CE Student Guide PC_HandsOnWorkshop

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Informatica PowerCenter Hands-On Workshop

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Agenda

Time Topic

9:00 Introduction to Informatica

9:30 Introduction to Informatica Data Integration Platform

10:00 Introduction to PowerCenter

10:30 Tutorial Lesson 1


12:30 Lunch



2:30 Using the Debugger

3:00 Putting It All Together


4:30 Review and Q/A

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Workshop Objectives

By the end of the day you will:

• Understand – the broad set of data integration challenges

facing organizations today and how the Informatica Platform

can be used to address them

• Access – data from different data sources and targets

• Profile – a data set and understand how to look for basic

problems that need to be solved

• Integrate – data from multiple sources through Extraction,

Transformation and Load (ETL)

• Debug – data integration processes (mappings)

• Expose – integration logic as Web Services for use in a SOA

architecture

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2005 2006 2007 2008 2009 2010 2011 2012

Informatica The #1 Independent Leader in Data Integration

• Founded: 1993

• 2012 Revenue: $811.6 million

• 7-year Annual CAGR:

17% per year

• Employees: 2,810+

• Partners: 450+

• Major SI, ISV, OEM and

On-Demand Leaders

• Customers: Over 5,000

• Customers in 82 Countries

• Direct Presence in 28 Countries

• # 1 in Customer Loyalty Rankings

(7 Years in a Row)

5

Global Presence & Global Perspective

Employees in 26

Countries….and growing!

Product Development Customer Support Professional Services

6

Why Informatica?

Proven Technology Leadership

7

Product Leadership Proven Technology Leadership

B2B Data Exchange

Informatica supports the

requirements of cross-organizational

data exchange, so users apply

familiar & trusted data integration

tools and techniques to the growing

practice of B2B data integration.

Cloud Data Integration Enterprise Data Integration

Complex Event Processing

Informatica received high praise for

its services from customers. For

deployments involving systems

monitoring use cases, Informatica

offers a five-day stand‐up of

RulePoint.

Ultra Messaging

In spite of the new entrants,

Informatica remains the market

leader in this highly demanding part

of the messaging market.

Data Quality Master Data Management

Application ILM

ULTRA

MESSAGING

COMPLEX EVENT

PROCESSING

B2B DATA

EXCHANGE

CLOUD DATA

INTEGRATION

ENTERPRISE DATA

INTEGRATION

APPLICATION

ILM

DATA

QUALITY

MASTER DATA

MANAGEMENT

8

Q1 2012

Informatica 9.1

Data Quality

Q4 2010 Cloud

• Cloud Express • Trust.InformaticaCloud.com • B2B & AddressDoctor plugins

• Big Data Integration • Self Service • Adaptive Data Services • Authoritative & Trustworthy Data

Q2 2011 Informatica 9.1

Q4 2011 ILM 9.1 MDM 9.2

• Dynamic Data Masking • Unified Registry & Hub MDM

Q3 2011 Ultra Messaging

Cloud MDM

• UM PowerCenter integration • Broad Cloud Connectivity • DQ Dashboards and Reports • MDM Counterparty Master • MDM Social Networking

Q1 2011 CEP 5.2

MDM

• Proactive Monitoring Options for DQ, PC

• MDM for DB2 • MDM Securities Master

Why Informatica? A Track Record of Continuous Innovation

• DQ templates

• DR 9.1 for Sybase

• CEP Proactive PC Monitoring

Q2 2012

Informatica 9.5

• Data Services 9.5

• PowerCenter 9.5

• PowerExchange 9.5

• Data Quality 9.5

• Data Explorer 9.5

Q3 2012

ILM DDM 9.5.1

IIR 9.5

MDM 9.5

• DVO 9.5

• ILM Dynamic Data

Masking 9.5.1

• Informatica Identity

Resolution 9.5

• Informatica MDM-

Registry Edition

9.5

9

Why Informatica? Empowering the Data-Centric Enterprise

Business &

Operational

Intelligence

Legacy

Retirement

Application

ILM

Customer,

Supplier,

Product

Hubs

BPO

SaaS

B2B

Integration

Application

Consolidation

Risk

Mitigation &

Regulatory

Reporting

Zero

Latency

Operations

Data Warehouse

Data Migration

Test Data Management & Archiving

Master Data Management

Data Synchronization

B2B Data

Exchange

Data

Consolidation

Complex Event Processing

Ultra

Messaging

Improve

Decisions

Modernize

Business

Improve

Efficiency

& Reduce

Costs

Mergers

Acquisitions

&

Divestitures

Acquire &

Retain

Customers

Outsource

Non-core

Functions

Governance

Risk

Compliance

Increase

Partner

Network

Efficiency

Increase

Business

Agility

BUSINESS IMPERATIVES

IT INITIATIVES

DATA INTEGRATION PROJECTS

10

Why Informatica? The Neutral, Trusted and Preferred Partner

OEM Partners Cloud Global SI Partners

Database and Infrastructure

BI OEM Partners Cloud Partners Global SI Partners

Database & Infrastructure

Operating Systems

Platforms & Technologies

INFORM SI

Partners

11

Secular Technology Megatrends IT is Changing

CLOUD

ON-PREMISE TRANSACTIONS DESKTOP

MOBILE INTERACTIONS

12

Data Integration Data is Changing

CLOUD

ON-PREMISE

INTERACTIONS

TRANSACTIONS

MOBILE

DESKTOP

13

Maximize Return on Data

14

We empower organizations to maximize return on

data to drive their top business imperatives

Our Singular Mission Maximize Return on Data

= Value of Data

15

Informatica Value Proposition Increase Value Of Data by Enabling Top Business Imperatives And Reduce IT Costs

TRANSACTIONS INTERACTIONS DESKTOPS MOBILE CLOUD ON-PREMISE

16

The Informatica Platform

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18

TRANSACTIONS INTERACTIONS DESKTOPS MOBILE CLOUD ON-PREMISE

Informatica Value Proposition Comprehensive, Unified & Open

19

Source: An IDC White Paper - sponsored by EMC. As the Economy Contracts, the Digital Universe Expands.

Relational Data

“Transactional”

Social Data

“Interactional”

The Growing Challenge: “BIG DATA” Expanding the Frontiers of Data Integration

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Big Data Confluence of Big Transaction, Big Interaction and Big Data Processing

Big Transaction Data Big Interaction Data

Online Transaction

Processing (OLTP)

Oracle

DB2

Ingres

Informix

Sysbase

SQL Server

…

Cloud

Salesforce.com

Concur

Google App Engine

Amazon

…

Other Interaction Data

Clickstream

image/Text

Scientific

Genomoic/pharma

Medical

Medical/Device

Sensors/meters

RFID tags

CDR/mobile

…

Social Media Data

Facebook

Twitter

Linkedin

Youtube

…

Big Data Processing

Online Analytical

Processing (OLAP) &

DW Appliances

Teradata

Redbrick

EssBase

Sybase IQ

Netezza

Exadata

HANA

Greenplum

DataAllegro

Asterdata

Vertica

Paraccel …

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CUSTOMER

PRODUCT ORDER

Barriers to Becoming Data Driven

PRODUCT CUSTOMER CUSTOMER CUSTOMER

INVOICE ORDER INVOICE ORDER PRODUCT ORDER PRODUCT INVOICE

Customer Service Portal

Sales Automation Application

BI Application

• Data is not

timely

22


CUSTOMER

PRODUCT ORDER





BI Application

• Data is not

timely

• Data is not

trustworthy

23


Business IT

? ?

CUSTOMER

PRODUCT ORDER





BI Application

• Data is not

timely

• Data is not

trustworthy

• Data is not

relevant

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Application Database Partner Data

SWIFT NACHA HIPAA …

Cloud Computing Unstructured

Data Warehouse

Data Migration

Test Data Management & Archiving

Master Data Management

Data Synchronization

B2B Data

Exchange

Data

Consolidation

The Informatica Approach Comprehensive, Unified, Open and Economical platform

http://www.peoplesoft.com/corp/en/public_index.asp

http://www.hyperion.de/

http://www.workday.com/index.php

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What’s New with Informatica

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Informatica Delivers Greater Value to Customers Acquisition of Best-in-Class Products from Adjacent Markets

Recent Acquisitions Since January 2009

Applimation (Jan. 2009) – Leader in Application Information Life Cycle Management.

Helping Customers manage their data assets from cradle-to-grave:

Data Archive for storing inactive and rarely accessed data on lower cost storage

medium.

Data Privacy for masking identifying and identity data to remain in compliance with

today’s stringent personal information and privacy laws.

Data Subset for creating purpose-built data sets for environment (DEV/QA/SYSTEM)

or functional (CRM/ERP/FINANCE/HR) based testing.

Address Doctor (Mid-2009) – Leader in Worldwide Name and Address Validation for Over

200 Countries. Providing Customers with the highest quality name and address content for

name and address standardization and validation.

