training guide omplete window says … some issues were found. heck the job log. job log says...

Training Guide

Advanced Data Mining

2018 Andar User Group Conference Mason, OH

7300 Warden Avenue, Suite 503 Markham, Ontario Canada L3R 9Z6 Phone: 905-479-3780 Toll Free: 877-479-3780 Fax: 905-479-1047 e-Mail: [email protected] Web: www.AndarSoftware.com.com Copyright © 2018 Andar Software Ltd. All rights reserved. No part of this document may be transmitted, stored in a retrieval system, or reproduced in any way without the written permission of Andar Software. Trainings, demos, presentations, etc., (whether on-site or web-based) may not be recorded, photographed, captured, etc., in any way without the written permission from Andar Software.

2018 User Group – Advanced Data Mining of 27

Contents 1. Basic Data Mining Concepts .................................................................................................................. 4

2. More Complex Selections ...................................................................................................................... 5

Comments Section ............................................................................................................................ 5

Operators .......................................................................................................................................... 5

Clear Selected Accounts ................................................................................................................... 7

Using a Warehouse as Part of Selection .......................................................................................... 7

Call Another DMO in a DMO ............................................................................................................. 7

3. Roll Up Accounts/Data ........................................................................................................................... 8

4. Working with Employees........................................................................................................................ 8

5. Working with Transactions ..................................................................................................................... 9

6. Extracting Designations ....................................................................................................................... 10

7. Mailing Lists and Usages ..................................................................................................................... 11

The basics ....................................................................................................................................... 11

Two Methods for Creating a Mailing List Usage ............................................................................. 11

Comparison of Two Methods .......................................................................................................... 13

Mailing List Usage Options ............................................................................................................. 13

8. Running Canned Reports .................................................................................................................... 15

9. e-Mailing Output ................................................................................................................................... 15

10. Extract Table ................................................................................................................................... 16

11. Transpose ....................................................................................................................................... 16

12. Using SQL in Data Mining ............................................................................................................... 17

Using SQL to Select Accounts ........................................................................................................ 18

Using SQL to Alter the Extract ........................................................................................................ 19

13. Extract Tables Report (MIG) ........................................................................................................... 25

14. General Letters (MIG) ..................................................................................................................... 26


1. BASIC DATA MINING CONCEPTS

Section vs. condition

section is the main DMO step; condition qualifies or defines a section (indented)

Selecting vs. extracting

selecting = rows; extracting = columns

Selecting Accounts

Only active accounts are chosen by default. You do not need to have a select condition from the Bio tab.

Avoid select conditions which should be extract conditions.

It’s not necessary to always save accounts in a warehouse. There is a temporary warehouse called *Current.

Extracting Data

Must always extract from at least one Bio tab. This picks up the account number.

If no accounts are selected

Job Complete window says “… some issues were found. Check the job log”.

Job log says “WARNING: No data found for insert into new Extract SQL table…”.

First data row of spreadsheet has “** No data found”.


If no spreadsheet is created, it means:

there is no Extract/download or Download section.

the DMO ended in error.

Exercises a. Select all Organizations in the Manufacturing node. (Start with Select Accounts >

Organizations.) Extract Organization Name, ECC name and work phone number (from the Contacts tab), and last year overall employee gift.

b. Select all ECC Contacts of Organizations in the Manufacturing node. (Start with Select Accounts > Contacts.) Extract Organization Name, Individual name (i.e. the ECC’s name), ECC’s work phone number (from the Phone tab), and last year overall employee gift.

c. Create a DMO that selects Individuals with a current year gift of $1,000 or more. (Use the Gift tab. Include all types of gifts: Employee, Indiv, Other, etc., but only in the UW Campaign.) Save accounts in a warehouse. (We will use this later.)

