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Informatica PowerCenter 7 LevelI Developer

Education ServicesVersion PC7LID-20050301

Informatica Corporation, 2003 - 2004. All rights reserved.


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Introduction


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By the end of this course you will:

Understand how to use the major PowerCentercomponents for development

Be able to build basic ETL mappings and mapplets* Be able to create, run and monitor workflows

Understand available options for loading target data

Be able to troubleshoot most problems

Note: The course does not cover PowerCenter optionalfeatures or XML support.

Course Objectives

* A mapplet is a subset of a mapping


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Founded in 1993

Leader in enterprise solution products

Headquarters in Redwood City, CA

Public company since April 1999 (INFA)

2000+ customers, including over 80% ofFortune 100

Strategic partnerships with IBM, HP, Accenture, SAP,

and many others Worldwide distributorship

About Informatica


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Informatica Products

PowerCenter ETL batch and real-time data integration

PowerAnalyzer BI reporting web-browser interface with reports,dashboards, indicators, alerts; handles real-time

metricsSuperGlue* Centralized metadata browsing cross-enterprise,

including PowerCenter, PowerAnalyzer, DBMS,BI tools, and data modeling tools

PowerExchange Data access to mainframe, mid-size system and

complex filesPowerCenterConnect products

Data access to transactional applications andreal-time services

* Uses PowerCenter to extract metadata and PowerAnalyzer to display reports


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www.informatica.com provides information (under Services) on: Professional Services

Education Services

my.informatica.com sign up to access:

Technical Support

Product documentation (under Tools online documentation)

Velocity Methodology (under Services)

Knowledgebase

Webzine

Mapping templates devnet.informatica.com sign up for Informatica Developers Network

Discussion forums

Web seminars

Technical papers

Informatica Resources


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Informatica offers three distinct Certification titles:

Exam A: Architecture and Administration Exam C: Advanced Administration

Exam A: Architecture and Administration Exam B: Mapping Design Exam D: Advanced Mapping Design

Exams A, B, C, D plus

Exam E: Enablement Technologies

For more information and to register to take an exam:http://www.informatica.com/services/Education+Services/Professional+Certification/

Informatica Professional Certification


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Extract, Transform and Load

Transaction level data

Optimized for transactionresponse time

Current

Normalized or

De-normalized data

Operational Systems

MainframeRDBMS Other

Aggregated data

Historical data

Decision Support

Data

Warehouse

ETL Load

Transform

Extract

Aggregate data Cleanse data Consolidate data Apply business rules De-normalize data


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PowerCenter Client Tools

Repository Designer Workflow Workflow Rep ServerManager Manager Monitor Administration

Console

Manage repository: Connections Folders

Objects Users and groups

Administer repositories on aRepository Server: Create/upgrade/delete

Configuration Start/stop Backup/restore

Build ETLmappings

Build and startworkflows torun mappings

Monitorand startworkflows


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PowerCenter 7 Architecture

Not Shown: Client ODBC connections from Designer to sources and targets for metadata

TargetsSources

Native Native

TCP/IP

HeterogeneousTargets

Repository

RepositoryServer

RepositoryAgent

TCP/IP

Native

Informatica Server

HeterogeneousSources

Repository Designer Workflow Workflow Rep ServerManager Manager Monitor Administrative

Console


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Distributed Architecture and Platforms

The following components can be distributed across anetwork of host computers: Clients Tools

PowerCenter Servers

Repository Servers Repository Databases

Sources and Targets

Platforms: Client tools run on Windows Servers run on AIX, HP-UX, Solaris, Redhat Linux, Windows

Repositories on any major RDBMS


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Design and Execution Process

1. Create Source definition(s)

2. Create Target definition(s)

3. Create a Mapping

4. Create a Session Task

5. Create a Workflow with Task components

6. Run the Workflow and verify the results


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Demonstration


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Source Object Definitions


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Source Object Definitions

By the end of this section you will:

