClient\Tutorial.

6. Click Open.

The wizard names the data object All_Customers.

7. Click Next.



10. Click Next.


62 Chapter 15: Lesson 2. Importing Physical Data Objects


13. Click Finish.

The All_Customers physical data object appears under Physical Data Objects in the tutorial project.





Importing Physical Data Objects SummaryIn this lesson, you learned that physical data objects are representations of data based on a flat file or a relationaldatabase table.

You created physical data objects from flat files. You also set the source file directory so that the Data IntegrationService can read the source data from the correct directory.

You use the data objects as mapping sources in the data quality lessons.

Importing Physical Data Objects Summary 63

C H A P T E R 1 6

Lesson 3. Profiling DataThis chapter includes the following topics:

¨ Profiling Data Overview, 64

¨ Task 1. Perform a Join Analysis on Two Data Sources, 65

¨ Task 2. View Join Analysis Results, 66

¨ Task 3. Run a Profile on a Data Source, 66

¨ Task 4. View Column Profiling Results, 67

¨ Profiling Data Summary, 67

Profiling Data OverviewA profile is a set of metadata describing the content and structure of a dataset.

Data profiling is often the first step in a project. You can run a profile to evaluate the structure of data and verifythat data columns are populated with the types of information you expect. If a profile reveals problems in data, youcan define steps in your project to fix those problems. For example, if a profile reveals that a column containsvalues of greater than expected length, you can design data quality processes to remove or fix the problem values.

A profile provides the following facts about data:

¨ The number of unique and null values in each column, expressed as a number and a percentage.

¨ The patterns of data in each column, and the frequencies with which these values occur.

¨ Statistics about the column values, such as the maximum and minimum lengths of values and the first and lastvalues in each column.

¨ For join analysis profiles, the degree of overlap between two data columns, displayed as a Venn diagram andas a percentage value. Use join analysis profiles to identify possible problems with column join conditions.

You can run a profile at any stage in a project to measure data quality and to verify that changes to the data meetyour project objectives. You can run a profile on a transformation in a mapping to indicate the effect that thetransformation will have on data.

StoryHypoStores wants to verify that customer data is free from errors, inconsistencies, and duplicate information.Before HypoStores designs the processes to deliver the data quality objectives, it needs to measure the quality ofits source data files and confirm that the data is ready to process.

64


¨ Perform a join analysis on the Boston_Customers data source and the LA_Customers data source.

¨ View the results of the join analysis to determine whether or not you can successfully merge data from the twooffices.

¨ Run a profile on the All_Customers data source.

¨ View the column profiling results to observe the values and patterns contained in the data.



Time Required¨ Set aside 20 minutes to complete this lesson.

Task 1. Perform a Join Analysis on Two Data SourcesIn this task, you perform a join analysis on the Boston_Customers and LA_Customers data sources to view thejoin conditions.

1. In the Object Explorer view, browse to the data objects in your tutorial project.

2. Select the Boston_Customers and LA_Customers data sources.

Tip: Hold down the Shift key to select multiple data objects.

3. Click File > New > Profile .

The New Profile window opens.

4. In the Name field, enter JoinAnalysis.

5. Click Next.

6. Clear all column selections by clicking the check boxes next to the Boston_Customers data source and theLA_Customers data source.

7. Select the CustomerID column in both data sources.

8. Click Next.

9. Click Add to add join conditions.

The Join Condition window opens.

10. In the Columns section, click the New button.

11. Double-click the first row in the left column and select CustomerID.

12. Double-click the first row in the right column and select CustomerID.

13. Click OK.

14. Click Finish.

The JoinAnalysis profile opens in the editor and the profile runs.

Task 1. Perform a Join Analysis on Two Data Sources 65

Task 2. View Join Analysis ResultsIn this task, you view the join analysis results in the Results view of the JoinAnalysis profile.

1. Click Window > Show View > Progress to view the progress of the JoinAnalysis profile.

The Progress view opens.

2. When the Progress view reports that the JoinAnalysis profile finishes running, click the Results view in theeditor.

3. In the Join Profile section, click the first row.

The Details section displays a Venn diagram and a key that details the results of the join analysis.

4. Verify that the Join entry in the key reports a 0% join.A 0% join indicates that none of the CustomerID fields are duplicates, suggesting you can successfully mergethe two data sources.

5. To view the CustomerID values for the LA_Customers data object, double-click the circle labeledLA_Customers in the Venn diagram.

Tip: You can double-click circles in the Venn diagram and squares in the key to view the data rows describedby these items. In cases where circles intersect in the Venn diagram, you can double-click the intersection toview data values common to both data sets.

The Data Viewer displays the CustomerID values contained in the LA_Customers data object.

Task 3. Run a Profile on a Data SourceIn this task, you run a profile on the All_Customers data source to view the content and structure of the data.


2. Select the All_Customers data source.

3. Click File > New > Profile .

The New Profile window opens.

4. In the Name field, enter All_Customers.

5. Click Finish.

The All_Customers profile opens in the editor and the profile runs.

66 Chapter 16: Lesson 3. Profiling Data

Task 4. View Column Profiling ResultsIn this task, you view the column profiling results for the All_Customers data object and examine the values andpatterns contained in the data.

1. Click Window > Show View > Progress to view the progress of the All_Customers profile.

The Progress view opens.

2. When the Progress view reports that the All_Customers profile finishes running, click the Results view in theeditor.

3. In the Column Profiling section, click the CustomerTier column.

The Details section displays all values contained in the CustomerTier column and displays information abouthow frequently the values occur in the dataset.

4. In the Details section, double-click the value Ruby.

The Data Viewer runs and displays the records where the CustomerTier column contains the value Ruby.

5. In the Column Profiling section, click the OrderAmount column.

6. In the Details section, click the Show list and select Patterns.

The Details section shows the patterns found in the OrderAmount column. The string 9(5) in the Patterncolumn refers to records that contain five-figure order amounts. The string 9(4) refers to records containingfour-figure amounts.

7. In the Pattern column, double-click the string 9(4).

The Data Viewer runs and displays the records where the OrderAmount column contains a four-figure orderamount.

8. In the Details section, click the Show list and select Statistics.

The Details section shows statistics for the OrderAmount column, including the average value, the standarddeviation, maximum and minimum lengths, the five most common values, and the five least common values.

Profiling Data SummaryIn this lesson, you learned that a profile provides information about the content and structure of the data.

You learned that you can perform a join analysis on two data objects and view the degree of overlap between thedata objects. You also learned that you can run a column profile on a data object and view values, patterns, andstatistics that relate to each column in the data object.

You created the JoinAnalysis profile to determine whether data from the Boston_Customers data object can mergewith the data in the LA_Customers data object. You viewed the results of this profile and determined that all valuesin the CustomerID column are unique and that you can merge the data objects successfully.

You created the All_Customers profile and ran a column profile on the All_Customers data object. You viewed theresults of this profile to discover values, patterns, and statistics for columns in the All_Customers data object.Finally, you ran the Data Viewer to view rows containing values and patterns that you selected, enabling you toverify the quality of the data.

Task 4. View Column Profiling Results 67

C H A P T E R 1 7

Lesson 4. Parsing DataThis chapter includes the following topics:

¨ Parsing Data Overview, 68

¨ Task 1. Create a Target Data Object, 69

¨ Task 2. Create a Mapping to Parse Data, 71

¨ Task 3. Run a Profile on the Parser Transformation, 73

¨ Task 4. Run the Mapping, 73

¨ Task 5. View the Mapping Output, 73

¨ Parsing Data Summary, 74

Parsing Data OverviewYou can parse data to identify logical elements in one input column and write these elements to multiple outputcolumns.

Parsing data allows you to have greater control over the data quality of individual logical elements within data. Forexample, consider a data field that contains a person's full name, Bob Smith. You can use the Parsertransformation to split the full name into separate data columns containing the first name and the last name. Afteryou parse the data into separate logical elements, you can create custom data quality operations for each element.

You can configure the Parser transformation to use token sets to parse data columns into component strings. Atoken set identifies logical elements within data, such as words, ZIP codes, phone numbers, and Social Securitynumbers.