2. MORE COMPLEX SELECTIONS

COMMENTS SECTION

allows you to add your own comments, usually to explain a more complex DMO

will show up as tooltip text for the section

printed out the DMO Report

OPERATORS

AND ................Both first and second conditions are true for selected accounts. OR ...................First or second condition is true for selected accounts. (Or both could be true.) AND NOT ........First condition is true and second condition is false for selected accounts. OR NOT ...........First condition is true or second condition is false for selected accounts. (Rarely

used)

Used to join multiple Select conditions.

Rule of Thumb: If you have both ANDs and ORs, use parentheses.

Remember from grade school - in an equation we do:

what's in parentheses first

then multiplication and division

then adding and subtracting

E.g. 6 + 3 x 2 = 12 But (6 + 3) x 2 = 18

Similarly, in a DMO we do the ANDs first, then the ORs


Example: You want all your Direct Mail donors who gave this year or last year.

Donor Name Node 2011 Gift 2012 Gift Lloyd Skinner Direct Mail $500 $0 Mike Hamilton Direct Mail $250 $250 April Isaac Direct Mail $0 $100 Nora Wilson Direct Mail $0 $0 Brenda Lucas Leadership $2500 $0 Randy Tripp Leadership $1000 $1000 Taylor George Leadership $0 $1200

This DMO:

Select Individual Accounts Where: Ind. in Structure Node ‘Direct Mail (10)’ AND Ind. Gift 2012 … OR Ind. Gift 2011 …

will select these accounts:

Lloyd Skinner Mike Hamilton April Isaac Brenda Lucas Randy Tripp

But this DMO:

Select Individual Accounts Where: Ind. in Structure Node ‘Direct Mail (10)’ AND ( Ind. Gift 2012 … OR Ind. Gift 2011 … )

will select these accounts: Lloyd Skinner Mike Hamilton April Isaac


CLEAR SELECTED ACCOUNTS

Removes from the *Current warehouse, all Accounts that have been selected so far

Does not delete accounts from Saved Account Warehouses or Mailing Lists

When save accounts to a Warehouse or Mailing List

this copies accounts from *Current warehouse to the specified Warehouse or ML

they remain in *Current warehouse until cleared

USING A WAREHOUSE AS PART OF SELECTION

In the Select Accounts section, where a relationship is involved

As a Select condition

Example: Find all United Way volunteers who are neither a Leadership giver nor the spouse of a Leadership giver.

CALL ANOTHER DMO IN A DMO

Insert Section > Execute > Another Data Mining Operation

submits another, existing DMO to refresh a warehouse or mailing list Exercises

For these exercises, extract just the Individual name

a. Pull all ECCs of all Organizations in the Manufacturing node. Include Organizations with no ECC contact. If the Organization has multiple ECCs, include all of them. Pull the same columns as above. (Start by making a copy of your DMO from 1.b.)

b. Select Loyal Contributors (under Dates) and Business Owners (demographic ‘Owns Own Business’) that you haven’t communicated with in the past 6 months.

c. Select all Individuals who were United Way volunteers during the 2013 calendar year. Exclude those who are $1,000+ donors or the spouse of a $1,000+ donor. Execute the DMO created in 1c as part of your larger DMO.

d. Select all employees of Organizations in the Retail node. Exclude employees of Superstore and its subsidiaries. (Account #3244 Superstore Yonge and Sheppard is the Parent account.)

e. Select all Loyal Contributors and their spouses. Save in a warehouse. Extract from the General Rel tab so you can see who has the spouse relationship. Hint: you must have a Clear Selected Accounts section.


3. ROLL UP ACCOUNTS/DATA

Method

Select all subsidiary accounts > save in warehouse

Clear selected accounts

Select Organizations with desired conditions

Add another condition AND NOT in the Subsidiary warehouse

Note: Child billing accounts automatically excluded when select from the A/R tab; when extract from the A/R tab, transactions are on consolidated billing account.

Select and Extract Conditions

Can select accounts based on:

Gift RU

Numerical – Number of Employees Roll Up

RankingRU

TrackParmRU

Can extract same RU data, plus

Leadership – check the ‘Include Subsidiaries’ box.