Agent Logic (Oct. 2009) – Leader in Complex Event Processing and Operational

Intelligence. Helping Customers institutionalize event detection patterns and human

analysis patterns into automated opportunistic action and response alerts.

Siperian (Jan. 2010) – Leader in Master Data Management. Helping Customers achieve

mastery of a single view of ‘X’ across all mission critical data domains.

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Introduction to PowerCenter

Enterprise Data Integration and ETL

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PowerCenter

Cli

en

t S

erv

ice

s F

ram

ew

ork

Designer

Design

Workflow

Manager Workflow

Monitor

Repository

Repository

Service

Integration

Service

Web

Services

Adm

inis

trato

r

XML, Messaging, and Web Services

Packaged Applications

Relational and Flat Files

Mainframe and Midrange

Provider





Portals, Dashboards, and Reports

Consumer

Informatica Platform Single unified architecture

Manage Monitor

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PowerCenter

Cli

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t S

erv

ice

s F

ram

ew

ork

Designer

Design

Workflow

Manager Workflow

Monitor

Repository

Repository

Service

Integration

Service

Web

Services

Adm

inis

ter





Provider






Consumer

Proven Scalability Threaded Parallel Processing

Manage Monitor

Provider Thread Consumer Thread

In-memory pipeline

Partition Point

Transformation Threads

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PowerCenter

Cli

en

t S

erv

ice

s F

ram

ew

ork

Designer

Design

Workflow

Manager Workflow

Monitor

Repository

Repository

Service

Integration

Service

Web

Services

Adm

inis

trato

r





Provider






Consumer

Proven Scalability Pipeline Parallel Processing

Manage Monitor Provider Thread Consumer Thread Transformation Threads

In-memory pipeline

Provider Thread Consumer Thread Transformation Threads

In-memory pipeline

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What will we learn in this chapter?

How to:

1. Launch PowerCenter Designer to start your project

2. Connect to the PowerCenter Repository

3. Import Source and Target Structures

• From Relational Tables and Flat Files

4. Create Target Structures

• Define Tables and Create them in the Database

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PowerCenter Client Tools

Designer – Used to create mappings that logically define what is to be done and how. Mappings define the sources, the targets and the transformations that you want to perform on the data all through a graphical drag and drop environment.

Workflow Manager – Used to create, schedule and run workflows. A workflow is a set of instructions that describes how and when to run tasks related to extracting, transforming, and loading data.

Workflow Monitor – Used to graphically monitor the status of scheduled and running workflows for each PowerCenter server. You can view what tasks succeeded or failed and drill into the execution logs for each task to get run-time details.

Repository Manager – Used to create and administer the metadata repository. You can create users and groups and assign privileges and permissions to them and create folders to contain the metadata.

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PowerCenter

Cli

en

t S

erv

ice

s F

ram

ew

ork

Designer

Design

Workflow

Manager Workflow

Monitor

Repository

Repository

Service

Integration

Service

Web

Services

Adm

inis

trato

r





Provider






Consumer

Informatica Platform Single unified architecture

Manage Monitor

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Sub-Tools within Designer

Source Analyzer - Used to Import or create source definitions.

Warehouse Designer - Used to Import or create target definitions.

Mapplet Designer - Used to create reusable groups of transformations

Transformation Designer - Used to create reusable transformations

Mapping Designer - Used to create mappings to extract, transform and load data.

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Source Analyzer

• Integrated. Key component of PowerCenter Designer, Source

Analyzer offers “universal data access” in a single unified platform

• Consistent. A single consistent method to access and manage

any data source regardless of type or location

• Visual. Simple graphical interface for importing and creating source

definitions for any of the data sources supported by PowerCenter

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Target Designer

• Integrated. Key component of PowerCenter Designer, Target

Analyzer offers “universal data access” in a single unified platform

• Consistent. A single consistent method to access and manage

any data target regardless of type or location

• Visual. Simple graphical interface for importing target definitions for

any of the data types supported by PowerCenter

• Extensible. Can create target definitions, executable DDLs, and

even create new tables in the warehouse

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Tutorial Lesson 1 – 15 min

5 min for Lab and 10 min Break

Creating Users and Groups

Creating a Folder in the PowerCenter Repository

Creating Source Tables:

Pre Requisite - Create the demo source tables.

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Lesson 2

Creating Source Definitions

Creating Target Definitions and Target Tables

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Lab 2: Step-by-step Overview

1. Launch the Designer

2. Log into the repository

3. Import relational source structure

4. Import flat file source structure

5. Create a relational target structure and build it in the relational instance

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Using Designer

Double-Click to Launch Designer

45

Using Designer

1. Right-click the Workshop repository

2. Select Connect to open

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Using Designer

1. Enter Username: Administrator

2. Enter Password: Administrator

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Using Designer

1. Right-click the MappingLab

folder

2. Select Open to open

This is where most of our work will

be done

48

Using Designer

We should now be in the Source Analyzer

1. Make sure you see Source Analyzer at the

top left hand part of the gray work area

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Using Designer

Import a relational source

1. From the menu bar select Sources

Import from Database

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Using Designer

In the Import Tables dialog,

choose the ODBC

connection for the data

source where the source

tables reside

1. Click the ODBC data

source drop-down box

2. Select the data source

called “source” Note – Informatica only uses ODBC to import the

metadata structures into PowerCenter.

51

Using Designer

1. Enter Username: pc_user

2. The Owner name will self populate

3. Enter Password: pc_user

4. Press Connect

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Using Designer

1. Open up the directory tree under Select tables

2. select table CUSTOMERS

3. Press OK

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Using Designer

1. Verify the source

metadata structure for

the CUSTOMERS and

GOOD_CUST_STG

tables

Next, we will import our flat

file source structure

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Using Designer

1. From the menu bar and select Sources

Import from File

55

Using Designer

1. Navigate to the “C:\PowerCenter Workshop” directory

2. Select the TRANSACTIONS.dat file

56

Using Designer

1. Select the “Import field

names from the first

line” check box – this

tells PowerCenter to start

importing from the second

line (Note “Start Import at

Row:” has changed to “2”)

2. Keep the remaining

defaults (the flat file

source Delimited – not

Fixed Width)

3. Press Next The flat file wizard is now displayed

which allows us to parse through our flat

file source.

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Using Designer

1. Keep the defaults (the flat

file is comma delimited)

2. Press Next Look around this page. Notice you can

account for multiple delimiters, consecutive

delimiters and quotes around data.

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Using Designer

1. Press Finish

Earlier we told PowerCenter to

use the first line of the original flat

file for the column names. Note

that the columns are now named

for us. Review the other options

on this page.

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Using Designer

Congratulations!

You just successfully imported one flat file and

two relational source structures.

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Using Designer

Select the Target Designer to bring in our

target structures

1. Select the second icon on the shortcut line

61

Using Designer

Notice when you select the Target designer, the

menu options change. One now says Targets

1. Select Targets and choose the Import from

Database option

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Using Designer

The target structures are in the target instance of the

database

1. Select the target ODBC data source named “target”

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Using Designer

1. Enter Username: target

2. The Owner name will self populate

3. Enter Password: target

4. Press Connect

64

Using Designer

1. Expand the directory tree

2. Select CUSTOMER_NONAME

and GOOD_CUSTOMERS

3. Select OK

CUSTOMER_NONAME will capture all of our

records that do not have an associated customer

name. GOOD_CUSTOMERS will capture all

clean records to be loaded into our Data

Warehouse.

65

Using Designer

Build a date table

Select Targets Create

One of the objectives of our Data Warehouse is to allow

end users to drill into a customer name and determine

the date that the customer has purchased their items.

66

Using Designer

Select the database type

1. Click the drop-down box and choose

Oracle for the database type

67

Using Designer

1. Enter CUSTOMER_DATES as the name

for the target table

2. Press Create

68

Using Designer

A new table should appear in the workspace

behind the pop up menu

1. Select Done to close the Create Target

Table dialog

69

Using Designer

Edit the table - CUSTOMER_DATES

1. Double-click the CUSTOMER_DATES table

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Using Designer

The properties for the CUSTOMER_DATES table is displayed

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Using Designer

1. Select the Columns tab

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Using Designer

Add columns to the table

1. Press the “Add” icon three times to add in

three new columns

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Using Designer

1. Click NEWFIELD

2. Rename the column CUST_ID

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Using Designer

1. Click in the Datatype column

drop-down for CUST_ID

2. Select number

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Using Designer

1. Click in the Key Type drop-down for

CUST_ID to make this field a Primary Key

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Using Designer

1. Change the second Column

Name to TRANSACTION_ID

2. Change the Datatype of the

TRANSACTION_ID to number.

3. Change the third Column Name

to Date_of_Purchase

4. Change the Datatype of the

Date_of_Purchase column to

date

5. Press OK

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Using Designer

We now have a metadata target structure in the

PowerCenter Metadata Repository. We will now

build the table in the Oracle target instance.