You can also use the Parser transformation to parse data that matches reference table entries or custom regularexpressions that you enter.

StoryHypoStores wants the format of customer data files from the Los Angeles office to match the format of the datafiles from the Boston office. The customer data from the Los Angeles office stores the customer name in aFullName column, while the customer data from the Boston office stores the customer name in separateFirstName and LastName columns. HypoStores needs to parse the Los Angeles FullName column data into firstnames and last names so that the format of the Los Angeles data will match the format of the Boston data.

68


¨ Create and configure an LA_Customers_tgt data object to contain parsed data.

¨ Create a mapping to parse the FullName column into separate FirstName and LastName columns.

¨ Add the LA_Customers data object to the mapping to connect to the source data.

¨ Add the LA_Customers_tgt data object to the mapping to create a target data object.

¨ Add a Parser transformation to the mapping and configure it to use a token set to parse full names into firstnames and last names.

¨ Run a profile on the Parser transformation to review the data before you generate the target data source.

¨ Run the mapping to generate parsed names.

¨ Run the Data Viewer to view the mapping output.




Task 1. Create a Target Data ObjectIn this task, you create an LA_Customers_tgt data object that you can write parsed names to.

To create a target data object, complete the following steps:

1. Create an LA_Customers_tgt data object based on the LA_Customers.csv file.

2. Configure the read and write options for the data object, including file locations and file names.

3. Add Firstname and Lastname columns to the LA_Customers_tgt data object.

Step 1. Create an LA_Customers_tgt Data ObjectIn this step, you create an LA_Customers_tgt data object based on the LA_Customers.csv file.


The New Data Object window opens.

2. Select Flat File Data Object and click Next.

3. Verify that Create from an Existing Flat File is selected.


5. Click Open.

6. In the Name field, enter LA_Customers_tgt.

7. Click Next.

8. Click Next.

Task 1. Create a Target Data Object 69

9. In the Preview Options section, select Import Field Names from First Line and click Next.

10. Click Finish.

The LA_Customers_tgt data object appears in the editor.

Step 2. Configure Read and Write OptionsIn this step, you configure the read and write options for the LA_Customers_tgt data object, including file locationsand file names.

1. Verify that the LA_Customers_tgt data object is open in the editor.

2. In the editor, select the Read view.

3. Click Window > Show View > Properties .

4. In the Properties view, select the Runtime view.

5. In the Value column, double-click the source file name and type LA_Customers_tgt.csv.

6. In the Value column, double-click to highlight the source file directory.

7. Right-click the highlighted name and select Copy.

8. In the editor, select the Write view.


10. In the Value column, double-click the Output file directory entry.

11. Right-click and select Paste to paste the directory location you copied from the Read view.

12. In the Value column, double-click the Header options entry and choose Output Field Names.

13. In the Value column, double-click the Output file name entry and type LA_Customers_tgt.csv.

14. Click File > Save to save the data object.

Step 3. Add Columns to the Data ObjectIn this step, you add Firstname and Lastname columns to the LA_Customers_tgt data object.


2. Double-click the LA_Customers_tgt data object.

The LA_Customers_tgt data object opens in the editor.

3. Verify that the Overview view is selected.

4. Select the FullName column and click the New button to add a column.

A column named FullName1 appears.

5. Rename the column to Firstname. Click the Precision field and enter "30."

6. Select the Firstname column and click the New button to add a column.

A column named FirstName1 appears.

7. Rename the column to Lastname. Click the Precision field and enter "30."

8. Click File > Save to save the data object .

70 Chapter 17: Lesson 4. Parsing Data

Task 2. Create a Mapping to Parse DataIn this task, you create a mapping and configure it to use data objects and a Parser transformation.

To create a mapping to parse data, complete the following steps:

1. Create a mapping.

2. Add source and target data objects to the mapping.

3. Add a Parser transformation to the mapping.

4. Configure the Parser transformation to parse the source column containing the full customer name intoseparate target columns containing the first name and last name.

Step 1. Create a MappingIn this step, you create and name the mapping.

1. In the Object Explorer view, select your tutorial project.

2. Click File > New > Mapping .

The New Mapping window opens.

3. In the Name field, enter ParserMapping.

4. Click Finish.

The mapping opens in the editor.

Step 2. Add Data Objects to the MappingIn this step, you add the LA_Customers data object and the LA_Customers_tgt data object to the mapping.


2. Select the LA_Customers data object and drag it to the editor.

The Add Physical Data Object to Mapping window opens.

3. Verify that Read is selected and click OK.

The data object appears in the editor.


5. Select the LA_Customers_tgt data object and drag it to the editor.


6. Select Write and click OK.


7. Select the CustomerID, CustomerTier, and FullName ports in the LA_Customers data object. Drag the portsto the CustomerID port in the LA_Customers_tgt data object.

Tip: Hold down the CTRL key to select multiple ports.

The ports of the LA_Customers data object connect to corresponding ports in the LA_Customers_tgt dataobject.

Task 2. Create a Mapping to Parse Data 71

Step 3. Add a Parser Transformation to the MappingIn this step, you add a Parser transformation to the ParserMapping mapping.

1. Select the editor containing the ParserMapping mapping.

2. In the Transformation palette, select the Parser transformation.

3. Click the editor.

The New Parser Transformation window opens.

4. Verify that Token Parser is selected and click Finish.

The Parser transformation appears in the editor.

5. Select the FullName port in the LA_Customers data object and drag the port to the Input group of the Parsertransformation.

The FullName port appears in the Parser transformation and is connected to the FullName port in the dataobject.

Step 4. Configure the Parser TransformationIn this step, you configure the Parser transformation to parse the column containing the full customer name intoseparate columns that contain the first name and last name.


2. Click the Parser transformation.


4. In the Properties view, select the Configuration view.

5. Click Add.

The Add a Parsing Operation window opens.

6. Verify that Parse using token set is selected and click Browse.

The Select Token Sets window opens.

7. Select the Undefined token set and click OK.

8. In the Enter Parsing Details section, click the Add button to add an output.

An output named Undefined_output appears in the Output field.

9. Click OK.

10. Click Select to select a delimiter.

The Select Delimeters window opens.

11. Select the Space delimiter and click OK.

12. In the Parser transformation, click the Undefined_output port and drag it to the FirstName port in theLA_customers_tgt data object.

A connection appears between the ports.

13. In the Parser transformation, click the OverflowField port and drag it to the LastName port in theLA_customers_tgt data object.


14. Click File > Save to save the mapping.


Task 3. Run a Profile on the Parser TransformationIn this task, you run a profile on the Parser transformation to verify that you configured the Parser transformationto parse the full name correctly.


2. Right-click the Parser transformation and select Profile Now.

The profile runs and opens in the editor.

3. In the editor, click the Results view to display the result of the profiling operation.

4. In the Profiling section, select the Undefined_output column to display information about the column theDetails Section.

The values contained in the Undefined_output column appear in the details section, along with frequency andpercentage statistics for each value.

5. View the data and verify that only first names appear in the Undefined_output column.

Task 4. Run the MappingIn this task, you run the mapping to create the mapping output.


2. Click Run > Run Mapping .

The mapping runs and writes output to the LA_Customers_tgt.csv file.

Task 5. View the Mapping OutputIn this task, you run the Data Viewer to view the mapping output.

1. In the Object Explorer view, locate the LA_Customers_tgt data object in your tutorial project and double clickthe data object.

The data object opens in the editor.

2. Click Window > Show View > Data Viewer .

The Data Viewer view opens.

3. In the Data Viewer view, click Run.

The Data Viewer runs and displays the data.

4. Verify that the FirstName and LastName columns display correctly parsed data.

Task 3. Run a Profile on the Parser Transformation 73

Parsing Data SummaryIn this lesson, you learned that parsing data identifies logical elements in one input column and writes theseelements to multiple output columns.

You learned that you can use the Parser transformation to parse data. You also learned that you can create aprofile for any transformation in a mapping to analyze the output from that transformation. Finally, you learned thatyou can view mapping output using the Data Viewer.