Numerical – check the ‘Include Subsidiaries’ box to roll up any numerical info.

Cannot use Node Ranking (MIG), Pattern or Track Analyze for rollup Exercises

Find the top 20 accounts, based on current year C+E+S gifts. Pull the rank and position. Also from the General Rel tab, extract the Group Number Hierarchy for the Parent/subsidiary relationship.

o Start by using the Ranking tabs. Keep the results. o Create a second DMO using the Ranking RU tabs. Compare to the Ranking tab.

You decide the Roll Up dollars are what you need, but subsidiaries should not be included in your extract.

4. WORKING WITH EMPLOYEES

Select Accounts > Employees

Effective Date Selects Employee Relationships that are unexpired on the selected date

Select a single employer per employee Selects just one relationship per individual, looking first for the preferred employer, then for the most recently created relationship.

Gift extract > Account Type > Both

Extracted gift will match BOTH the Org and Ind accounts in the selected warehouse.

Must extract from both Org and Ind Bio tabs.

Note: Workplace Special Event transactions do not create an employee relationship.


Exercises

Pull all employees of Andar Software. Extract the 2012 employee gift from the Gift tab.

o First use Account Type = Individual. Check Campaign Type = Employee. Compare the total to Helix’s employee gift on the Camp History sub-tab.

o Try using Account Type = Both. What is the difference? Why does the total still not agree with Helix’s total employee gift amount?

5. WORKING WITH TRANSACTIONS

Selecting accounts based on Transactions

Select Accounts > Transactions

Get both Organization and Individual accounts in the warehouse, like employee and contact relationships

Not based on employee relationship, but on combination of accounts on transactions

Includes memos unless deselect memo trans types

Selection based on existence of a transaction – even if net amount is zero Select Accounts > Individuals > Trans tab

Get only Individual accounts in the warehouse

Does not matter if transaction has an Organization account number also Select Accounts > Organizations > Trans tab

Get only Organization accounts in the warehouse

Will not consider transactions that have an Individual account number also. e.g.

Company ABC has only a batch payroll transaction

Company MNO has a batch payroll transaction and many non-batch

Company XYZ has only non-batch payroll transactions

If you select Organizations from Trans tab and select payroll transaction type, will get only Company ABC and Company MNO.

With all these three, can select accounts with transaction in any status (incl. open envelopes)

c.f. Gift tab, which looks only at processed transactions

Extracting from the Trans tab

Extract will have one row per selected transaction; c.f. Gift tab which is one row per account.

Two sub-tabs:

Attributes – you are selecting the transaction rows

Transactions with account numbers matching the extracted Bio tab(s) will be selected. i.e.

If you extract from the Bio (Ind) tab only, transactions matching the Individual account will be selected.


If you extract from both the Bio (Ind) and the Bio (Org) tabs, transactions matching both accounts will be selected.

Data – here you select the columns you need in your extract.

Note: Account numbers and names can be extracted here. Exercises

a. Using Select Accounts > Transactions, select donors who pledged through Helix in 2012. Extract the 2012 employee gift from the Gift tab.

b. Again using Select Accounts > Transactions, select donors who pledged through Helix in 2012.

i. Extract the Ind Bio tab. Extract 2012 employee transactions from the Trans tab. Choose Accounting Date, Total Pledge and Transaction Type.

ii. Extract both the Ind and Org Bio tab. How is this different than just extracting the Ind Bio tab?

c. You started using the Event Participation transaction types in 2011. You need to verify that all Event Participation transaction types entered in 2011 had the Event account and occurrence entered.

i. Select Individuals that have any of the 4 Employee or 4 Individual Event Participation transaction types. Extract the 2011 Event Participation transactions. Check the Total Pledge and Event boxes (this pulls Event account, name, occurrence, start and end date and time).

ii. You realize there are also Corporate Event Participation transactions. Add to your DMO to pull these 4 transaction types as well.

