storage of data resources2

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E. Wainright Martin Carol V. Brown Daniel W. DeHayes

Jeffrey A. HofferWilliam C. Perkins

MANAGINGINFORMATION

TECHNOLOGYFIFTH EDITION

CHAPTER 5

THE DATA RESOURCE


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2005 Pearson Prentice-Hall Chapter 5 - 2

Organizations could not function longwithout critical business data

Cost to replace data would be very high

Time to reconcile inconsistent data maybe too long

Data often needs to be accessed quickly

WHY MANAGE DATA?

Page 135


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Data should be: Cataloged

Named in standard ways

Protected

Accessible to those with a need to know

Maintained with high quality

WHY MANAGE DATA?

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TECHNICALASPECTS OFMANAGING THE DATA RESOURCE

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Data modeloverall map for business data needed to effectively

manage the data

The Data Model


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2005 Pearson Prentice-Hall Chapter 5 - 5 Page 135

Data modeling involves:

Methodology, or steps followed to identifyand describe data entities

Notation, or a way to illustrate data entitiesgraphically

The Data Model



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Entity-relationship diagram (ERD)

Most common method for representing adata model and organizational data needs

Captures entities and their relationships

Entities things about which data are

collected Attributes actual elements of data that are

to be collected

TECHNICALASPECTS OFMANAGING THE DATA RESOURCEThe Data Model


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2005 Pearson Prentice-Hall Chapter 5 - 7 Page 135Figure 5.1 Entity-Relationship Diagram

NOTE:

Entities are Customer, Order, and Product.

Attributes of the Customer entity could be

customer last name, first name, street, city,

TECHNICALASPECTS OFMANAGING THE DATA RESOURCEThe Data Model


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Enterprise modeling Top-down approach Describes organization and data

requirements at high level, independent ofreports, screens, or detailed specifications

Not biased by how business operates today

TECHNICALASPECTS OFMANAGING THE DATA RESOURCEData Modeling


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Enterprise Modeling Steps:

Divide work into majorfunctions

Divide each function intoprocesses

Divide processes intoactivities

List data entities

assigned to each activity

Identify relationshipsbetween entities


Figure 5.2 Enterprise Decompositionfor Data Modeling


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View integration Bottom-up approach Each report, screen, form, document

produced from databases first eachcalled a user view



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View Integration Steps:

Create user views

Identify data elements in each user view and put into astructure called a normal form

Normalize user views

Integrate set of entities from normalization into onedescription


Normalization

process of creating simple data structures from more complex

ones


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2005 Pearson Prentice-Hall Chapter 5 - 12 Page 136-137

Data modeling guidelines: Objective effort must be justified by need Scope broader scope, more chance of

failure

Outcome uncertainty leads to failure

Timing consider an evolutionary approach



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TECHNICALASPECTS OFMANAGING THE DATA RESOURCEDatabase Architecture

Database

shared collection of logically related data, organized tomeet needs of an organization

Database Architecture

way in which the data are structured and stored in the

database


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2005 Pearson Prentice-Hall Chapter 5 - 14 Page 137Figure 5.3 The Data Pyramid


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Six basic database architectures:

1. Hierarchical (top-down organization)

2. Network (high-volume transaction processing)

3. Relational (data arranged in simple tables)

4. Object-oriented (data and methods encapsulated in objectclasses)

5. Object-relational (hybrid of relational and object-

oriented)

6. Multidimensional(used by data warehouses)

Database Architecture


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TECHNICALASPECTS OFMANAGING THE DATA RESOURCETools for Managing Data

Database Management System (DBMS)

support software used to create, manage, and protectorganizational data


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A DBMS helps manage data by providingseven functions:

1. Data storage, retrieval, update2. Backup

3. Recovery

4. Integrity control

5. Security control6. Concurrency control

7. Transaction control

Tools for Managing Data


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Most popular type of database architectureis relational

Not all relational systems are identical.

Best effort to date for standardizingrelational databases is SQL



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2005 Pearson Prentice-Hall Chapter 5 - 19 Page 139-140


Contains:

Definition of each entity,

relationship, and data

element

Display formats

Integrity rules

Security restrictions

Volume and sizes List of applications that use

the data


Data Dictionary/Directory (DD/D)

central encyclopedia of data definitions and usage

information a database about data


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TECHNICALASPECTS OFMANAGING THE DATA RESOURCEDatabase Programming

Query language

a 4 GL, nonprocedural programming language to obtain

data from a database, often provided by the DBMS

SQL query language example:

SELECT ORDER#, CUSTOMER#, CUSTNAME,

ORDER-DATE FROM CUSTOMER, ORDER

WHERE ORDER-DATE > 04/12/05

AND CUSTOMER.CUSTOMER# =

ORDER.CUSTOMER#


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The need to manage data is permanent

Data can exist at several levels

Application software should be separate from thedatabase

Application software can be classified by how theytreat data

1. Data capture2. Data transfer

3. Data analysis and presentation

MANAGERIAL ISSUES INMANAGING DATA

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Principles in Managing Data


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2005 Pearson Prentice-Hall Chapter 5 - 22 Page 142Figure 5.4


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Application software should beconsidered disposable

Data should be captured once

There should be strict data standards


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Page 143


Figure 5.5 Types of Data Standards


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Page 144

The Data Management Process

Figure 5.6 Asset Management Functions


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2005 Pearson Prentice-Hall Chapter 5 - 26 Page 146Figure 5.7 The Data Warehouse


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Organizations should have policies regarding:

Data ownershipData administration

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Data Management Policies


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Page 148

Data Ownership

Corporate information policy

foundation for managing the ownership of data


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2005 Pearson Prentice-Hall Chapter 5 - 29 Page 149Figure 5.8 Example Data Access Policy


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Data Administration

Page 150

Key functions of the data administration group:

Promote and control data sharing

Analyze the impact of changes to application systems when datadefinitions change

Maintain the data dictionary

Reduce redundant data and processing

Reduce system maintenance costs and improve system

development productivity

Improve quality and security of data

Insure data integrity



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Data Administration

Page 150-151

Key functions of the database administrator (DBA):

Tuning database management systems.

Selection and evaluation of and training on database technology.

Physical database design.

Design of methods to recover from damage to databases.

Physical placement of databases on specific computers and

storage devices. The interface of databases with telecommunications and other

technologies.


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