You created and configured the LA_Customers_tgt data object to contain parsed output. You created a mapping toparse the data. In this mapping, you configured a Parser transformation with a token set to parse first names andlast names from the FullName column in the Los Angeles customer file. You configured the mapping to write theparsed data to the Firstname and Lastname columns in the LA_Customers_tgt data object. You also ran a profileto view the output of the transformation before running the mapping. Finally, you ran the mapping and used theData Viewer to view the new data columns in the LA_Customers_tgt data object.


C H A P T E R 1 8

Lesson 5. Standardizing DataThis chapter includes the following topics:

¨ Standardizing Data Overview, 75

¨ Task 1. Create a Target Data Object, 76

¨ Task 2. Create a Mapping to Standardize Data, 77



¨ Standardizing Data Summary, 80

Standardizing Data OverviewStandardizing data improves data quality by removing errors and inconsistencies in the data.

To improve data quality, standardize data that contains the following types of values:

¨ Incorrect values

¨ Values with correct information in the wrong format

¨ Values from which you want to derive new information

Use the Standardizer transformation to search for these values in data. You can choose one of the followingsearch operation types:

¨ Text. Search for custom strings that you enter. Remove these strings or replace them with custom text.

¨ Reference table. Search for strings contained in a reference table that you select. Remove these strings, orreplace them with reference table entries or custom text.

For example, you can configure the Standardizer transformation to standardize address data containing thecustom strings Street and St. using the replacement string ST. The Standardizer transformation replaces thesearch terms with the term ST. and writes the result to a new data column.

StoryHypoStores needs to standardize its customer address data so that all addresses use terms consistently. Theaddress data in the All_Customers data object contains inconsistently formatted entries for common terms such asStreet, Boulevard, Avenue, Drive, and Park.

75


¨ Create and configure an All_Customers_Stdz_tgt data object to contain standardized data.

¨ Create a mapping to standardize the address terms Street, Boulevard, Avenue, Drive, and Park to a consistentformat.

¨ Add the All_Customers data object to the mapping to connect to the source data.

¨ Add the All_Customers_Stdz_tgt data object to the mapping to create a target data object.

¨ Add a Standardizer transformation to the mapping and configure it to standardize the address terms.

¨ Run the mapping to generate standardized address data.

¨ Run the Data Viewer to view the mapping output.



TimingSet aside 15 minutes to complete this lesson.

Task 1. Create a Target Data ObjectIn this task, you create an All_Customers_Stdz_tgt data object that you can write standardized data to.

To create a target data object, complete the following steps:

1. Create an All_Customers_Stdz_tgt data object based on the All_Customers.csv file.

2. Configure the read and write options for the data object, including file locations and file names.

Step 1. Create an All_Customers_Stdz_tgt Data ObjectIn this step, you create an All_Customers_Stdz_tgt data object based on the All_Customers.csv file.




3. Verify that Create from an Existing Flat File is selected.

4. Click Browse and navigate to All_Customers.csv in the following directory: <Informatica Installation Directory>\clients\DeveloperClient\Tutorial

5. Click Open.

6. In the Name field, enter All_Customers_Stdz_tgt.

7. Click Next.

8. Click Next.


10. Click Finish.

The All_Customers_Stdz_tgt data object appears in the editor.

76 Chapter 18: Lesson 5. Standardizing Data

Step 2. Configure Read and Write OptionsIn this step, you configure the read and write options for the All_Customers_Stdz_tgt data object, including filelocations and file names.

1. Verify that the All_Customers_Stdz_tgt data object is open in the editor.




5. In the Value column, double-click the source file name and type All_Customers_Stdz_tgt.csv.

6. In the Value column, double-click the Source file directory entry.

7. Right-click the highlighted name and select Copy.




11. Right-click and select Paste to paste the directory location you copied from the Read view.


13. In the Value column, double-click the Output file name entry and type All_Customers_Stdz_tgt.csv.


Task 2. Create a Mapping to Standardize DataIn this task, you create a mapping and configure the mapping to use data objects and a Standardizertransformation.

To create a mapping to standardize data, complete the following steps:

1. Create a mapping.


3. Add a Standardizer transformation to the mapping.

4. Configure the Standardizer transformation to standardize common address terms to consistent formats.



2. Click File > New > Mapping .


3. In the Name field, enter StandardizerMapping.

4. Click Finish.


Task 2. Create a Mapping to Standardize Data 77

Step 2. Add Data Objects to the MappingIn this step, you add the All_Customers data object and the All_Customers_Stdz_tgt data object to the mapping.


2. Select the All_Customers data object and drag it to the editor.





5. Select the All_Customers_Stdz_tgt data object and drag it to the editor.




7. Select all ports in the All_Customers data object. Drag the ports to the CustomerID port in theAll_Customers_Stdz_tgt data object.

Tip: Hold down the Shift key to select multiple ports. You might need to scroll down the list of ports to selectall of them.

The ports of the All_Customers data object connect to corresponding ports in the All_Customers_Stdz_tgtdata object.

Step 3. Add a Standardizer Transformation to the MappingIn this step, you add a Standardizer transformation to standardize strings in the address data.

1. Select the editor containing the StandardizerMapping mapping.

2. In the Transformation palette, select the Standardizer transformation.


A Standardizer transformation named NewStandardizer appears in the mapping.

4. To rename the Standardizer transformation, double-click the title bar of the transformation and typeAddressStandardizer.

5. Select the Address1 port in the All_Customers data object and drag the port to the Input group of theAddressStandardizer transformation.

In the NewStandardizer transformation, ports named Address1 appear in the input and output groups. Theinput Address1 port connects to the Address1 port in the All_Customers data object.

6. Select the Address1 port in the output group of the AddressStandardizer transformation. Drag the port to theAddress1 port in the All_Customers_Stdz_tgt data object.

The Remove Existing Link window opens.

7. Click Yes.



Step 4. Configure the Standardizer TransformationIn this step, you configure the Standardizer transformation to standardize address terms in the source data.


2. Click the Standardizer transformation.


4. In the Properties view, select the Standardization view.

5. Click Add to create a standardization operation.

The Add Standardizer Operation window opens.

6. Select Using Text.

7. Click Edit.

The Enter Text window opens.

8. Click Add and enter a string from the Text to Replace column in the table below.

Text to Replace Replacement Text

STREET ST.

BOULEVARD BLVD.

AVENUE AVE.

DRIVE DR.

PARK PK.

9. Click OK.

10. Select Replace with Custom Text. Type the entry from Replacement Text column in the table above thatcorresponds to the Text to Replace string you added in step 8.

11. Click OK.

12. Repeat steps 5 through 11 until you have added standardization operations for all rows in the table in step 8.

13. Click Select to select a delimiter.

14. Select the Space delimiter and the Comma delimiter and click OK.

15. Click File > Save to save the mapping.

Task 3. Run the MappingIn this task, you run the mapping to write standardized addresses to the output data object.


2. Click Run > Run Mapping .

The mapping runs and writes output to the All_Customers_Stdz_tgt.csv file.

Task 3. Run the Mapping 79

Task 4. View the Mapping OutputIn this task, you run the data viewer to view the mapping output and verify that the address data is correctlystandardized.

1. In the Object Explorer view, locate the All_Customers_Stdz_tgt data object in your tutorial project and double-click the data object.


2. Click Window > Show View > Data Viewer .

The Data Viewer view opens.

3. In the Data Viewer view, click Run.

The Data Viewer displays the mapping output.

4. Verify that the Address1 column displays correctly standardized data. For example, all instances of the stringSTREET should be replaced with the string ST.

Standardizing Data SummaryIn this lesson, you learned that you can standardize data to remove errors and inconsistencies in the data.

You learned that you can use a Standardizer transformation to standardize strings in an input column. You alsolearned that you can view mapping output using the Data Viewer.

You created and configured the All_Customers_Stdz_tgt data object to contain standardized output. You created amapping to standardize the data. In this mapping, you configured a Standardizer transformation to standardize theAddress1 column in the All_Customers data object. You configured the mapping to write the standardized outputto the All_Customers_Stdz_tgt data object. Finally, you ran the mapping and used the Data Viewer to view thestandardized data in the All_Customers_Stdz_tgt data object.