6. EXTRACTING DESIGNATIONS

There are two ways to extract designations:

Example: Pull designations for Macmillian employees with a current year gift.

Use Data Mining

Extract from Trans tab, then Desig tab

You will get one row per designation, i.e. could have multiple rows per person

You will also get rows for payment transactions

Use Designations Download Utility

Use Data Mining to extract all desired data except designations.

Save output as .csv file.

Go to Donor Choice Management > DC Administration > Designations Download Utility

adds columns for designations to an existing spreadsheet

get one row per Individual account

done on *Local processor - no Job Completed window

Go to System > My Output. Output name is Designations Download.


Exercises a. Start by making a copy of your DMO from 5.b.ii. Extract the 2012 designations of Helix

employees. Extract Total Donation and Designated Account #/Name. b. Save your output from the above exercise to My Documents. Use the Designations

Download Utility to add the 2012 designations to this output.

7. MAILING LISTS AND USAGES

THE BASICS

Mailing List (ML) – is a changing list of accounts. It also includes:

7 pecking orders for Name, Address, Salutation, e-Mail Address, Phone Number, Fax Number and Contact Type

Mailing List Usage default values

Mailing List Usage (MLU) – keeps a record of each time a Mailing List is used.

You add a Mailing List Usage to a Mailing List each time you use the list.

It is a snapshot of who was contacted, along with their pecked name, address, salutation, e-mail, etc. (using the ML pecking orders)

The MLU can also refine the list of accounts in the ML by merging combined accounts, eliminating duplicates, excluding Anonymous or Opt Out accounts. i.e. an account may be in the ML but not the MLU.

Also used for:

Summarizing pledge data from pledges entered with the MLU source code

E-mail tracking e.g. number of reads and clicks, number subscribed / unsubscribed to e-newsletter

TWO METHODS FOR CREATING A MAILING LIST USAGE

Using Menu Options

Step 1 – Use Data Mining to create a Mailing List


Step 2 – Create Mail List Usage Communications > Mailing List Management > Mailing Lists

High-light Mailing List > click Usage > click Add

Step 3 – Wait for Ready status, then download Mailing List High-light Usage > click Download

Choose Field Separator = comma Compare EMPLOYERNAME1 (column R), which is part of the address, to

ORGNAME1 (column CW), which is the Org in the Mailing List.

Step 4 – Delete Unnecessary Mailing List Usages High-light Usage > click Delete

Through Data Mining

Step 1 – Use Data Mining to create a Mailing List

Step 2 – In the same DMO, Create Mailing List Usage Insert Section > Create Mailing List Usage

Select the Mailing List name to get Usage defaults

Step 3 – Extract Data and Download Insert Section > Extract Data and Download

Remember to update with the Mailing List Name!

Step 4 – Add Extract Conditions Extract from the Mailing tab!

Step 5 – Delete Unnecessary Mailing List Usages Communications > Mailing List Management > Mailing Lists

High-light Mailing List > click Usage > high-light Usage > click Delete


COMPARISON OF TWO METHODS

Using Menu Options Through Data Mining

Knowledge of

Data Mining

Not required Required

Data in extract Limited to name, address, etc. Anything that Data Mining allows

List of Usages Tend to be well maintained. This is

important when relying on MLUs to track

when an account is contacted.

Tend to become a mess. Not as important

when using Communications to track

when an account is contacted.

Additional

Options

- add to existing file

- all upper case

- none

Date Used and

Status

When download, Date Used is populated

and Status changes to ‘Used’

Date Used is not populated and Status

remains at ‘Ready’

Comments

Good when one person can create ML in

DMO and another person does mail

merge and envelope stuffing. Schedule

DMOs to refresh MLs nightly so they are

up to date when needed.

Users tend to forget to select the ML

under 'Extract/download data from …'

section. Cannot extract from Mailing tab.