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Using Designer

Build the table in the Oracle target instance

1. Select Targets Generate/Execute SQL…

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Using Designer

Connect to the Oracle instance

1. Press Connect

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Using Designer

1. Press the ODBC data source drop-

down menu

2. Select the “target” database

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Using Designer

1. Enter the Username “target”

2. Enter the Password “target”

3. Press Connect

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Using Designer

We are now connected to “target”

Build the CUSTOMER_DATES table

1. Select Selected tables on the radio menu (we only want to build

the CUSTOMER_DATES table)

2. Choose the options above (We know the table doesn’t exist but

let’s drop the table before we build the new one just in case)

3. Press “Generate and execute”

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Using Designer

The table has been successfully built

1. Close the Database Object Generation box

84

Using Designer

With the Target Designer Selected

1. Expand the Sources folder so that GOOD_CUST_STG is visible

2. Drag the GOOD_CUST_STG object from the Sources directory tree

in the navigation pane to the Target Designer Canvas.

The table GOOD_CUST_STG is for staging

good customer records prior to loading them

into the data warehouse. It will be used as

both a target (when we clean the data) and

a source (when we load the clean data into

the warehouse). We can reuse the source

definition to create the target.

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Using Designer

GOOD_CUST_STG is now setup to be used

as both a source and a target in

PowerCenter. However, while the table

exists in PowerCenter, it does not yet exist in

our target Oracle database. Let’s build this

table in our target Oracle database.

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Using Designer

Build the table in the Oracle target instance

1. Select Targets Generate/Execute SQL…

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Using Designer

Connect to the Oracle instance

1. Press Connect

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Using Designer

1. Press the ODBC data source drop-

down menu

2. Select the “target” database

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Using Designer

1. Enter the Username “target”

2. Enter the Password “target”

3. Press Connect

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Using Designer

We are now connected to “target”

Build the GOOD_CUST_STG table

1. Select Selected tables on the radio menu (we only want to build

the GOOD_CUST_STG table)

2. Choose the options above (We know the table doesn’t exist but

let’s drop the table before we build the new one just in case)

3. Press “Generate and execute”

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Using Designer

The table has been successfully built

1. Close the Database Object Generation box

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Using Designer

If we look back at the directory

tree in the Navigation Pane, we

will see that we now have three

Sources

• TRANSACTIONS (flat file)

• CUSTOMERS (relational)

• GOOD_CUST_STG (relational)

and four Targets (all relational)

• CUSTOMER_DATES

• CUSTOMER_NONAME

• GOOD_CUSTOMERS

• GOOD_CUST_STG

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Lab 2: Tutorial Lesson 2

15 min

Creating Source Definitions

Creating Target Definitions and Target Tables

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Lesson 3: Building a Mapping

Creating a Pass-Through Mapping

Creating Sessions and Workflows

Running and Monitoring Workflows

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• What is a mapping?

• What are Transformation Objects?

• How do we build a mapping?

• How do we Join sources together?

• How do we separate out records with

missing data?

96

PowerCenter – Mapping Designer

• A mapping is a logical definition of your Data

Integration process – it represents a set of source

and target definitions that are linked by

transformation objects.

• The mapping designer is a graphical drag and drop

environment that lets you define the sources, define

the targets and the transformations that you want to

perform on the data

• An easy to use GUI environment for creating,

organizing, and maintaining a series of mappings.

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• Update Strategy

• Source Qualifier

• Sort

• Rank

• Sequence Generator

• Aggregator

• Transaction Control

• Router

• Normalizer

• Custom Transformation

• Stored Procedure

• Lookup • Mapplet

• Filter

• JAVA

• Target Definition

• Union

• XML Parser

• XML Generator

• Expression

• Joiner

• Mapplet Input

• Mapplet Output

PowerCenter Transformations Some examples

Transformations used

in this mapping.

For a detailed

description of these

Transformations and

their function see the

tables in Appendix A

98

PowerCenter Functions

Summary view of all available functions

Character manipulation (CONCAT, LTRIM, UPPER, …)

Datatype Conversion (TO_CHAR, TO_DECIMAL, …)

Data matching and parsing (Reg_Match, Soundex, …)

Date manipulation (Date_Compare, Get_Date_Part, …)

Encryption/Encoding (AES_Encrypt, Compress, MD5, …)

Financial Functions (PV, FV, Pmt, Rate, …)

Mathematical operations (LOG, POWER, SQRT, Abs, …)

Trigonometric Functions (SIN, SINH, COS, TAN, …)

Flow Control and Conditional (IIF, DECODE, ERROR, …)

Test and Validation (ISNULL, IS_DATE, IS_NUMBER, …)

Library of Reusable User Created Functions

Variable Updates (SETVARIABLE, SETMINVARIABLE, …)

Available Lookups that may be used

Some Examples. A more complete

reference can be found in the

Appendix B at the end of this Guide

99

In this Scenario…

We show how to build mappings with Designer. Mappings

are a logical process that define the structure of data and

how it is changed as it flows from one or more data

sources to target locations. Mappings are the core of the

Informatica data integration tool set. With Informatica

transformations and mappings are reusable and can be

used in multiple different scenarios.

For our first mapping we need to combine two sets of data

for our data warehouse. We also need to separate good

records from bad ones that are missing the customer

name.

100

Sample Step-by-step Overview Scenario

1. Create a new mapping:

2. Join data from two sources CUSTOMERS and

TRANSACTIONS.dat

3. Check to see if the Customer Name is missing

from any of the records

4. Store these records in the CUSTOMER_NONAME

table

5. Write all good records to the staging table

GOOD_CUSTOMERS_STG for loading into the

warehouse

101

How to build a Mapping

1. Select the Mapping Designer icon

102


1. Validate that the Mapping Designer is active

103


1. Select Mappings Create to start building a new mapping

104


1. Rename the mapping m_remove_missing_customers

2. Press OK

105


Add the source TRANSACTIONS to the mapping

1. Expand the “+” next to “source” and “Flatfile” so TRANSACTIONS

and CUSTOMERS are visible (as above)

2. Drag the TRANSACTIONS source into the work area

106


The TRANSACTIONS source is added to the mapping.

107


Add the source CUSTOMERS table to the mapping

1. Click and drag the CUSTOMERS source into the workspace

108


Both TRANSACTIONS and CUSTOMERS are now

added to the mapping.

109


Add the target tables to the mapping.

1. Expand the Targets folder

2. While holding CTRL select the CUSTOMER_NONAME and

GOOD_CUST_STG tables

3. Still holding CTRL, drag them onto the workspace

110


111


1. Collapse the Navigation Pane for now to give us more

work space (Single click-left icon)

2. Collapse the Output Window at the bottom of our screen

(Single Click-right icon)

112


Add a joiner transformation to join the two source files together

1. Single click on the joiner transform

2. Single click in the workspace, the Joiner transformation should appear

113


1. Highlight all of the fields in the TRANSACTION Source Qualifier

transformation (holding SHIFT, click the first field then click the last)

2. Still holding SHIFT, drag the selection to the Joiner Transformation

114


To join the two sources we

need to add the Customer

fields to the Joiner

1. Highlight the fields in the

CUSTOMERS Source

Qualifier transformation

2. Drag them to the Joiner

Next, we need to edit the

Joiner properties

1. Double-click on the

Joiner

115


1. Click Rename

Remember, all of this metadata will be captured in the PowerCenter

Metadata Repository. Since we have the ability to report on the

PowerCenter Metadata Repository, we want the names of our

transformation objects to be meaningful.

116


1. Rename the joiner “jnr_many_to_one”

2. Click OK

117


1. Click on the Ports tab Notice that once we have a field in each

source named CUST_ID, it named the

second instance of CUST_ID to CUST_ID1.

118


Add a join condition

1. Click on the Condition tab

2. Click on the Add condition icon

119


1. Press OK

A default condition will be displayed. Since we

have two fields with similar names, by default,

the condition will use these to field names.

120


With the data joined we need to separate good records from those

with missing customer names.

1. Click on the Router Transformation

2. Click on the workspace to add a router to the mapping

121


We want to keep all of the fields from the Joiner except

CUST_ID1, which is the same as CUST_ID.

1. Hold CTRL and select all fields except for CUST_ID1

2. Drag the selected fields to the Router

We need to tell the Router what conditions to check for.

1. Double-click the Router to edit it.

122


Rename the Router

1. Click Rename

2. Type Transformation Name “rtr_check_customer_name”

3. Click OK

123


1. Select the Groups tab.

124


We need to create two groups. One for

records with a customer name and one

records where the name is missing.

1. Click the Add button twice.

The Router groups data based on user defined

conditions. All records that meet the Group Filter

Condition are included in the output for that group.

125


Rename the Groups

1. Click on the first Group Name

2. Rename the group GOOD_CUSTOMER

3. Click on the second Group Name

4. Rename the group CUSTOMER_NONAME

Next we need to edit the Group Filter Condition

1. Click the arrow on the first condition to open editor

126


Bad records have a NULL value for the customer

name. If the record is not NULL then it is good.