C H A P T E R 1 9

Lesson 6. Validating Address DataThis chapter includes the following topics:

¨ Validating Address Data Overview, 81

¨ Task 1. Create a Target Data Object , 82

¨ Task 2. Create a Mapping to Validate Addresses, 84

¨ Task 3. Configure the Address Validator Transformation, 85



¨ Validating Address Data Summary, 89

Validating Address Data OverviewAddress validation is the process of evaluating and improving the quality of postal addresses. It evaluates addressquality by comparing input addresses with a reference dataset of valid addresses. It improves address quality byidentifying incorrect address values and using the reference dataset to create fields that contain correct values.

An address is valid when it is deliverable. An address may be well formatted and contain real street, city, and postcode information, but if the data does not result in a deliverable address then the address is not valid. TheDeveloper tool uses address reference datasets to check the deliverability of input addresses. Informaticaprovides address reference datasets.

An address reference dataset contains data that describes all deliverable addresses in a country. The addressvalidation process searches the reference dataset for the address that most closely resembles the input addressdata. If the process finds a close match in the reference dataset, it writes new values for any incorrect orincomplete data values. The process creates a set of alphanumeric codes that describe the type of match foundbetween the input address and the reference addresses. It can also restructure the address, and it can addinformation that is absent from the input address, such as a four-digit ZIP code suffix for a United States address.

Use the Address Validator transformation to build address validation processes in the Developer tool. This multi-group transformation contains a set of predefined input ports and output ports that correspond to all possible fieldsin an input address. When you configure an Address Validator transformation, you set the default referencedataset and you create an input and output address template using the transformation ports. In this lesson youconfigure the transformation to validate United States address data.

StoryHypoStores needs correct and complete address data to ensure that its direct mail campaigns and other consumermail items reach its customers. Correct and complete address data also reduces the cost of mailing operations for

81

the organization. In addition, HypoStores needs its customer data to include addresses in a printable format that isflexible enough to include addresses of different lengths.

To meet these business requirements, the HypoStores ICC team creates an address validation mapping in theDeveloper tool.


¨ Create a target data object that will contain the validated address fields and match codes.

¨ Create a mapping with a source data object, a target data object, and an Address Validator transformation.

¨ Configure the Address Validator transformation to validate the address data of your customers.

¨ Run the mapping to validate the address data, and review the match code outputs to verify the validity of theaddress data.



¨ United States address reference data is installed in the domain and registered with the Administrator tool.Contact your Informatica administrator to verify that United States address data is installed on your system.The reference data installs through the Data Quality Content Installer.

TimingSet aside 25 minutes to complete this lesson.

Task 1. Create a Target Data ObjectIn this task, you create a target data object, configure the write options, and add ports.

To create and configure the target data object, complete the following steps:

1. Create an All_Customers_av_tgt data object based on the All_Customers.csv file.

2. Configure the read and write options for the data object, including the file locations and file names.

3. Add ports to the data object to receive the match code values generated by the Address Validatortransformation.

Step 1. Create the All_Customers_av_tgt Data ObjectIn this step, you create an All_Customers_av_tgt data object based on the All_Customers.csv file.




3. Verify that Create from an Existing Flat File is selected. Click Browse next to this selection, find theAll_Customers.csv file, and click Open.

4. In the Name field, enter All_Customers_av_tgt.

5. Click Next.

6. Click Next.

82 Chapter 19: Lesson 6. Validating Address Data


8. Click Finish.

The All_Customers_av_tgt data object appears in the editor.

Step 2. Configure Read and Write OptionsIn this step, you configure the read and write options for the All_Customers_av_tgt data object, including the targetfile name and location.

1. Verify that the All_Customers_av_tgt data object is open in the editor.


3. Select Window > Show View > Properties .


5. In the Value column, double-click the source file name and type All_Customers_av_tgt.csv.

6. In the Value column, double-click to highlight the source file directory path.

7. Right-click the highlighted path and name and select Copy.




11. Right-click this entry and select Paste to add the path you copied from the Read view.


13. In the Value column, double-click the Output file name entry and type All_Customers_av_tgt.csv.

14. Select File > Save to save the data object.

Step 3. Add Ports to the Data ObjectIn this step, you add two ports to the All_Customers_av_tgt data object so that the Address Validatortransformation can write match code values to the target file. Name the ports MailabilityScore and MatchCode.

The MailabilityScore value describes the deliverability of the input address. The MatchCode value describes thetype of match the transformation makes between the input address and the reference data addresses.


2. Double-click the All_Customers_av_tgt data object.

The All_Customers_av_tgt data object opens in the editor.

3. Verify that Overview is selected.

4. Select the final port in the port list. This port is named MiscDate.

5. Click New.

A port named MiscDate1 appears.

6. Rename the MiscDate1 port to MailabilityScore.

7. Select the MailabilityScore port.

8. Click New.

A port named MailabilityScore1 appears.

9. Rename the MailabilityScore1port to MatchCode.


Task 1. Create a Target Data Object 83

Task 2. Create a Mapping to Validate AddressesIn this task, you create a mapping and add data objects and an Address Validator transformation.

To create the mapping and add the objects you need, complete the following steps:

1. Create a mapping object.


3. Add an Address Validator transformation to the mapping.



2. Select File > New > Mapping .


3. In the Name field, enter ValidateAddresses.

4. Click Finish.


Step 2. Add Data Objects to the MappingIn this step, you add the source and target data objects to the mapping.

All_Customers is the source data object for the mapping. The Address Validator transformation reads data fromthis object. All_Customers_av_tgt is the data target object for the mapping. This object reads data from theAddress Validator transformation.


2. Select the All_Customers data object and drag it to the editor.





5. Select the All_Customers_av_tgt data object and drag it onto the editor.




7. Click Save.


Step 3. Add an Address Validator Transformation to the MappingIn this step, you add an Address Validator transformation to the mapping that contains the source and data objects.

When this step is complete, you can configure the transformation and connect its ports to the data objects.

1. Select the editor containing the ValidateAddresses mapping.

2. In the Transformation palette, select the Address Validator transformation.


The Address Validator transformation appears in the editor.

Task 3. Configure the Address Validator TransformationIn this task, you configure the Address Validator transformation to read and validate addresses from theAll_Customers data source.

Note: The Address Validator transformation contain a series of predefined input and output ports. Select the portsyou need and connect them to the objects in the mapping.

To configure the transformation, complete the following steps:

1. Select the default address reference dataset.

2. Configure the transformation ports and connect the transformation to the mapping.

3. Connect unused source ports to the data target.

Step 1. Set the Default Address Reference DatasetIn this step, you select the default reference dataset. Address reference data files are defined by country, so youselect a country name as the default dataset. The Address Validator transformation uses reference data relating tothis country if it cannot determine the country to use from the input data values.

1. Select the Address Validator transformation in the editor.

2. Under Properties, click General Settings.

3. In the Default Country menu, select United States.

Step 2. Configure the Address Validator Transformation Input PortsIn this step, you select transformation input ports and connect these ports to the All_Customers_av data object.

The Address Validator transformation contains several groups of predefined input ports. Select the input ports thatcorrespond to the fields in your input address and save these ports as a template in the transformation. Thetemplate makes it easier to view ports in the editor.

Note: Hold the Ctrl key when selecting ports in the steps below to select multiple ports in a single operation.

1. Select the Address Validator transformation in the editor.

2. Under Properties, click Templates.

3. Expand the Basic Model port group.

Task 3. Configure the Address Validator Transformation 85

4. Expand the Hybrid input port group and select the following ports:

Port Name Description

DeliveryAddressLine1 Street address data, such as street name and building number.

LocalityComplete1 City or town name.

Postcode1 Postcode or ZIP code.

Province1 Province or state name.

CountryName Country name or abbreviation.

5. On the toolbar above the port names list, click Add selection to current model.

This toolbar is visible when you select Templates.

The selected ports appear in the transformation in the mapping editor.

6. Connect the source ports to the Address Validator transformation ports as follows:

Source Port Address Validator Transformation Port

Address1 DeliveryAddressLine1

City LocalityComplete1

ZIP Postcode1

State Province1

Country CountryName

Step 3. Configure the Address Validator Transformation Output PortsIn this step, you select transformation output ports and connect these ports to the All_Customers_av_tgt dataobject.