If don't do this, there is not much point to

using ML and MLU.

MAILING LIST USAGE OPTIONS

Exclude Anonymous Accounts Based on checkbox under Account Profile > Contact Info > Privacy Dfts

Merge Combined Givers

To get one row per Combined Giver Group

Based on Current Year Combined Giver Relationship AND on having the selected salutation type on only one account in the group.

Combined account with the selected salutation is put into the Usage, even if account was not in the original selection. Other combined account(s) is/are simply excluded from the Usage.

If none or more than one of the combined givers has the selected salutation, they won't be merged.

Override merged account’s salutation with the selected salutation type - will override pecked salutation.

Override merged account’s name with Combined Giver Name - will override pecked name.


Also Merge Combined Giver with picked employer address - If an employer address is pecked:

If the box is checked, the Combined Giver Group will be sent one piece of mail using the pecked employer address.

If the box is not checked, the accounts in the Combined Givers Group will not be merged.

Remove duplicate individuals at different organizations

E.g. Select Employee Campaign Coordinators. Same ECC is on multiple subsidiary accounts. Check this box so ECC will get only one piece of mail. Organization with the Preferred Employer flag will be included.

Can also mean the same account is in Mailing List twice - once with an organization account and once without. When checked, the row without an organization account will be removed from the MLU.

Take the attached organization as employer

For address pecking, instead of using the organization from the Employment Relationship, the organization in the Mailing List is used to get the address.

Most often the organization in the Mailing List is the Employer, but not always. E.g. You have selected Board Members based on Affiliation relationships but those individuals don't actually work at those Orgs.

NOT recommended in most situations.

Include Opt In/Exclude Opt Out Accounts

Based on rules on Account Profile > Contact Info > Contact Rules.

Only include opt in accounts – An account will be included in the Usage if it has the opt in flag for the current month. i.e. opt out and unspecified are excluded.

Exclude opt out accounts – An account will be excluded from the Usage if it has the opt out flag for the current month. i.e. opt in and unspecified included.

The system date is used to compare with the effective date range.

Andar users who have the Major Gift license can additionally refine the Include/Exclude accounts based on Category.

Exclude ‘Blank’ Accounts

An account will be excluded from the Usage if it has no data for every selected Mail Type. E.g. You select By Postal and By e-Mail Mail Types and the account has no pecked address and no pecked e-mail.

Generate Care Of Account (MIG)

If an account is the Addressee in a Care Of relationship (under General Relationships), contact information for the Care Of Host will be extracted in place of the Addressee’s contact information.


Mail Types

Has two purposes:

Controls which data is extracted.

Used in conjunction with Include Opt In/Exclude Opt Out and Exclude Blank Accounts.

Exercises

Create a Mailing List for the Kick-off invitation.

Invite all Leadership givers (excluding Active Community Investors, who give $500 – 999) and invite current United Way volunteers. Send to their home address. Merge Combined Givers.

Add to the same DMO. We need to also invite all CEOs and ECCs. Send to their workplace address. Be sure to exclude those CEOs and ECCs who are leaders or volunteers.

8. RUNNING CANNED REPORTS

Insert Section > Reports

Presented with a tree of all Andar reports, in Main Menu order

Drill Down > select Report

Presented with Report options on the right-hand side

When running the report by Warehouse is an option, you can select the *Current warehouse (exception is the DC Summary Management Report)

Cannot select Saved Parameters from here Exercises

Select Orgs in the state of Ohio (based on Street Address). Run the Allocable Designations Report for this *Current warehouse. (Found under DC Reports.)

9. E-MAILING OUTPUT

Insert Section > e-Mail Output

For e-mailing DMO outputs to one or more recipients. E-Mail will contain attachments of all output generated by previous steps.

Required:

Who to send to, e.g. one account, mailing list, warehouse, send to user executing this data mining operation

Subject line – prompted if blank

E-mail text or template

Clear Output Section

Removes previous outputs (extracts and reports) so they won’t be e-mailed again.