1. Enter the expression:

NOT ISNULL(CUST_NAME)

2. Click Validate to test your expression

3. Click OK, to close the message window.

4. Click OK, to close the Expression Editor

127


1. Open the Expression Editor for

CUSTOMER_NONAME

128


1. Enter the expression:

ISNULL(CUST_NAME)

2. Click OK

129


1. Press OK

130


The Router appears. Expand the transformation and scroll down

to see the two we created.

131


We need to connect the output

groups to the appropriate table.

1. Expand the Router transform

and scroll until the

GOOD_CUSTOMER group

is visible

2. Select all of the fields (or

ports) under

GOOD_CUSTOMER

3. Drag the selected fields to

the CUST_ID field on the

GOOD_CUST_STG target

Note: When you drag and release, Designer connects the

first field in the set being dragged to the field under the

cursor when the mouse is released, the second with the

second and so on. If your fields are not in matching order

you may need to connect them one at a time.

132


1. Connect the

CUSTOMER_NONAME

group to the

CUSTOMER_NONAME

target table

Both tables should now be

connected

133


We’re almost done. A few final details before we finish.

1. Click the disk icon to Save the mapping

2. Click the Toggle Output Window icon to view save

status and other messages

3. Verify the mapping is VALID, if it is not check for

Error messages

4. Finally clean up the workspace. Right-click and

select Arrange All Iconic

134


Congratulations!

You just built your first mapping.

135

Lab 3: 20 min (take 5 min break) Creating a Pass-Through Mapping

Creating a Pass-Through Mapping

136

Lesson 3: Workflow

Using Workflow Manager and Monitor

137

What will we learn in this section?

1. What is Workflow Manager?

2. How do we build a session task?

3. How do we sequence sessions?

4. How do we execute our mapping?

5. How do we monitor execution with Workflow

Monitor?

138

PowerCenter

Cli

en

t S

erv

ice

s F

ram

ew

ork

Designer

Design

Workflow

Manager Workflow

Monitor

Repository

Repository

Service

Integration

Service

Web

Services

Adm

inis

trato

r





Provider






Consumer

Informatica Platform Workflow Manager and Workflow Monitor

Manage Monitor

139

Workflow Tasks

Workflow Tasks Description

Assignment Assigns a value to a workflow variable

Command Specifies a shell command to run during the workflow.

Control Stops or aborts the workflow.

Decision Specifies a condition to evaluate.

Email Sends email during the workflow.

Event-Raise Notifies the Event-Wait task that an event has occurred.

Event-Wait Waits for an event to occur before executing the next task.

Session Runs a mapping you create in the Designer.

Timer Waits for a timed event to trigger.

140

In this Scenario…

We will use the Workflow Manager and Workflow Monitor to

build a workflow to execute the mappings we just built. We

will configure our workflow and then monitor the workflow in

the Workflow Monitor. Along the way, we will investigate

the various options in both tool sets.

141

Step-by-step Overview

1. Open the Workflow Manager through Designer

2. Create a session task.

3. Configure the session task to run the mappings we

just built.

4. Investigate the options in the Workflow Manager.

5. Monitor the execution of the session in the

Workflow Monitor.

6. View the run properties and session log in the

Workflow Manager.

142

Working with Data

Launch the Workflow Manager

1. Press the Orange W on the tool bar above

to launch the Workflow Manager

143

Workflow Manager Tools

Create reusable

tasks

Create worklets Create

workflows

144

1. Select the Workflow Designer

Using the Workflow Manager

145

1. Select the Session task and drop it in by

clicking on the Workflow Designer

workspace


146

We need to join and remove records with no customer name before

we can load them into the Data Warehouse.

1. Select the mapping m_remove_missing_customers

2. Click OK


147

Keep all the defaults

1. Press OK


148

We need to configure the Session to

connect to the source and target structures

1. Double-click the Session task to open

and edit it


149


1. Select the Mapping tab 2. Select SQ_TRANSACTIONS (under the

Sources folder on the left)

150

1. Scroll down under Properties until you see Source file directory

2. Enter the location “C:\PowerCenter Workshop” as the Source file

directory

3. Enter “TRANSACTIONS.dat” as the Source filename


151

1. Select SQ_CUSTOMERS under Sources on the left

2. Click the drop-down to select the correct Oracle

instance that houses this source table


152

The Relational Connection Browser opens

1. Select the Source connection under Objects (this is the

Oracle instance where the CUSTOMERS table resides)

2. Press OK


153

Configure the target structures

1. Select CUSTOMER_NONAME from the Targets folder on the left

2. Click the drop-down box under Value to open the Relational Connction

Browser


154

1. Select Target

2. Press OK


155


1. Right click in the Value box

2. Select Apply Connection Value To all Instances

to assign this connection value to all target tables

Since all of our target

tables exist in the same

place, let’s take a

shortcut.

156


1. Review the information for GOOD_CUST_STG

2. Notice Target is already filled in

3. Press OK to close the Session Editor

157


1. Under Properties, scroll down and select the

Truncate target table option

2. Select OK to close the Session Editor

The GOOD_CUST_STG staging table may

have data in it from previous runs. We

want to make sure the only data in the table

is for the current run.

158


1. Add another Session task to the workspace

Loading the Data Warehouse is a two part process.

The first mapping/session joins the source data,

removes bad records and loads good data into a

staging table. The data still needs to be refined and

loaded into the Data Warehouse. The second

mapping we built does this.

159

1. Select the mapping m_build_customer_DW

2. Click OK


160

The new Session is added. We need to sequence the sessions

so they execute in the proper order.

1. Select Link Tasks

2. Click on the left session and drag to the session on the right,

so the sessions are connected.

3. Double-click the new Session (on right) task to edit it


161

1. Select the Mapping tab


162

1. Select SQ_GOOD_CUST_STG under Sources on the left

2. Click the arrow under Value to select the correct Oracle

instance for this source table


163

In the Relational Connection Browser

1. Select the Target connection under Objects – why ??

2. Press OK


164

Configure the target structures

1. Select CUSTOMER_DATES from the Targets folder on the left

2. Click the arrow under Value to open the Relational Connction Browser


165

1. Select Target

2. Press OK


166


1. Right click in the Value box

2. Select Apply Connection Value To all Instances

to assign this connection value to all target tables

Since all of our target

tables exist in the same

place, let’s take a

shortcut.

167


1. Verify GOOD_CUSTOMERS now uses the Target

Connection

168


Under the Transformations folder in the left navigation pane

1. Verify the lkp_product_description Connection Value

uses Source, if not click the arrow and update

2. Click OK

The Lookup

Transformation also

requires a Connection

169


Take a moment to review the

configuration options under

the other session tabs.

1. Review Properties

Properties allow you to specify

log options, recovery strategy,

commit intervals for this

session in the workflow and so

forth. Note in this case the

workflow will continue even if

the mapping fails.

170


1. Review Config Object

The Config Object allows

you to specify a variety of

Advanced, Logging, Error

Handling and Grid related

options. Scroll down to

view the range of options

available.

171


1. Review Components

2. Select OK to close the

Session Editor

In the Components tab,

you can configure pre-

session shell commands,

post-session commands,

email messages if the

session succeeds or fails,

and variable assignments.

172


Save the workflow

1. Click Save under the Repository menu

173


1. Verify the workflow is VALID, if not

scroll up to check for errors

2. Select Workflows Start Workflow

174

Using the Workflow Monitor

Workflow Monitor provides

a variety of views for

monitoring workflows and

sessions. This view shows

the status of running jobs.

1. Notice that the Workflow Monitor is

displayed when you start a workflow

2. Let the task run to completion

175


1. Select the Task View tab

This view allows users to view the tasks

associated with a specific workflow. Note

that in this case our workflow has two

sessions and has been successfully run

several times. Your view may vary

depending on when and how many times

you have run your mapping

176


1. Select the Gantt Chart view

2. Right click on the first session in the

workflow we just ran

3. Select Get Run Properties

177


1. Review the Task Details

2. Note the session Status

3. Note the number of

Source and Target rows

Do the results make sense?

Two tables were joined so we

would expect a lower total

written than read, Correct?

1. Click and expand

Source/Target Statistics

178


1. Review Source/Target Statistics

2. 8 rows were written to CUSTOMER_NONAME Table

but 11 were rejected rows

3. Scroll over and check the Last Error Message for

that target

Looks like Writer execution failed for some reason with

error 8425. Let’s take a look at the session log and find out

what the 8425 error is. 1. Select the Get Session Log tab

(Hyperlink on top right)

179


1. Select Find. . .

2. Enter the Error Number 8425

3. Select the radio button for All fields

4. Select Find Next

180


1. Close out the session

It seems we have a unique constraint violation. Mostly likely there

are duplicate primary keys in the data. Let’s debug.

181


1. Open up our Session Task again

In order to debug, let’s override writing our

data to the CUSTOMER_NONAME table.

182


1. Select CUSTOMER_NONAME from the Mapping tab

2. Override the Relational Writer

3. Select the drop-down box

183


1. Select File Writer

Notice we can override our target because

PowerCenter separates logical design

from physical bindings. Specifically

mappings do not include connection

information, while workflows do, actual

binding occurs at runtime.