The Address Validator transformation contains several groups of predefined output ports. Select the ports thatdefine the address structure you require and save these ports as a template in the transformation. The templatemakes it easier to view ports in the editor.

You can also select ports containing information on the type of validation achieved for each address.

1. Select the Address Validator transformation in the mapping editor.

2. Under Properties, click Templates.

3. Expand the Basic Model port group.

4. Expand the Address Elements output port group and select the following port:


StreetComplete1 Street address data, such as street name and building number.


5. Expand the LastLine Elements output port group and select the following ports:


LocalityComplete1 City or town name.

Postcode1 Postcode or ZIP code.

ProvinceAbbreviation1 Province or state identifier.

Note: Hold the Ctrl key to select multiple ports in a single operation.

6. Expand the Country output port group and select the following port:


CountryName1 Country name.

7. Expand the Status Info output port group and select the following ports:


MailabilityScore Score that represents the chance of successful postal delivery.

MatchCode Code that represents the degree of similarity between the input address and the referencedata.

8. On the toolbar above the port names list, click Add selection to current model.

This toolbar is visible when you select Templates.

9. Connect the Address Validator transformation ports to the All_Customers_av_tgt ports as follows:

Address Validator Transformation Port Target Port

StreetComplete1 Address1

LocalityComplete1 City

Postcode1 ZIP

ProvinceAbbreviation1 State

CountryName1 Country

MailabilityScore MailabilityScore

MatchCode MatchCode

Step 4. Connect Unused Data Source Ports to the Data TargetIn this step, you connect the unused ports on the All_Customers data source to the data target.

u Connect the unused ports on the data source to the ports with the same names on the data target.

Task 3. Configure the Address Validator Transformation 87

Task 4. Run the MappingIn this task, you run the mapping to create the mapping output.

1. Select the editor containing the ValidateAddresses mapping.

2. Select Run > Run Mapping .

The mapping runs and writes output to the All_Customers_av_tgt.csv file.

Task 5. View the Mapping OutputIn this task, you run the Data Viewer to view the mapping output. Review the quality of your validated addressesby examining the values written to the MailabilityScore and MatchCode columns in the target data object.

The MatchCode value is an alphanumeric code representing the type of validation that the mapping performed onthe address.

The MailabilityScore value is a single-digit value that summarizes the deliverability of the address.

1. In the Object Explorer view, find the All_Customers_av_tgt data object in your tutorial project and double clickthe data object.


2. Select Window > Show View > Data Viewer .

The Data Viewer opens.

3. In the Data Viewer, click Run.

The Data Viewer displays the mapping output.

4. Scroll across the mapping results so that the MailabilityScore and MatchCode columns are visible.

5. Review the values in the MailabilityScore column.

The scores can range from 0 through 5. Addresses with higher scores are more likely to be deliveredsuccessfully.

6. Review the values in the MatchCode column.

MatchCode is an alphanumeric code. The alphabetic character indicates the type of validation that thetransformation performed ,and the digit indicates the quality of the final address.

The following table describes the common MatchCode values:

MatchCode Description

V4 Verified as deliverable by the Address Validator. Input data is correct, and inputs are a perfect matchwith the reference data.

V3 Verified as deliverable by the Address Validator. Input data is correct, but there was an imperfectmatch with the reference data. This is possibly due to poor standardization of address elements.


MatchCode Description

V2 Verified as deliverable by the Address Validator. Input data is correct, but there was an imperfectmatch with the reference data. Some reference data files may be missing files.

V1 Verified as deliverable by the Address Validator. Input data is correct but poor standardization hasreduced address deliverability.

C4 Corrected by the Address Validator. All elements have been processed and corrected where necessary.

C3 Corrected by the Address Validator. All elements have been processed, but some elements could notbe checked.

C2 Partially corrected by the Address Validator. because some reference data files may be missing.

C1 Corrected by the Address Validator, but poor standardization has reduced address deliverability.

I4 Input data could not be corrected, but the address is very likely to be deliverable as it matches aunique reference address.

I3 Input data could not be corrected, but the address is very likely to be deliverable as it matches multiplereference addresses.

I2 Input data could not be corrected, and deliverability is not likely.

I1 Input data could not be corrected, and deliverability is very unlikely.

N1... N6 No validation was performed. This may be due to an absence of current or licensed reference data.The address may or may not be deliverable.

Note: Although some MatchCode values can confirm the deliverability of an address, others provide guidelineinformation only. In these cases, you may need to reconfigure the address template in the Address Validatortransformation or check that the address reference data is up to date.

Validating Address Data SummaryIn this lesson, you learned that address validation compares input address data with reference data and returnsthe most accurate possible version of the address.

You learned that the address validation process also returns status information on the quality of each address.

You learned that Administrator tool users run the Data Quality Content Installer to install address reference data.

You also learned that the Address Validator transformation is a multi-group transformation, and you learned thatyou must define port templates to display the input and output ports when the transformation is open in a mapping.The input ports you select determine the content of the address that is validated, and the output ports determinethe content of the final address.

Validating Address Data Summary 89

Part IV: Getting Started withInformatica Developer (DataServices)


¨ Lesson 1. Setting Up Informatica Developer, 91

¨ Lesson 2. Importing Physical Data Objects, 95

¨ Lesson 3. Creating a Logical View of Data, 98

¨ Lesson 4. Creating a Virtual View of Data, 104

¨ Lesson 5. Exporting a Mapping to PowerCenter, 108

90

C H A P T E R 2 0

Lesson 1. Setting Up InformaticaDeveloper


¨ Setting Up Informatica Developer Overview, 91

¨ Task 1. Start Informatica Developer, 92

¨ Task 2. Add a Domain, 92

¨ Task 3. Add a Model Repository, 93



¨ Task 6. Select a Default Data Integration Service, 94

¨ Setting Up Informatica Developer Summary, 94

Setting Up Informatica Developer OverviewBefore you start the lessons in this tutorial, you must start and set up the Developer tool. To set up the Developertool, you add a domain. You add a Model repository, and you create a project and folder to store your work. Youalso select a default Data Integration Service.

The Informatica domain is a collection of nodes and services that define the Informatica environment. Services inthe domain include the Model Repository Service and the Data Integration Service.

The Model Repository Service manages the Model repository. The Model repository is a relational database thatstores the metadata for projects that you create in the Developer tool. A project stores objects that you create inthe Developer tool. A project can also contain folders that store related objects, such as objects that are part of thesame business requirement.

The Data Integration Service performs data integration tasks in the Developer tool.


¨ Start the Developer tool and go to the Developer tool workbench.

¨ Add a domain in the Developer tool.

¨ Add a Model repository so that you can create a project.

¨ Create a project to store the objects that you create in the Developer tool.

91


¨ Select a default Data Integration Service to perform data integration tasks.


¨ You have installed the Developer tool.

¨ You have a domain name, host name, and port number to connect to a domain. You can get this informationfrom a domain administrator.

¨ A domain administrator has configured a Model Repository Service in the Administrator tool.

¨ You have a user name and password to access the Model Repository Service. You can get this informationfrom a domain administrator.

¨ A domain administrator has configured a Data Integration Service.

¨ The Data Integration Service is running.


Task 1. Start Informatica DeveloperStart the Developer tool to begin the tutorial.

1. Select Start > Programs > Informatica 9.0 > Client > Developer Client > Launch Informatica Developerfrom the Windows Start menu.

The Welcome page of the Developer tool appears.

2. Click the Workbench button.

The Developer tool workbench appears.

Task 2. Add a DomainIn this task, you add a domain in the Developer tool to access a Model repository.



2. Select Informatica > Domains .

3. Click Add.

The New Domain dialog box appears.

4. Enter the domain name, host name, and port number.

5. Click Finish.

6. Click OK.


Task 3. Add a Model RepositoryIn this task, you add the Model repository that you want to use to store projects and folders.

1. Click File > Connect to Repository .

The Connect to Repository dialog box appears.

2. Click Browse to select a Model Repository Service.

3. Click OK.

4. Click Next.

5. Enter your user name and password.

6. Click Finish.

The Model repository appears in the Object Explorer view.