For example:

Create an extract and e-mail to User A.


Clear Output

Create a report and e-mail to User B.

This ensures User B does not get User A’s extract.

Exercises

Select accounts managed by Loaned Executive William Ackroyd. Extract Org Name, and the Goal, Reported, and Processed for the current year employee campaign. E-mail his report to yourself, by keying your e-mail address into the ‘To Recipient Address’ field.

Repeat for LE Drew Terrell.

Don’t forget to Clear Accounts and to Clear Output.

10. EXTRACT TABLE

For more advanced Data Mining functions, it’s important to understand what’s going on behind the scenes.

The Extract Data and Download section does two things:

Extract Data

Creates a database table in the data extract database (separate from your production database)

The table is populated with rows and columns you requested

By default, this table is named TEMPxxx and the table is deleted after the DMO runs

However, you can choose to rename and retain the extract table

Download Extract to My Output

Copies data from the extract table into a csv file and puts it in My Output

Sometimes you do not need the download step, you want to perform additional operations on the extract table before you download it. You can control this section by:

Changing Extract Table Name and Description

Unchecking Download Extract to Output

Changing Output Name (do this even on simple DMOs)

Unchecking Delete Extract Table After Download

There are also separate sections for:

Extract Data

Download Data to My Output

11. TRANSPOSE

Enables extracting all accounts in the same general relationship in a single row

Example: Pull all leadership givers. Get the individual and combined gift amounts, individual and combined leader levels, employer, and birthdate of each. Need one row per couple.


Steps:

Select accounts and Extract data as usual

Extract from General Rel tab

Select Group Number Hierarchy

If working with Combined Givers, select Salutation Type.

Click on ‘Extract/download data from…’

Uncheck the Delete Extract Table After Download box

May optionally uncheck Download Extract To Output

Click on Update.

Insert Section > Transpose Extract Table

Select columns to display on other account(s)

Note the top half of the screen has same options as Extract Data and Download

May optionally change the Output Name

Click on Insert Section.

Exercises

Pull your current Board of Directors. Pull their Assistant if they have one (relationship = Supervisor/Assistant). Include the Individual Work phone number of both.

12. USING SQL IN DATA MINING

Need to know the name of your:

Data extract schema and database; typically it’s DataExtract.Andar (Look under System Preferences > General > Data extract table prefix)

Production schema; typically it’s Andar

Those who are hosted by UPIC and IT Collaborative (and some other customers, as well) will have different schema and database names.

Where to find column and table names:

1. Help > Contents > Andar Database Tables (down and to the right)

Click on this link, then click on table description, or

Click on Complete List of Andar Database Tables and Fields

2. Locate desired data on the Andar screen

Click Help > What is this?

Click on field on in table column > look for help items

About “tablename” database file

About “columnname” database field


USING SQL TO SELECT ACCOUNTS

Use the SQL tab to insert conditions into the query Data Mining is building.

Unless testing a column in Individuals or Organizations, begin with exists (…) or accountnumber in (…)

Queries that do not use production database name are more portable (can used in Training database or shared with other users)

The note above the query window will tell you how to link the selected account type (Org, Ind, employees, etc.) to other tables.

Query text is limited to 4096 characters.

Example: Pull the Individual accounts that were updated by a Connector import during a certain date range. We want just the ones that were updated, not those that were created.

Example: On the billing schedule there is a checkbox ‘Do not issue statement’. We think this has been used incorrectly. Find all the Orgs with this box checked in years 2010 – 2013.

Example: Find Individual accounts that have the same e-mail address for Main and Work.