184


1. Under properties Scroll down

to Header Options

2. Click drop-down and select

Output Field Names

3. Select Set File Properties

185


1. Switch the radio button to Delimited

2. Press OK

3. Press OK to exit the Session Editor

186


1. Save the changes we made

2. Verify the workflow is VALID

3. Run the workflow again

187


1. Review the output file

We were now able to load all 19 rows.

No rows were rejected.

188


1. In Windows Explorer navigate to

C:\Informatica\9.0.1\server\infa_shared\TgtFiles

2. Double-click on the customer_noname1.out file

189


As we suspected, we have duplicate Customer IDs

and will have to deal with that in our mapping, but

we’ll save that for another day!

190


1. Go to Designer and open the Target Designer

2. Right click on the GOOD_CUSTOMERS target

3. Select Preview Data. . .

Before we finish, we want to verify that our

data loaded into the Data Warehouse.

191


1. Verify the ODBC data source is target

2. Enter Username: target

3. Enter Password: target

4. Press Connect

192


Congratulations!!

The Data was

Successfully Loaded!

You just completed

building and loading the

Data Warehouse!

193

Lab 3: 30 min 10 min break

Creating Sessions and Workflows

Running and Monitoring Workflows

194

Lesson 4

195

What will we learn in this section?

• How to use a look-up to enrich records with

data from another source?

• What is a reusable transformation?

• How to use expressions to format data?

• How to use aggregate functions to

generate results from a data set?

196

In this Scenario…

We will use Designer to build another mapping.

Where the last lab focused on joining raw data

and removing bad records, this lab focuses on

using transformations to convert, enrich, and

reformat the data and, finally, load it into the data

warehouse.

Specifically, we will be working with the good

records that the first mapping loaded into the

staging table.

197

• Update Strategy

• Source Qualifier

• Sort

• Rank

• Sequence Generator

• Aggregator

• Transaction Control

• Router

• Normalizer

• Custom Transformation

• Stored Procedure

• Lookup • Mapplet

• Filter

• JAVA

• Target Definition

• Union

• XML Parser

• XML Generator

• Expression

• Joiner

• Mapplet Input

• Mapplet Output

PowerCenter Transformations Some examples

Transformations we

will use in this lab

198


1. Create a new mapping called

m_build_customer_DW

2. Get a product description from the PRODUCT table

3. Format customer names and product descriptions

so the first letter is Upper Case

4. For the good data, perform a simple calculation to

determine total revenue

5. Collapse any duplicates

6. Load transaction dates into a table so a reporting

tool can get the date of a specific transaction

199


Starting from the Mapping Designer

1. Select Mappings Create to build a new mapping

200


1. Rename the mapping m_build_customer_DW

2. Press OK

201

Working with Data

Add the source GOOD_CUST_STG to

the mapping

1. Drag the GOOD_CUST_STG

source into the work area

Note: This is the source view of

the same staging table we wrote

the good customer data to in the

last lab.

202

Working with Data

The GOOD_CUST_STG source is added to the mapping

203


Add the target tables to the mapping

1. Expand the Targets folder

2. Select and drag CUSTOMER_NONAME and

GOOD_CUST_STG tables onto the workspace

204


All sources and

targets are now

imported

1. Collapse the

Navigation Pane

for now to give us

more space to

work space

2. Collapse the

Output Window

at the bottom of

our screen

205

Working with Data

Add a Lookup Transformation

1. Click the Lookup Transformation icon

once and single click in the workspace

The Lookup Transformation will

allow us to pull back the product

description names from our

PRODUCT table. This is required

by the end user so they can see

exactly what products were

purchased by our customers.

206

Working with Data

Select the Lookup Table

1. Click on the Import tab

2. Select From Relational Table

207

Working with Data

1. Click on ODBC data source the drop-

down box

2. Select the “source” ODBC connection

We have to connect to the database

instance that holds our lookup table.

Note that PowerCenter will NEVER

override database level security.

208

Working with Data

1. Enter the Username “source”

2. Enter the Password “source”

3. Press Connect

209

Working with Data

1. Expand up TABLES folder

2. Select the PRODUCT table

3. Press OK

210

Working with Data

The Lookup Transformation

appears in the workspace.

We will use the Product_ID

from the source to lookup the

data we need

1. Highlight the

PRODUCT_ID field from

the Source Qualifier

and drag it onto the

white space at the

bottom of the Lookup

211

Working with Data

Open and configure the Lookup Transformation

1. Double-click on the Lookup

212

Working with Data

1. Press Rename

2. Rename the transformation “lkp_product_description”

3. Press OK

213

Working with Data

1. Select the Condition tab

2. Click the Add condition button

Much like the joiner, the lookup transformation requires a condition to be

true for it to pass values. In this case, we want the product ID from the

TRANSACTIONS file to match the product ID in the PRODUCTS table.

Once there is a match, the lookup will return the proper product

description value.

214

Working with Data

We want to return the Product Description that matches

the Product_ID we passed in. Designer automatically

identified the correct ports to compare for the lookup.

No change is required

1. Click on the Ports tab

215

Working with Data

Select the Return value

1. Check the box in the “R” column for PRODUCT_DESC

2. Press OK

216

Working with Data

Add an Expression for

formatting data

1. Select the Expression

Transformation

2. Click on the

workspace

We would like to do some formatting on

our source data. We want the initial

character of our customer names and

product descriptions to be Upper Case

217

Working with Data

1. Click and drag all the required fields from the Source Qualifier to

the Expression Transformation (skip the PRODUCT_ID field

since we only need it for the lookup)

218

Working with Data

We need to add the Lookup

output in with the other ports

1. Drag the PRODUCT_DESC

port from Lookup to a blank

line in the Expression

219

Working with Data

Minimize completed transformations

1. Click on the minimize icon for each completed transformation

2. Next, double-click on the Expression Transformation to edit it

220

Working with Data

1. Press Rename

2. Enter “exp_format_data”

3. Press OK

221

Working with Data

1. Select the Ports tab

2. Add field button twice to add two “output ports”

3. Select the first field and rename it CUST_NAME_OUT

4. Select the second field and rename it

PRODUCT_DESC_OUT

222

Working with Data

1. Change the precision to 50 for each new port

2. De-select the “O” (output) ports for CUST_NAME and PRODUCT_DESC

(they will be replaced by the new fields)

3. De-select the “I” for the new fields (they originate here and have no input)

• When the “O” is selected the expression editor box on the right will

become active

223

Working with Data

1. Select the Expression box area next to the first field

CUST_NAME_OUT (an arrow will appear)

2. Click the arrow to open the Expression Editor

224

Working with Data

Notice the help!!!

Press F1 for more

1. Edit the Expression

2. Expand the Character folder

3. Select the Initcap function

4. Double-click the function to add it

to the Formula

225

Working with Data

1. Edit the Formula so that it matches the one above.

Remember CUST_NAME is the input being

modified, CUST_NAME_OUT is the result

2. Press OK to close the editor

This is a simple expression telling

PowerCenter capitalize the first letter of

the customer first and last name.

226

Working with Data

Repeat for PRODUCT_DESC_OUT

1. Press the down arrow to open the Expression Editor

227

Working with Data

1. Select the Initcap function

2. Edit the Formula so it matches

the one above

3. Press OK

228

Working with Data

1. Click the row number at left and use the black arrows

to move the row up or down in the list

This is how the fields should look now. For

housekeeping purposes, move the fields directly

below the fields with which they correspond.

229

Working with Data

1. Validate that the Ports are in the proper order

2. Press OK

230

Working with Data

1. Validate the mapping – it should look like this

2. Open the Navigation Pane

Next we need to format our date. In our flat

file, the date is an 8 character string. We

need to convert that string to a date format so

that it matches the format the target database

(Oracle) is expecting

231

Working with Data

1. Select the Transformation Developer

2. Expand the Transformations folder in the

left Navigation pane

3. Drag the exp_formatted_date

transformation onto the workspace

4. Double-click the transformation to edit it

exp_formatted_date is a

sharable, re-usable

transformation

232

Working with Data


2. Open the Expression Editor for the

formatted_date port

233

Working with Data

1. Review the expression formula

2. Press OK

3. Press OK on the next screen to close

the Edit Transformations window

234

Working with Data

1. Right click on the transformation

2. Select Dependencies

Because this is a reusable transformation, any changes we make

will propagate to every mapping that uses the transformation. We

may want to know what mappings include this transformation before

we change it. To do this we run a dependency report.

235

Working with Data

1. Select any Object Types that should be

included in the report

2. Press OK

236

Working with Data

1. Review the report content. In this

case there are no dependencies.