Task 4. Create a ProjectIn this task, you create a project to store objects that you create in the Developer tool. You can create one projectfor all tutorials in this guide.

1. In the Object Explorer view, select a Model Repository Service.

2. Click File > New > Project .

The New Project dialog box appears.


4. Click Finish.

The project appears under the Model Repository Service in the Object Explorer view.

Task 5. Create a FolderIn this task, you create a folder to store related objects. You can create one folder for all tutorials in this guide.

1. In the Object Explorer view, select the project that you want to add the folder to.

2. Click File > New > Folder .

3. Enter a name for the folder.

4. Click Finish.

The Developer tool adds the folder under the project in the Object Explorer view. Expand the project to seethe folder.

Task 3. Add a Model Repository 93

Task 6. Select a Default Data Integration ServiceIn this task, you select a default Data Integration Service to run mappings and preview data.



2. Select Informatica > Data Integration Services .

3. Expand the domain.

4. Select a Data Integration Service.

5. Click Set as Default.

6. Click OK.

Setting Up Informatica Developer SummaryIn this lesson, you learned that the Informatica domain services include the Model Repository Service and DataIntegration Service. The Model Repository Service manages the Model repository. A Model repository containsprojects and folders. The Data Integration Service performs data integration tasks.

You started the Developer tool and set up the Developer tool. You added a domain to the Developer tool, added aModel repository, and created a project and folder. You also selected a default Data Integration Service.

Now, you can use the Developer tool to complete other lessons in this tutorial.


C H A P T E R 2 1

Lesson 2. Importing Physical DataObjects


¨ Importing Physical Data Objects Overview, 95

¨ Task 1. Import the Boston_Customers Flat File Data Object, 96

¨ Task 2. Import the LA_Customers Flat File Data Object, 97

¨ Importing Physical Data Objects Summary, 97

Importing Physical Data Objects OverviewA physical data object is a representation of data based on a flat file or relational database table. You can import aflat file or relational database table as a physical data object to use as a source or target in a mapping.

StoryHypoStores Corporation stores customer data from the Los Angeles office and Boston office in flat files.HypoStores wants to work with this customer data in the Developer tool.

ObjectivesIn this lesson, you import flat files as physical data objects. You also set the source file directory so that the DataIntegration Service can read the source data from the correct directory.




95

Task 1. Import the Boston_Customers Flat File DataObject

In this task, you import a physical data object from a file that contains customer data from the Boston office.






4. Enter Boston_Customers as the data object name.

5. Select Create from an existing flat file.

6. Click Browse and navigate to Boston_Customers.csv in the following directory: <Informatica InstallationDirectory>\clients\DeveloperClient\Tutorial

7. Click Open.

The wizard names the data object "Boston_Customers."

8. Click Next.



11. Click Next.


13. Select Import column names from first line.

14. Click Finish.

The Boston_Customers physical data object appears under Physical Data Objects in the tutorial project.



17. Set Source file directory to the following directory on the Data Integration Service machine: \Informatica\9.0\server\Tutorial

18. Click the Data Viewer view.

19. Click Run.

The Data Integration Service reads the data from the Boston_Customers file and shows the results in theOutput window.


96 Chapter 21: Lesson 2. Importing Physical Data Objects

Task 2. Import the LA_Customers Flat File Data ObjectIn this task, you import a physical data object from a flat file that contains customer data from the Los Angelesoffice.






4. Select Create from an existing flat file.


6. Click Open.

The wizard names the data object "LA_Customers."

7. Click Next.



10. Click Next.


12. Select Import column names from first line.

13. Click Finish.

The LA_Customers physical data object opens in the editor.



16. Set the source file directory to the following directory on the Data Integration Service machine: \Informatica\9.0\server\Tutorial


18. Click Run.

The Data Integration Service reads the data from the LA_Customers file and shows the results in the Outputwindow.


Importing Physical Data Objects SummaryIn this lesson, you learned that physical data objects are representations of data based on a flat file or a relationaldatabase table.

You imported physical data objects from flat files. You also set the source file directory so that the Data IntegrationService can read the source data from the correct directory.

Task 2. Import the LA_Customers Flat File Data Object 97

C H A P T E R 2 2

Lesson 3. Creating a Logical Viewof Data


¨ Creating a Logical View of Data Overview, 98

¨ Task 1. Import a Logical Data Object Model, 100

¨ Task 2. Create a Logical Data Object Mapping, 100

¨ Task 3. Run the Logical Data Object Mapping, 102

¨ Creating a Logical View of Data Summary, 103

Creating a Logical View of Data OverviewA logical view of data is a data model in an enterprise. It provides a single view of physical data in an enterprise,even if the data comes from various sources, such as different files or databases.

To develop a single view of data, you need to define a logical data object model. A logical data object modeldescribes the structure and use of data in an enterprise. A logical data object model also describes how differenttypes of data are related to each other. For example, a logical data object model can describe how customer dataand order data are formatted and structured and how they are related.

A logical data object model contains logical data objects. A logical data object defines a data entity in anenterprise, such as a customer or an order. It describes the attributes of the entity, such as name and address in acustomer data object. It also describes key relationships of those attributes to attributes in other logical dataobjects. For example, it can define a relationship between the order ID in an order logical data object and thecustomer ID of a customer logical data object. Therefore, the model states that in an enterprise, each order IDmust be associated with a customer ID.

A logical data object mapping contains a logical data object as the mapping input or output. You can read datafrom multiple sources and apply the output to a logical data object. The mapping can also contain transformationlogic to transform the data.

98

The following figure shows a logical view of data:

StoryHypoStores Corporation wants a single view of customer data from the Los Angeles and Boston offices. Theenterprise data model requires that customer names use the same format regardless of the data source. Thecustomer data from the Los Angeles office uses a different format for customer names than the data from theBoston office. The data from the Los Angeles office uses the correct format, so you need to reformat the customerdata from the Boston office to conform to the data model.


1. Import a logical data object model that contains the Customer and Orders logical data objects.

2. Create a logical data object mapping with the Customer logical data object as the mapping output. Themapping transforms the Boston customer data and defines a single view of the data from the Los Angeles andBoston offices.

3. Run the mapping to view the combined customer data.


¨ Complete lessons 1 and 2 in this tutorial.


Creating a Logical View of Data Overview 99

Task 1. Import a Logical Data Object ModelIn this task, you import a logical data object model that contains the Customer and Order logical data objects.


2. Click File > New > Logical Data Object Model .

The New Logical Data Object Model dialog box appears.

3. Select Create Existing Model from File.

4. Click Browse and navigate to Customer_Order.xsd in the following directory: <Informatica InstallationDirectory>\clients\DeveloperClient\Tutorial

5. Click Open.

The wizard names the data object Customer_Order.

6. Click Next.

7. Click the Move All Items button to add the Customer and Order logical data objects to the model.

8. Click Finish.

The Customer and Order logical data objects appear in the editor.

Task 2. Create a Logical Data Object MappingIn this task, you create a logical data object mapping that combines the first and last names of the customer datafor the Boston office. The mapping also combines the customer data for the Los Angeles and Boston offices.

To create the logical data object mapping, complete the following steps:

1. Create a mapping with the Customer data object as the mapping output.

2. Add the LA_Customers and Boston_Customers physical data objects as sources.

3. Add an Expression transformation to concatenate the FirstName and LastName columns of the Bostoncustomer data. Preview the transformation output.

4. Add a Union transformation to combine the Los Angeles and Boston customer data.

Step 1. Creating the MappingCreate a logical data object mapping with the Customer data object as the mapping output.

1. In the Object Explorer view, select the Customer_Order logical data object model.

2. Click File > New > Other.

3. Select Informatica > Data Objects > Data Object Mapping and click Next.

4. Click Browse and select the Customer logical data object.

5. Select Read as the mapping type.

6. Click Finish .

The editor displays a mapping with the Customer logical data object as an Output transformation.


100 Chapter 22: Lesson 3. Creating a Logical View of Data

Step 2. Adding Sources to the MappingAdd the LA_Customers and Boston_Customers data objects to the mapping as sources.