Both of these queries will work:

exists (select * from andar.emails mn join andar.emails wk on mn.accountnumber = wk.accountnumber where i.accountnumber = mn.accountnumber and mn.emailtype = 'Main' and wk.emailtype = 'Work' and mn.emailaddress = wk.emailaddress)


i.accountnumber in (select mn.accountnumber from andar.emails mn join andar.emails wk on mn.accountnumber = wk.accountnumber where mn.emailtype = 'Main' and wk.emailtype = 'Work' and mn.emailaddress = wk.emailaddress)

USING SQL TO ALTER THE EXTRACT

After the Extract step, we can run SQL queries on the temporary table to:

delete rows from the extract

delete columns from the extract (non-MIG)

add a column for

a calculated amount

string manipulation

to bring in other data

change column headers (non-MIG)

General Steps:

1. Start by creating and submitting a DMO that selects accounts and extracts as usual, without any SQL queries.

2. From the csv file, get the names of the columns you will need to copy and paste into the SQL queries.

3. Change the Extract/download data section to simply Extract Data by unchecking the box ‘Download Extract to Output’.

4. Add SQL queries: Insert Section > Execute > SQL Statement In the queries, use the TEMPxxx table name found in the Extract data section.

5. As the last step, Insert Section > Download Extract to My Output Enter the Output Name. This will be the Name you see under System > My Output, instead of Extract Data Download.

Sample queries are supplied at the end of this document for you to copy and paste.

Example 1 - Deleting Rows

Pull the current volunteers on the Golf Tourney Organizing Committee (GTOC) and include their volunteer hours. In addition to rows for the GTOC, you can get a row for any other volunteer opportunity that a GTOC member is on. Remove these from the extract.


1. Here is the DMO we start with.

2. We need to know the column name for Opportunity number (VOLASSIGNED_IND_ANY_OPSNUMBER) and that the GTOC opportunity number is 24.

3. Uncheck the ‘Download Extract to Output’ box in the Extract/download data from… section.

4. Add an SQL statement to delete rows where the Opportunity is not GTOC. Make sure the TEMP table number matches that in the Extract data section.


5. Insert Download Extract to My Output section. Enter the Output Name.

Now our output looks like this:

Example 2 – Changing column headers, deleting columns and adding a column

Pull the Orgs in the Major Firms node. Include the CEO name and work number, two years of Corporate gift, and the % change in the gift amount.

1. Here is the DMO we start with. When extracting from the Contacts tab, check the box ‘Exclude effective date from column heading in extract table’.


2. We want to change the column headers for the two gift amounts. Our calculation will use the new column headers. We also want to delete those extra columns (contact type, account number, sort field) for the CEO.

3. Uncheck the ‘Download Extract to Output’ box in the Extract/download data from… section.

4. Add SQL Queries

a. Change the column headers. (Don’t forget to change the TEMP table number.) You can change more than one header in the same SQL Statement section, but it will become difficult to read. (This print screen was made to be readable – the queries will run together as one long string.)

b. Add a column to your TEMP table with this query:

c. Calculate the values for the new column.

d. Delete the unwanted CEO columns.


5. Insert Download Extract to My Output section.

Now our output looks like this:

Exercises To Select Accounts

a. Find Individual accounts created by Connector#102. Extract name, gender, anonymous flag and birthdate. (To see how the Create User is formatted for Connector imports, see account 41897 as an example. Go to Audit Log tab > Audit sub-tab.)

b. Select Individuals that have the Do Not Merge flag checked on the Main Bio. c. Find both Individuals and Orgs that have a billing schedule with the flag ‘No Overriding

Thru Transactions’ checked in the previous or current year. To Alter the Extract

d. Select individuals who designated to the Education service category. Extract designations. Delete rows that are not designations to Education.

e. In your DMO extract from exercise 1a, delete the Contact Type and Contact Sort field columns.

f. Select Manufacturing accounts. For current and previous year, extract the total of the Corp + Empl + Special Event gifts (in one column).

a. Add a column and calculate the % increase. i. Change the Gift column headers to something readable.

ii. Concatenate Org Names 1 and 2.