2. Close the report

237

Working with Data

1. Click and drag the exp_formatted_date

expression to the workspace

238

Working with Data

1. Link the DATEOFTRANSACTION port to the

DATE_IN port on the new Expression

Transformation

2. Add an Aggregator to our mapping

239

Working with Data

We need to calculate the total revenue for each

customer. The Aggregator transformation performs these

types of functions on groups of data. It can also help

collapse records based on a grouping criteria (CUST_ID

in this case), eliminating duplicate sets of results

240

Working with Data 1. Map the output ports from the

two expressions to the

Aggregator transformation

2. Minimize the Expressions

now we are done with them

3. Double-click the Aggregator

to edit the transformation

properties

241

Working with Data

Rename the Aggregator Transformation

1. Click Rename

2. Name the transformation agg_revenue

242

Working with Data

Update port names and build the aggregate

calculation


2. Remove the “_OUT” from the CUST_NAME

and PRODUCT_DESC ports

3. Click Add new port button once

A new port is added to the Aggregator

243

Working with Data

1. Rename NEWFIELD to TOTAL_REVENUE

2. Change the Datatype to Double

3. De-select the “I” so the Expression Editor

becomes available

4. Click the arrow to open the Expression Editor

244

Working with Data

1. Build the expression shown above

2. Press OK

245

Working with Data

Our calculation computes the total revenue by customer. To

accomplish this, data needs to be grouped by Customer ID

1. Check the GroupBy box for the CUST_ID port

2. Press OK

246

Working with Data We are ready to map the fields

from the aggregator to the

GOOD_CUSTOMERS table

1. Select the relevant ports from the Aggregator

2. Map the selected fields to the matching ports on the

GOOD_CUSTOMERS target table

247

Working with Data We want to map three of the fields in the

Aggregator to our second target,

CUSTOMER_DATES. The CUST_ID field

will go to both targets.

1. Select the relevant ports from the Aggregator to map to

CUSTOMER_DATES

2. Connect the selected fields to the matching ports on the target table

248

Working with Data

Almost done. Let’s apply the finishing touches.

1. Save the mapping

2. Verify the mapping is VALID

3. Clean up. Right click anywhere in the

workspace, select Arrange All Iconic

249

Working with Data

Congratulations!

You are now ready to load your

data into the Data Warehouse.

250

Lab 4: 1 hr

251

Using the Debugger

252


• What is the Debugger?

• How do we use the Debugger?

• What are the advantages of using the Debugger?

• What are some of the options in the Debugger?

253

In this Scenario…

As a developer you want to test the mapping you

built prior to running the data to ensure that the

logic in the mapping will work.

For this lab we will use a pre-built mapping to

review the features of the Debugger

254


1. Open the Debugger lab folder

2. Run the Debugger

3. Configure the Session with the Debugger Wizard

4. Edit Breakpoints

5. Step through the mapping

6. Monitor results

255

Using the Debugger

Open the DebuggerLab

1. Right-click on DebuggerLab folder and select Open

256

Using the Debugger

1. Open the Mapping Designer

2. Expand the Mappings Folder

3. Drag M_DebuggerLab to the Mapping Designer workspace

257

Using the Debugger

Start Debugger

Stop the Debugger

Next Instance

Step to Instance

Show Current Instance

Continue

Break Now

Edit Breakpoints

Debugger Toolbar

258

1. Start the Debugger

Using the Debugger

259

1. Review the pre-requisites

2. Press Next

Using the Debugger

260

1. Select the Int_Workshop_Service as

the Integration Service on which to

run the debug session

2. Leave the defaults

3. Click Next

Using the Debugger

261

1. Choose the Source and Target

database connection

2. Leave the default values of Source

and Target

3. Click Next

Using the Debugger

262

Configure Session parameters.

No change.

1. Click Next

Using the Debugger

263

Configure Session parameters.

No change.

1. Click Next

Using the Debugger

264

Using the Debugger

Do we want to physically load the table or roll back

the data before commit in the debug session?

In this case we just want to test the mapping, not

actually load the data.

Configure Session parameters

1. Check Discard target data

2. Click Finish to start the session

265

Using the Debugger

Let’s adjust the tool bars so it is easier to work

with the Debugger.

1. Right click on the tool bar and unselect the

Advanced Transformations tool bar

2. Repeat and select Debugger so the toolbar is

visible

266

Using the Debugger

1. Select “Edit Breakpoints” to establish

breakpoints to stop the debug session at

specific transformations

267

We want to establish a breakpoint at the Expression Transformation

1. Select the EXPTRANS object

Using the Debugger

268

1. Select the Add button to create a breakpoint at the expression

transformation

2. Under Condition, click the Add box to set the breakpoint rules

3. Edit the rule so that it will stop when CUST_ID = 325

4. Click OK

Using the Debugger

269

1. Notice the “Stop Sign” Breakpoint set at

EXPTRANS Transformation

Using the Debugger

270

Target Instance

Window

Transformation

Instance

Data Window

Output Window –

Debugger or

Session Log

Debugger

Menu Using the Debugger

Breakpoint

271

Next Instance

Examine values See Output

From the Debugger Toolbar

1. Click Next Instance to step into the mapping

2. Review values and outputs in the debug panes

3. Continue to step through and monitor changes

Using the Debugger

272

1. Click Next

Instance until 9

records have been

processed.

2. Monitor Output

below

3. Click Stop the

Debugger

Using the Debugger

273

When the Debugger closes, Designer

returns to the normal design view

1. Note the “shutdown complete” message

in the output window

Using the Debugger

274

Additional Informatica

Resources

275

Informatica Community my.informatica.com

276

My.informatica.com Assets

• Searchable knowledge base

• Online support and service request management

• Product documentation and demos

• Comprehensive partner sales, support and training tools

• Velocity – Informatica’s implementation methodology

• Educational services offerings

• Mapping Templates

• Link to devnet

• Many more …

277

Developer Network devnet.informatica.com

278

Informatica Partner Enablement Presales and Implementation Roles

279

Welcome to

• What is beINFORMed?

• Informatica‘s Partner Home

• A variety of online tools and resources to help you sell and deliver

Informatica solutions

• Answers your Informatica questions

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http://partners.informatica.com/

280

How to Register ... http://partners.informatica.com

Log in and “Register

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When you login,

you can change

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http://partners.informatica.com/

281

What does beINFORMed Offer?

• Enablement

Become an expert on selling Informatica, positioning Informatica solutions and implementing Informatica technology. Follow well-defined “learning paths” for your role (sales, presales, implementation) to become enabled.

• Software

Ensuring that you are successful with the deployment of the Informatica platform, we offer you internal training and demonstration software.

• Resource Center

A one-stop shop for technical, marketing, and sales information around Informatica's products, solutions and programs.

• Manage Sales Leads and Register for Referral Fees

You can always use a little extra help when it comes time to meet with your customer...we're here to support you.

• Marketing Center Review and participate in joint programs to drive pipeline

282

beINFORMed What It Looks Like

Increase your

Informatica skills

Request

software

Log your

opportunities

Find resources

Do joint

marketing

283

beINFORMed Submit and Manage Software Requests

Submit Requests

Track approval

through

fulfillment

284

beINFORMed Enablement Paths – Your Steps to Success

Increase your

selling skills

Understand

solutions

Hone your

technical,

hands-on Skills

Fast,

comprehensive

solution

information

285

beINFORMed Current Pre-Sales Enablement Paths

Solution Basics Demos and

Positioning Support & Awareness

INFORMATICA

• Chalktalk eLearnings

• Download software

• Solution Positioning

Presentations

• Topical INFOCenters

• Chalktalk eLearnings

• Demos / recordings

• Solution Starter kits

• POC requirements docs

• 24x7 Support

• Solution Webinar series

DELIVERY

beINFORMed

beINFORMed

SC workshops

VMWare Image

Phone / email support

SC pairing/mentoring

286

Silver Accreditation Gold Accreditation Platinum Accreditation

Presales Accreditation on Platform, DI, DQ, MDM and other Informatica Solution Areas

Presentation and Positioning

Expert

Demo and Presentation Expert POC, Demo and Presentation

Expert

DELIVERY

beINFORMed

Alliances Webinar Series

Solution InfoCenters

eLearnings

beINFORMed


Online SC Webinars

eLearnings

Demo Recordings/Scripts

Modular Web-based

consumption

beINFORMed


SC Bootcamps

VMWare-based POC scenarios

POC reviews and validation

POC Shadowing

Success Measures

2010 Manual review process

2011 Automated review

process per solution area


2011 Automated review

process per solution area


2011 Automated review process

per solution area

beINFORMed Presales Accreditation – 2010-2011 Next Steps

287

beINFORMed (From Enablement Page)

Solutions at your finger tips

288

beINFORMed Comprehensive Resource Center

Find hot

information,

collateral, demos

Search by

category or

solution area

289

beINFORMed Implementer Enablement Paths – Data Quality

Follow the

Initial Steps

Identify proper

Education

Stay in touch,

resolve issues

290

Step 1 – QuickStart

6 eLearnings Quickstart, MetaData Manager, New Features, Unified

Security, Data Analyzer, Real-Time eLearning

Software Download Software for Training or evaluation purposes

Guides Installation Guide, Getting Started

Documentation Install Guide, Getting Started Guide, User Guide

Demos Real-Time Edition, MetaData Manager, Data Masking

291

Step 2 – Education Global Education Services

PowerCenter 8.x - Level 1 Developer • 4 day course (Virtual or classroom based) - More Details >>