1. In the Object Explorer view, expand Physical Data Objects in the tutorial folder.

2. Select LA_Customers and drag it to the editor that contains the logical data object mapping.

3. Select Read and click OK.

LA_Customers appears in the editor as a source.

4. Select Boston_Customers and drag it to the editor.

5. Select Read and click OK.

Boston_Customers appears in the editor as a source.


Step 3. Adding an Expression Transformation to the MappingAdd an Expression transformation to concatenate the FirstName and LastName columns of the Boston customerdata. Preview the transformation output.

1. In the Transformation palette, select the Expression transformation and drag it to the editor.

An Expression transformation appears in the editor.

Tip: To find the Expression transformation, click the Customize the Transformation Palette button at the topof the palette. Select Show Icons and Labels. Expand the palette from the right edge to see the labels.

2. Select all columns in the Boston_Customers source and drag them to the Expression transformation.

The columns appear as ports in the Expression transformation.

3. Select the Expression transformation and click the Ports tab in the Properties view.

4. Select Output Only and click the New button.

A port appears.

5. Enter FullName as the port name and change the precision to 20.

6. Click the Open button on the right of the Expression column to open the Expression editor.

7. Enter the following expression: CONCAT( CONCAT( FIRSTNAME, ' ' ), LASTNAME )8. Click Validate to validate the expression.

9. Click OK.

10. Select the Expression transformation in the editor.

11. Select the FullName port.

12. Click the Down arrow at the top of the transformation twice to move the FullName port below the CustomerTier port.



15. Click Run.

The Data Integration Service processes the data from the Boston_Customers source and the Expressiontransformation. The Developer tool shows the results in the Output window. The results show that the DataIntegration Service has concatenated the FirstName and LastName columns from the source.

Task 2. Create a Logical Data Object Mapping 101

Step 4. Adding a Union Transformation to the MappingAdd a Union transformation to combine the source data.

1. In the Transformation palette, select the Union transformation and drag it to the editor.

A Union transformation appears in the editor.

2. Select all columns in the LA_Customers source and drag them to the Union transformation.

Tip: Hold down the Shift key to select multiple ports. You might need to scroll down the list of ports to selectall of them.

The columns appear as ports in an input group and an output group of the Union transformation.

3. Select the Union transformation and click the Groups tab in the Properties view.

4. Click New to add a group.

5. Name the group Boston_Input.

The Union transformation includes the Boston_Input group with ports of the same name as the input groupand output group.

6. Select all of the ports in the Expression transformation except FirstName and LastName.

7. Drag the ports to the Boston_Input group.

The Developer tool links the ports in the Expression transformation to the ports in the Boston_Input group ofthe Union transformation.

8. Select the ports in the output group of the Union transformation and drag them to the Customertransformation.

The Developer tool links the ports in the Union transformation to the ports in the Customer transformation.

9. Right-click an empty area in the editor and click Validate.

The Developer tool displays a message stating that it found no validation errors.

10. Click OK.


Task 3. Run the Logical Data Object MappingIn this task, you run the logical data object mapping to create a single view of customer data from the Los Angelesand Boston offices.

u Right-click an empty area in the editor and click Run Data Viewer.

The Data Viewer view appears.After the Data Integration Service runs the mapping, the Developer tool shows the data in the Output section ofthe Data Viewer view. The output shows that you merged the FirstName and LastName columns of theBoston_Customers source. It also shows that you combined the data from the LA_Customers source andBoston_Customers source.

102 Chapter 22: Lesson 3. Creating a Logical View of Data

Creating a Logical View of Data SummaryIn this lesson, you learned that a logical data object model describes the structure and use of data in anenterprise. The model contains logical data objects that define a data entity in an enterprise, such as a customeror an order. You also learned that you can create a mapping that reads data from multiple sources, transforms it,and applies the output to a logical data object.

You created a logical data object model to provide a single view of customer data.

Use the logical data object mapping that you created in this lesson in the following lessons:

¨ Chapter 23, “Lesson 4. Creating a Virtual View of Data” on page 104

¨ Chapter 24, “Lesson 5. Exporting a Mapping to PowerCenter” on page 108

Creating a Logical View of Data Summary 103

C H A P T E R 2 3

Lesson 4. Creating a Virtual Viewof Data


¨ Creating a Virtual View of Data Overview, 104

¨ Task 1. Create an SQL Data Service, 105

¨ Task 2. Run an SQL Query to Preview Data, 106

¨ Task 3. Create an Application, 106

¨ Task 4. Deploy the Application, 107

¨ Creating a Virtual View of Data Summary, 107

Creating a Virtual View of Data OverviewA virtual view of data is a virtual database that you can query as if it were a physical database.

To create a virtual database, you define an SQL data service in the Developer tool. The SQL data service mustcontain at least one virtual schema that defines the virtual database structure. The virtual schema must contain atleast one virtual table.

After you create an SQL data service, you create an application and add the SQL data service to the application.An application is an object that contains one or more SQL data services and mappings. You can deploy theapplication to a Data Integration Service to make the virtual database available for end users to query.

104

The following figure shows a virtual view of data:

StoryHypoStores Corporation wants to create a report about customers for the Los Angeles and Boston offices.However, the Los Angeles customer data is not in the central data warehouse. A developer in the IT departmenthas combined the data for the Los Angeles and Boston customer offices in a logical data object model. Thedeveloper can make this data available to query in a virtual database. A business analyst can create a reportbased on the virtual data.


1. Create an SQL data service to define a virtual database that contains customer data.

2. Preview the virtual data.

3. Create an application that contains the SQL data service.

4. Deploy the application to a Data Integration Service.


¨ Complete lessons 1, 2, and 3 in this tutorial.


Task 1. Create an SQL Data ServiceIn this task, you create an SQL data service to create a virtual database that end users can query.


2. Click File > New > Data Service .


3. Select SQL Data Service and click Next.

The New SQL Data Service dialog box appears.

Task 1. Create an SQL Data Service 105

4. Enter HypoStores_Customers for the SQL data service name and click Next.

5. To create a virtual table, click the New button.

The Developer tool adds a virtual table to the list of virtual tables.

6. Enter Customers for the virtual table name.

7. Click the Open button in the Source column.

The Select a Source dialog box appears.

8. In the tutorial folder, expand the Customer_Order logical data object model, and select the Customer logicaldata object.

9. Click OK.

The developer tool adds Customer as the virtual table source. It also specifies Data Object as the source typeand the tutorial project as the location.

10. Enter Customer_Schema in the Virtual Schemas column and press Enter.

11. Click Finish.

The Developer tool creates the HypoStores_Customers SQL data service. The SQL data service contains theCustomers table and the Customers mapping.

Task 2. Run an SQL Query to Preview DataIn this task, you run an SQL query against the Customers virtual table to preview the data.

1. In the Object Explorer view, open the HypoStores_Customers SQL data service.

2. Click the Relationships view in the editor.

3. Select the Data Viewer view.

4. In the Input section, enter the following SQL statement: SELECT * from customers5. Click Run.

The Output section displays the combined customer data from the Los Angeles and Boston offices.

Task 3. Create an ApplicationIn this task, you create an application that contains the SQL data service.


2. Click File > New > Application .

The New Application dialog box appears.

3. Enter HypoStores_Customers_App for the application name and click Next.

4. Click Add.

The Add Features dialog box appears.

5. Select HypoStores_Customers and click OK.

6. Click Finish.

The Developer tool creates an application that contains the HypoStores_Customers data service.

106 Chapter 23: Lesson 4. Creating a Virtual View of Data

Task 4. Deploy the ApplicationIn this task, you deploy the application so end users can query virtual tables in the SQL data service through aJDBC or ODBC client tool.

1. In the Object Explorer view, expand Applications in the tutorial project.

2. Right-click the HypoStores_Customers_App application and click Deploy.

The Deploy dialog box appears.

3. Click Browse next to the Domain option.

4. Select a domain and click OK.

5. Select the Data Integration Service that you want to deploy the application to.

6. Click Finish.

When the deployment succeeds, the Deployment Finished dialog box appears.