Be familiar with the Designer interface

Be familiar with Source Types

Be able to create Source Definitions

Understand Source Definition properties

Be able to use the Data Preview option


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Import from: Relational database Flat file XML object

Create manually

Methods ofAnalyzing Sources

Source Analyzer

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Analyzing Relational Database Sources

Table View Synonym

Relational DB Source

DEF

Source Analyzer

ODBC

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Analyzing Relational Database Sources

Editing Source Definition Properties


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Analyzing Flat File Sources

Mapped Drive NFS Mount Local Directory DEF

Fixed Width Delimited

Flat FileSource Analyzer

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Flat File Wizard

Three-stepwizard

Columns canbe renamed

within wizard

Text, Numericand Datetimedatatypes are

supported Wizard

guessesdatatype


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Flat File Source Properties


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Analyzing XML Sources

DEF

XML Schema (XSD),DTD or XML File

DATA

Source Analyzer

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native

Mapped Drive NFS Mounting Local Directory


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Data Previewer

Preview data in Relational database sources

Flat file sources

Relational database targets

Flat file targets

Data Preview Option is available in Source Analyzer

Warehouse Designer

Mapping Designer

Mapplet Designer


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Using Data Previewer in Source Analyzer

Data Preview Example From Source Analyzer,select Source drop downmenu, then Preview Data

Enter connection informationin the dialog box

A right mouse click on the object can also be used to preview data


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Using Data Previewer in Source Analyzer

Data Preview Results

DataDisplay

View upto 500rows


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Metadata Extensions

Allows developers and partners to extend themetadata stored in the Repository

Metadata extensions can be:

User-defined PowerCenter users can define and createtheir own metadata

Vendor-defined Third-party application vendor-createdmetadata lists

For example, applications such as Ariba or PowerCenter Connect

for Siebel can add information such as contacts, version, etc.


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Example Metadata Extension for a Source

Sample User DefinedMetadata, e.g. contact

information, business user


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Target Object Definitions


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Target Object Definitions

By the end of this section you will:

Be familiar with Target Definition types

Know the supported methods of creating TargetDefinitions

Understand individual Target Definition properties


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Creating Target Definitions

Methods of creating Target Definitions

Import from relational database

Import from XML object

Create automatically from a source definition

Create manually (flat file or relational

database)


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Import Definition from Relational Database

Can obtain existing object definitions from a databasesystem catalog or data dictionary

TableViewSynonym

WarehouseDesigner

Relational DB

DEF

ODBC

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Import Definition from XML Object

Can infer existing object definitions from a databasesystem catalog or data dictionary

WarehouseDesigner

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native

DEF

DTD, XML Schema orXML File

DATA

Mapped Drive NFS Mounting Local Directory


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Creating Target Automatically from Source

Drag-and-dropa SourceDefinition intothe WarehouseDesigner

Workspace


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Target Definition Properties


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Lab 1 Define Sources and Targets


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Mappings


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Mappings

By the end of this section you will be familiar with:

The Mapping Designer interface

Transformation objects and views Source Qualifier transformation

The Expression transformation

Mapping validation


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Mapping Designer

Iconized Mapping

Mapping List

Transformation Toolbar


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Transformations Objects Used in This Class

Source Qualifier: reads data from flat file & relational sources

Expression: performs row-level calculations

Filter: drops rows conditionally

Sorter: sorts data

Aggregator: performs aggregate calculations

Joiner: joins heterogeneous sources

Lookup: looks up values and passes them to other objects

Update Strategy: tags rows for insert, update, delete, reject

Router: splits rows conditionally

Sequence Generator: generates unique ID values


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Other Transformation Objects

Normalizer: normalizes records from relational or VSAM sources

Rank: filters the top or bottom range of records

Union: merges data from multiple pipelines into one pipeline

Transaction Control: allows user-defined commits

Stored Procedure: calls a database stored procedure

External Procedure : calls compiled code for each row

Custom: calls compiled code for multiple rows

Midstream XML Parser: reads XML from database table or message queue

Midstream XML Generator: writes XML to database table or message queue

More Source Qualifiers: read from XML, message queues andapplications


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Source Qualifier Transformation