PowerCenter 8.x - Level 2 Developer • 4 day course (Virtual or classroom based) - More Details >>

PowerCenter 8.X+ Administration • 4 day course (Virtual or classroom based) – More Details >>

Metadata Manager 8.6

• 3 day course (Virtual or classroom based) – More Details >>

http://inter.viewcentral.com/reg/informatica/PC8xL1D

http://inter.viewcentral.com/reg/informatica/PC8L2D

http://inter.viewcentral.com/reg/informatica/86A

http://inter.viewcentral.com/events/cust/search_results.aspx?keyword=&event_id=279&postingForm=default.aspx&cid=informatica&pid=1&lid=1&cart_currency_code=&payment_type=&orderby_location=&orderby_date=&newRegistration=&bundle_location_group=&errmsg=

292

Step 3 – Services

During Projects you can use the following services

Global Customer Support – 24 x 7 support Raise service request via Email / web

Search our knowledge base via http://my.informatica.com

Phone (North America: +1 866 563 6332)

Professional Services For initial engagements – DI experts can be contracted

To compliment your team

Velocity Methodology Available for Partners, Informatica Best

Practices – Search with “Velocity” on beINFORMed

PowerCenter Baseline Architecture

PowerExchange CDC Deployment for Mainframe Systems

Data Migration Jumpstart

http://my.informatica.com/

http://www.informatica.com/INFA_Resources/ips_powercenter_baseline_arch_deploy.pdf

http://www.informatica.com/INFA_Resources/ips_powerexchange_baseline_arch_changed_data.pdf

http://www.informatica.com/INFA_Resources/ips_data_migration_jump_start.pdf

293

Step 4 – Certification Global Education Services

Informatica Certified Developer PowerCenter QuickStart eLearning

PowerCenter 8.X+ Administrator course

PowerCenter Developer 8.x Level I course

PowerCenter Developer 8 Level II course

Three Exams

Informatica Certified Consultant PowerCenter QuickStart eLearning

PowerCenter 8.X+ Administrator course

PowerCenter Developer 8.x Level I course

PowerCenter Developer 8 Level II

Five Exams

294

beINFORMed Lead Management – Opportunity to Close

Log your

opportunities

Register Leads

Obtain Sales

Support

Collaborate

with Alliances

Report on joint

pipeline-

Receive

Referral Fees

295

beINFORMed Joint Marketing– Leverage Existing Programs and Content

Find Marketing

Info &

Opportunities

Do joint PR

Download

Programs

In a Box

296

Putting it all together

297

Suggested Naming Conventions

• Targets – T_TargetName.

• Mappings – m_MappingName.

• Sessions – s_MappingName.

• Workflows – wf_WorkflowName

• Transformations (in a mapping) – two or three

letter transformation abbreviation followed by name

Expression = exp_ExpressionName

Some Examples. A more complete set of

transformation naming conventions can be found

in the Appendix C at the end of this Guide

298

In this Scenario…

• You are the regional manager for a series of car

dealerships. Management has asked you to

track the progress of your employees.

Specifically, you need to capture:

• Employee name

• Name of the dealership they work at

• What they have sold

• How much they have sold (net revenue)

299


1. Create a new target definition to use in the mapping, and create

a target table based on the new target definition.

2. Create a mapping using the new target definition. You will add

the following transformations to the mapping:

• Lookup transformation. Finds the name of the employees, dealerships

they work at, and all products they have sold.

• Aggregator transformation. Calculates the net revenue that the

employee has sold.

• Expression transformation. Format all employees names and product

descriptions.

3. Create a workflow to run the mapping in the Workflow Manager

4. Monitor the workflow in the Workflow Monitor

300

Step 1: Sources and Targets

1. Open up the MappingLab folder

2. Use the mm_data user (user_id/password:

mm_data/mm_data) to bring in the mm_transactions table

3. Create your own Oracle target in the Target Designer in the

target instance in Oracle

• Target should be named T_Employee_Summary

• Columns should include:

• EMP_NAME (varchar2, length 50, primary key)

• PRODUCT_SOLD (varchar2, length 50)

• DEALERSHIP (varchar2, length 50)

• NET REVENUE (number)

301

Step 2: Mapping

1. Open up Mapping Designer

2. Create a new mapping – call it whatever you like

3. Bring in mm_transaction source and T_Employee_Summary target

4. Find dealership name (hint: Use the mm_data user as all dealerships names are kept in the mm_dealership table)

5. Find product description (hint: Use mm_data user as all product descriptions are kept in the mm_product table)

6. Find employee name (hint: Use mm_data user as all employees names are kept in the mm_employees table)

7. Format the employee name and make sure the name is capitalized

8. Format the product description and make sure the initial letters are capitalized

9. Calculate net revenue (hint: keep it simple, net revenue is revenue – cost)

10.Group by Employee_ID to collapse all unique employees

11.Map to target table

302

Step 3: Build the workflow

1. Open Workflow Manager

2. Create a new workflow

3. Use a session task to execute mapping

4. Configure session task

5. Execute mapping

303

Step 4: Monitor workflow

1. Open Workflow Monitor

2. Monitor workflow

3. Debug using session log as necessary

4. Preview data to be sure it worked properly

• Hint: To preview data, go to Designer open up

Target Designer right click on

T_Employee_Summary select Preview Data

enter username and password (target/target)

304

Thank You!

305

Appendix A – PowerCenter Transformations

306

Transformation Objects Transformation Description

Aggregator Performs aggregate calculations.

Application Source Qualifier

Represents the rows that the PowerCenter Server reads from an application,

such as an ERP source, when it runs a session.

Custom Calls a procedure in a shared library or DLL.

Data Masking

Replaces sensitive production data with realistic test data for non-production

environments.

Expression Calculates a value.

External Procedure Calls a procedure in a shared library or in the COM layer of Windows.

Filter Filters data.

HTTP Connects to an HTTP server to read or update data.

Input Defines mapplet input rows. Available in the Mapplet Designer.

Java

Executes user logic coded in Java. The byte code for the user logic is stored in

the repository.

Joiner Joins data from different databases or flat file systems.

Lookup Looks up values.

Normalizer

Source qualifier for COBOL sources. Can also use in the pipeline to normalize

data from relational or flat file sources.

Output Defines mapplet output rows. Available in the Mapplet Designer.

Rank Limits records to a top or bottom range.

307

Transformation Objects

Transformation Description

Router Routes data into multiple transformations based on group conditions.

Sequence Generator Generates primary keys.

Sorter Sorts data based on a sort key.

Source Qualifier Represents the rows that the PowerCenter Server reads from a relational or flat file

source when it runs a session.

SQL Executes SQL queries against a database.

Stored Procedure Calls a stored procedure.

Transaction Control Defines commit and rollback transactions.

Union Merges data from different databases or flat file systems.

Unstructured Data Transforms data in unstructured and semi-structured formats.

Update Strategy Determines whether to insert, delete, update, or reject rows.

XML Generator Reads data from one or more input ports and outputs XML through a single output

port.

XML Parser Reads XML from one input port and outputs data to one or more output ports.

XML Source Qualifier Represents the rows that the Integration Service reads from an XML

source when it runs a session.

308

Appendix B – PowerCenter Functions

309

Aggregate Functions

Function Description

AVG Returns the average of all values in a group.

COUNT Returns the number of records with non-null value, in a group.

FIRST Returns the first record in a group.

LAST Returns the last record in a group.

MAX Returns the maximum value, or latest date, found in a group.

MEDIAN Returns the median of all values in a selected port.

MIN Returns the minimum value, or earliest date, found in a group.

PERCENTILE Calculates the value that falls at a given percentile in a group of numbers.

STDDEV Returns the standard deviation for a group.

SUM Returns the sum of all records in a group.

VARIANCE Returns the variance of all records in a group.

310

Character Functions


ASCII

In ASCII mode, returns the numeric ASCII value of the first character of the string

passed to the function.

In Unicode mode, returns the numeric Unicode value of the first character of the

string passed to the function.

CHR Returns the ASCII or Unicode character corresponding to the specified numeric

value.

CHRCODE

In ASCII mode, returns the numeric ASCII value of the first character of the string

passed to the function.

In Unicode mode, returns the numeric Unicode value of the first character of the

string passed to the function.

CONCAT Concatenates two strings.

INITCAP Capitalizes the first letter in each word of a string and converts all other letters to

lowercase.

INSTR Returns the position of a character set in a string, counting from left to right.

311


LENGTH Returns the number of characters in a string, including trailing blanks.

LOWER Converts uppercase string characters to lowercase.

LPAD Adds a set of blanks or characters to the beginning of a string, to set a string to a

specified length.

LTRIM Removes blanks or characters from the beginning of a string.

METAPHONE Encodes characters of the English language alphabet (A-Z). It encodes both uppercase

and lowercase letters in uppercase.