7. Click OK.

Creating a Virtual View of Data SummaryIn this lesson, you learned that you can define an SQL data service that contains a virtual database. A virtualdatabase includes at least one schema and virtual table. You learned that you can associate the virtual table witha data object. You also learned that you can make the virtual database available so that end users can query thevirtual data.

You created a virtual view of data and ran an SQL query to preview the virtual data. You also created anapplication to contain the virtual data and deployed the application to a Data Integration Service.

Task 4. Deploy the Application 107

C H A P T E R 2 4

Lesson 5. Exporting a Mapping toPowerCenter


¨ Exporting a Mapping to PowerCenter Overview, 108

¨ Task 1. Export a Mapping to PowerCenter, 109

¨ Exporting a Mapping to PowerCenter Summary, 109

Exporting a Mapping to PowerCenter OverviewYou can export a mapping that you create in the Developer tool to a PowerCenter repository. Export mappings toPowerCenter to reuse the metadata for physical data integration or to create web services.

StoryYou have developed a mapping that provides a single view of Los Angeles and Boston customer data. You want toexport this mapping to PowerCenter so that you can apply version control and load the target data to the centraldata warehouse.

ObjectivesIn this lesson, you export a Developer tool mapping to a PowerCenter repository.


¨ Complete lessons 1, 2, and 3.

¨ You can connect to a PowerCenter 9.0 repository. To get the repository login information, contact a domainadministrator.

TimingSet aside 5 to 10 minutes to complete this task.

108

Task 1. Export a Mapping to PowerCenterIn this task, you export a mapping that you created in the Developer tool to a PowerCenter repository.


2. Click File > Export .

The Export dialog box appears.

3. Select Informatica > PowerCenter .

4. Click Next.

The Export to PowerCenter dialog box appears.

5. Select PowerCenter 9.0.0 as the target release.

6. Choose PowerCenter Repository as the export location.

7. Click Browse to connect to a PowerCenter repository.

The Connect to PowerCenter Repository dialog box appears.

8. Enter the connection information and click OK.

The Developer tool displays a message after it connects to the repository.

9. Click OK.

10. Select the repository folder that you want to export the mapping to.

If the repository contains a tutorial folder, select it.

11. Click Next.

The Developer tool prompts you to select the objects to export.

12. Select Customer_Orders and click Finish.

The Developer tool exports the objects to the location you selected.

Exporting a Mapping to PowerCenter SummaryIn this lesson, you learned that you can export Developer tool mappings to PowerCenter. You export mappings toPowerCenter to reuse the metadata for physical data integration or to create web services.

You also exported a mapping to a PowerCenter repository.

Task 1. Export a Mapping to PowerCenter 109

A P P E N D I X A

Frequently Asked QuestionsThis appendix includes the following topics:

¨ Administrator FAQ, 110

¨ Informatica Developer FAQ, 111

¨ Informatica Analyst FAQ, 112

Administrator FAQReview the FAQ to answer questions you may have about Informatica Administrator.

What is the difference between the Informatica Administrator and the PowerCenter Administration Console?

The PowerCenter Administration Console is renamed to Informatica Administrator (the Administrator tool).The Administrator tool has a new interface. Some of the properties and configuration tasks from thePowerCenter Administration Console have been moved to different locations in the Administrator tool. TheAdministrator tool is also expanded to include new services and objects.

Can I use one user account to access the Administrator tool and the Developer tool?

Yes. You can give a user permission to access both tools. You do not need to create separate user accountsfor each client application.

What is the difference between the PowerCenter Repository Service and the Model Repository Service?

The PowerCenter application services and PowerCenter application clients use the PowerCenter RepositoryService. The PowerCenter repository has folder based security.

The Data Integration Service, Analyst Service, Developer tool, and Analyst tool use the Model RepositoryService. The Model Repository Service has project based security.

You can migrate some Model repository objects to the PowerCenter repository.

Where can I use database connections that I create in the Informatica Administrator?

You can create, view, and edit database connections in the Administrator tool and the Developer tool. Youcan create and view database connections in the Analyst tool. You can also configure database connectionpooling in the Administrator tool.

What is the difference between the PowerCenter Integration Services and the Data Integration Service?

The PowerCenter Integration Service is an application service that runs sessions and workflows. The DataIntegration Service is an application service that performs data integration tasks for the Analyst tool, theDeveloper tool, and external clients. The Analyst tool and the Developer tool send data integration taskrequests to the Data Integration Service to preview or run data profiles, SQL data services, and mappings.

110

Commands from the command line or an external clients send data integration task request to the DataIntegration Service to run SQL data services.

Why can't I connect to an SQL data service that is deployed to a Data Integration Service?

To connect to an SQL data service, the application that contains the SQL data service must be running. Tostart the application, select the application in the application view of the Data Integration Service, and thenclick the Start option on the Domain tab Actions menu.

Informatica Developer FAQReview the FAQ to answer questions you may have about Informatica Developer.

What is the difference between a source and target in PowerCenter and a physical data object in the Developer tool?

In PowerCenter, you create a source definition to include as a mapping source. You create a target definitionto include as a mapping target. In the Developer tool, you create a physical data object that you can use as amapping source or target.

What is the difference between a mapping in the Developer tool and a mapping in PowerCenter?

A PowerCenter mapping specifies how to move data between sources and targets. A Developer tool mappingspecifies how to move data between the mapping input and output.

A PowerCenter mapping must include one or more source definitions, source qualifiers, and target definitions.A PowerCenter mapping can also include shortcuts, transformations, and mapplets.

A Developer tool mapping must include mapping input and output. A Developer tool mapping can also includetransformations and mapplets.

The Developer tool has the following types of mappings:

¨ Mapping that moves data between sources and targets. This type of mapping differs from a PowerCentermapping only in that it cannot use shortcuts and does not use a source qualifier.

¨ Logical data object mapping. A mapping in a logical data object model. A logical data object mapping cancontain a logical data object as the mapping input and a data object as the mapping output. Or, it cancontain one or more physical data objects as the mapping input and logical data object as the mappingoutput.

¨ Virtual table mapping. A mapping in an SQL data service. It contains a data object as the mapping inputand a virtual table as the mapping output.

¨ Virtual stored procedure mapping. Defines a set of business logic in an SQL data service. It contains anInput Parameter transformation or physical data object as the mapping input and an Output Parametertransformation or physical data object as the mapping output.

What is the difference between a mapplet in PowerCenter and a mapplet in the Developer tool?

A mapplet in PowerCenter and in the Developer tool is a reusable object that contains a set oftransformations. You can reuse the transformation logic in multiple mappings.

A PowerCenter mapplet can contain source definitions or Input transformations as the mapplet input. It mustcontain Output transformations as the mapplet output.

Informatica Developer FAQ 111

A Developer tool mapplet can contain data objects or Input transformations as the mapplet input. It cancontain data objects or Output transformations as the mapplet output. A mapping in the Developer tool alsoincludes the following features:

¨ You can validate a mapplet as a rule. You use a rule in a profile.

¨ A mapplet can contain other mapplets.

What is the difference between a mapplet and a rule?

You can validate a mapplet as a rule. A rule is business logic that defines conditions applied to source datawhen you run a profile. You can validate a mapplet as a rule when the mapplet meets the followingrequirements:

¨ It contains an Input and Output transformation.

¨ The mapplet does not contain active transformations.

¨ It does not specify cardinality between input groups.

Informatica Analyst FAQReview the FAQ to answer questions you may have about Informatica Analyst.

What combination of former product functionality is included in the Analyst tool?

The Analyst tools contains some functionality previously included in the following products:

¨ Informatica Data Quality

¨ Informatica Data Explorer

¨ Data Quality Assistant

¨ PowerCenter Reference Table Manager

Can I use one user account to access the Administrator tool, the Developer tool, and the Analyst Tool?

Yes. You can give a user permission to access all three tools. You do not need to create separate useraccounts for each client application.

What happened to the Reference Table Manager? Where is my reference data stored?

The functionality from the Reference Table Manager is included in the Analyst tool. You can use the Analysttool to create and share reference data. The reference data is stored in the staging database that youconfigure when you create an Analyst Service.

112 Appendix A: Frequently Asked Questions

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