SQL queries for you to copy and paste:

delete from dataextract.andar.TEMPxxx where VOLASSIGNED_IND_ANY_OPSNUMBER <> 24

<> means not equal to

execute ('use dataextract exec sp_rename [andar.TEMPxxx.from column name], [to column name], [COLUMN] ')

alter table dataextract.andar.TEMPxxx add Per_Change decimal(5,2)

(5,2) means 5 digits in total including 2 digits after the decimal. You may use other data types such as:

char(40) for a name char(8) for a date int for a campaign year

update dataextract.andar.TEMPxxx set Per_Change = ( [2012_Gift] - [2011_Gift] ) / [2011_Gift] * 100

alter table dataextract.andar.TEMPxxx add Full_Org_Name char(81)

update dataextract.andar.TEMPxxx set Full_Org_Name = rtrim(orgname1) + ‘ ‘ + ltrim(orgname2) alter table dataextract.andar.TEMPxxx drop column CNT_ORG_CEO_CONTACTTYPE, CNT_ORG_CEO_ACCOUNTNUMBER, CNT_ORG_CEO_SORTFIELD


13. EXTRACT TABLES REPORT (MIG)

For generating a pdf report based on data in an Extract Table, or Sorting, excluding columns, renaming columns in a csv report.

Steps:

Select accounts and Extract data as usual

Click on ‘Extract/download data from…’

Uncheck the Delete Extract Table After Download box

Click on Update.

Insert Section > Reports > Data Mining > Extract Tables Report

Sorting and Summaries tab

Select columns for sorting

Click on for ascending / descending

Use Top, Up, Down, Bottom to change order of sort fields

For each sort field, optionally select New Page or New Lines, and Summary Operations

Columns tab

Select columns to print on report

Use Add, Remove, Move Up, Move Down to change list and order

Use Insert New Line when you want to “stack” data items; check New Line on first field after --- Line separator ---.

For each column, update Header, Layout and Label tabs

System tab

Select pdf or csv report

Summaries, Layout and Label not supported in csv report

A report can also be created and saved from menu option Data Mining > Extract Tables Report based on an existing Extract Table.

Exercises

Select all Organizations in the 2013 MAIN Business node (and child nodes). Using the Pattern tab, include only Orgs with Employee giving in both 2012 and 2013. Then create a PDF report like the one on the following page.


14. GENERAL LETTERS (MIG)

For generating pdf letters (to print or e-mail) based on data in Mailing List Usage or Extract Table.

Steps:

Select Accounts

Save accounts in Mailing List

Create Mailing List Usage

Extract Data (Optional)

Do this when your letter requires data not available in the ML Usage, e.g. gift amount, leadership level, etc.

The Extract Data section must select from a Mailing List

Ensure Delete Extract Table After Download is unchecked

You must extract:

Both Ind AND Org Bio tabs

From the Mailing tab – check Mailing List Name and Generated ID


Create a General Letter Template

Can be done:

Inside the DMO using the Create General Letter section, selecting Mailing List or

Extract Table, and clicking green + icon

Can use only current Extract Table

Note: To update an existing General Letter template from within a DMO, click on the folder icon. Status must be Open to update.

Under menu option Communications > General Letters > General Letters Templates Maintenance

Find ML Usage fields under Insert Options > Note Variable

Can also insert fields from a selected Extract Table

Create General Letter

Template status must be Ready

Can be done:

Inside the DMO using the Create General Letter section

Under menu option Communications > General Letters > Create General Letters

Select PDF letter options: single PDF, mailing labels, e-mail PDF as attachment or embedded in e-mail body

Select Communication Log options: communicator, type, subject, attachment Exercises

Start by making a copy of your DMO from 7.a. Remove all select conditions except for Volunteers (so our jobs will run faster). Create General Letters for this Mailing List, using the Kickoff Invite template. Create PDF letters only. Put all letters into a single PDF. Do not create Communication Logs.

End of Training Guide

End of Workbook

End of Workbook