REPLACECHR Replaces characters in a string with a single character or no character.

REPLACESTR Replaces characters in a string with a single character, multiple characters, or no

character.

RPAD Converts a string to a specified length by adding blanks or characters to the end of the

string.

RTRIM Removes blanks or characters from the end of a string.

SOUNDEX

Works for characters in the English alphabet (A-Z). It uses the first character of the input

string as the first character in the return value and encodes the remaining three unique

consonants as numbers.

SUBSTR Returns a portion of a string.

UPPER Converts lowercase string characters to uppercase.

Character Functions (cont’d)

312

Conversion Functions


TO_BIGINT Converts a string or numeric value to a bigint value.

TO_CHAR Converts numeric values and dates to text strings.

TO_DATE Converts a character string to a date datatype in the same format as the character

string.

TO_DECIMAL Converts any value (except binary) to a decimal.

TO_FLOAT Converts any value (except binary) to a double-precision floating point number (the

Double datatype).

TO_INTEGER Converts any value (except binary) to an integer by rounding the decimal portion of a

value.

313

Data Cleansing Functions


GREATEST Returns the greatest value from a list of input values

IN Matches input data to a list of values

INSTR Returns the position of a character set in a string, counting from left to right.

IS_DATE Returns whether a value is a valid date.

IS_NUMBER Returns whether a string is a valid number.

IS_SPACES Returns whether a value consists entirely of spaces.

ISNULL Returns whether a value is NULL.

LEAST Returns the smallest value from a list of input values.

LTRIM Removes blanks or characters from the beginning of a string.

METAPHONE Encodes characters of the English language alphabet (A-Z). It encodes both

uppercase and lowercase letters in uppercase.

314

Data Cleansing Functions (cont’d)


REG_EXTRACT Extracts subpatterns of a regular expression within an input value

REG_MATCH Returns whether a value matches a regular expression pattern

REG_REPLACE Replaces characters in a string with a another character pattern.

REPLACECHR Replaces characters in a string with a single character or no character

REPLACESTR Replaces characters in a string with a single character, multiple characters, or no

character.

RTRIM Removes blanks or characters from the end of a string.

SOUNDEX Encodes a string value into a four-character string.

SUBSTR Returns a portion of a string.

TO_BIGINT Converts a string or numeric value to a bigint value.

TO_CHAR Converts numeric values and dates to text strings.

TO_DATE Converts a character string to a date datatype in the same format as the character string.

TO_DECIMAL Converts any value (except binary) to a decimal.

TO_FLOAT Converts any value (except binary) to a double-precision floating point number (the

Double datatype).

TO_INTEGER Converts any value (except binary) to an integer by rounding the decimal portion of a

value.

315


ADD_TO_DATE Adds a specified amount to one part of a date/time value, and returns a date in

the same format as the specified date.

DATE_COMPARE Returns a value indicating the earlier of two dates.

DATE_DIFF Returns the length of time between two dates, measured in the specified

increment (years, months, days, hours, minutes, or seconds).

GET_DATE_PART Returns the specified part of a date as an integer value, based on the default

date format of MM/DD/YYYY HH24:MI:SS.

IS_DATE Returns whether a string value is a valid date.

LAST_DAY Returns the date of the last day of the month for each date in a port.

MAKE_DATE_TIME Returns the date and time based on the input values

ROUND Rounds one part of a date.

SET_DATE_PART Sets one part of a date/time value to a specified value.

TO_CHAR (DATE) Date/Time datatype. Passes the date values you want to convert to character

strings

TRUNC Truncates dates to a specific year, month, day, hour, or minute.

Date Functions

316

Encoding Functions


AES_DECRYPT Returns encrypted data to string format

AES_ENCRYPT Returns data in encrypted format

COMPRESS Compresses data using the zlib compression algorithm

CRC32 Returns a 32-bit Cyclic Redundancy Check (CRC32) value

DEC_BASE64 Decodes the value and returns a string with the binary data representation of the data

DECOMPRESS Decompresses data using the zlib compression algorithm

ENC_BASE64 Encodes data by converting binary data to string data using Multipurpose Internet

Mail Extensions (MIME) encoding

MD5 Calculates the checksum of the input value. The function uses Message-Digest

algorithm 5 (MD5)

317

Financial Functions


FV Returns the future value of an investment, where you make periodic, constant

payments and the investment earns a constant interest rate

NPER Returns the number of periods for an investment based on a constant interest rate and

periodic, constant payments

PMT Returns the payment for a loan based on constant payments and a constant interest

rate

PV Returns the present value of an investment

RATE Returns the interest rate earned per period by a security

318

Numeric Functions


ABS Returns the absolute value of a numeric value.

CEIL Returns the smallest integer greater than or equal to the specified numeric value.

CONVERT_BASE Converts a number from one base value to another base value

CUME Returns a running total of all numeric values.

EXP Returns e raised to the specified power (exponent), where e=2.71828183.

FLOOR Returns the largest integer less than or equal to the specified numeric value.

LN Returns the natural logarithm of a numeric value.

LOG Returns the logarithm of a numeric value.

MOD Returns the remainder of a division calculation.

MOVINGAVG Returns the average (record-by-record) of a specified set of records.

MOVINGSUM Returns the sum (record-by-record) of a specified set of records.

POWER Returns a value raised to the specified exponent.

RAND Returns a random number between 0 and 1

ROUND Rounds numbers to a specified digit.

SIGN Notes whether a numeric value is positive, negative, or 0.

SQRT Returns the square root of a positive numeric value.

TRUNC Truncates numbers to a specific digit.

319

Scientific Functions


COS Returns the cosine of a numeric value (expressed in radians).

COSH Returns the hyperbolic cosine of a numeric value (expressed in radians).

SIN Returns the sin of a numeric value (expressed in radians).

SINH Returns the hyperbolic sin of a numeric value (expressed in radians).

TAN Returns the tangent of a numeric value (expressed in radians).

TANH Returns the hyperbolic tangent of a numeric value (expressed in radians).

320

Special Functions


ABORT Stops the session and issues a specified error message.

DECODE Searches a port for the specified value.

ERROR Causes the PowerCenter Server to skip a record and issue the specified error message.

IIF Returns one of two values you specify, based on the results of a condition.

LOOKUP Searches for a value in a lookup source column.

Informatica recommends using the Lookup transformation.

321

String Functions


CHOOSE Chooses a string from a list of strings based on a given position.

INDEXOF Finds the index of a value among a list of values.

REVERSE Reverses the input string.

322

Test Functions


IS_DATE Returns whether a value is a valid date..

IS_NUMBER Returns whether a string is a valid number.

IS_SPACES Returns whether a value consists entirely of spaces.

ISNULL Returns whether a value is NULL.

323

Variable Functions


SETCOUNTVARIABLE Counts the rows evaluated by the function and increments the current value

of a mapping based on the count.

SETMAXVARIABLE

Sets the current value of a mapping variable to the higher of two values:the

current value of the variable or the value specified. Returns the new current

value.

SETMINVARIABLE

Sets the current value of a mapping variable to the lower of two values: the

current value of the variable or the value specified. Returns the new current

value.

SETVARIABLE Sets the current value of a mapping variable to a value you specify. Returns

the specified value.

SYSTIMESTAMP Returns the current date and time of the node hosting the Integration Service

with precision to the nanosecond.

324

Appendix C – Transformation Naming Conventions

325

Transformation Naming Each object in a PowerCenter repository is identified by a unique name.

This allows PowerCenter to efficiently manage and track statistics all

the way down to the object level.

When an object is created, PowerCenter automatically generates a

unique name. These names, however, do not reflect project/repository

specific context. As a best practice Informatica recommends the

following convention for naming PowerCenter objects:

<Object Type Abbreviation>_<Descriptive Name>

Abbreviations are usually 1 – 3 letters, the minimum needed to easily

identify the object type. For example:

agg_quarterly_total (an aggregator that computes a quarterly totals)

m_load_dw (a mapping that loads the datawarehouse)

exp_string_to_date (an expression that converts a string to a date)

326


Transformation Suggested Convention

Aggregator AGG_TransformationName

Application Source Qualifier ASQ_TransformationName

Custom CT_TransformationName

Expression EXP_TransformationName

External Procedure EXT_TransformationName

Filter FIL_TransformationName

Joiner JNR_TransformationName

Lookup LKP_TransformationName

MQ Source Qualifier SQ_MQ_TransformationName

Normalizer NRM_TransformationName

Rank RNK_TransformationName

327


Transformation Suggested Convention

Router RTR_TransformationName

Sequence Generator SEQ_TransformationName

Sorter SRT_TransformationName

Stored Procedure SP_TransformationName

Source Qualifier SQ_TransformationName

Transaction Control TC_TransformationName

Union UN_TransformationName

Update Strategy UPD_TransformationName

XML Generator XG_TransformationName

XML Parser XP_TransformationName

XML Source Qualifier XSQ_TransformationName

328

Lesson 6: Lab - homework

Documents

CE Student Guide PC_HandsOnWorkshop