Ports All input/output

Usage Convert datatypes For relational sources:

Modify SQL statementUser Defined JoinSource FilterSorted portsSelect DISTINCTPre/Post SQL

Represents the source record set queried by theServer. Mandatory in Mappings using relational orflat file sources


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Source Qualifier Properties

User can modify SQL SELECT statement (DB sources)

Source Qualifier can join homogenous tables

User can modify WHERE clause

User can modify join statement

User can specify ORDER BY(manually orautomatically)

Pre- and post-SQL can be provided SQL properties do not apply to flat file sources


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Pre-SQL and Post-SQL Rules

Can use any command that is valid for the databasetype; no nested comments

Use a semi-colon (;) to separate multiple statements

Informatica Server ignores semi-colons within singlequotes, double quotes or within /* ...*/

To use a semi-colon outside of quotes or comments,escape it with a back slash (\)


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Expression Transformation

Ports Mixed Variables allowed

Create expression in anoutput or variable port

Usage Perform majority of

data manipulation

Perform calculations using non-aggregate functions(row level)

Click here to invoke theExpression Editor


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Expression Editor

An expression formula is a calculation or conditional statement for aspecific port in a transformation

Performs calculation based on ports, functions, operators, variables,constants and return values from other transformations


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Expression Validation

The Validate or OK button in the Expression Editor will:

Parse the current expression

Remote port searching (resolves references to ports in

other transformations) Parse default values

Check spelling, correct number of arguments in functions,other syntactical errors


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CharacterFunctions

Used to manipulate character data

CHRCODE returns the numeric value

(ASCII orU

nicode) of the first character ofthe string passed to this function

CONCAT is for backward compatibility only.Use || instead

ASCIICHRCHRCODECONCATINITCAPINSTR

LENGTHLOWERLPADLTRIMREPLACECHRREPLACESTRRPAD

RTRIMSUBSTRUPPER

Informatica FunctionsCharacter


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Informatica Functions Data Cleansing

INSTRIS_DATEIS_NUMBERIS_SPACESISNULLLTRIMMETAPHONE

REPLACECHRREPLACESTRRTRIMSOUNDEXSUBSTRTO_CHARTO_DATETO_DECIMALTO_FLOATTO_INTEGER

Used to process data during datacleansing

METAPHONE and SOUNDEX createindexes based on Englishpronunciation (2 different standards)


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Date Functions

Used to round, truncate, orcompare dates; extract one part

of a date; or perform arithmeticon a date

To pass a string to a datefunction, first use the TO_DATE

function to convert it to andate/time datatype

ADD_TO_DATEDATE_COMPAREDATE_DIFFGET_DATE_PARTLAST_DAYROUND (Date)

SET_DATE_PARTTO_CHAR (Date)TRUNC (Date)

Informatica Functions Date


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Informatica Functions Special and Test

ABORTDECODE

ERRORIIFLOOKUP

IIF(Condition,True,False)

IS_DATE

IS_NUMBERIS_SPACESISNULL

Test Functions

Used to test if a lookup result is null Used to validate data

Special Functions

Used to handle specific conditionswithin a session; search for certainvalues; test conditional statements


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Variable Ports

Use to simplify complex expressions e.g. create and store a depreciation formula to be

referenced more than once

Use in another variable port or an output port expression

Local to the transformation (a variable port cannot also be aninput or output port)


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Variable Ports (contd)

Use for temporary storage

Variable ports can remember values across rows; useful forcomparing values

Variables are initialized (numeric to 0, string to ) when the Mappinglogic is processed

Variables Ports are not visible in Normal view, only in Edit view


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Default Values Two Usages

For input and I/O ports, default values are used to replace nullvalues

For output ports, default values are used to handle transformationcalculation errors (not-null handling)

Defaultvalue for theselectedport

Selectedport Validate the

defaultvalue

expression

ISNULL functionis not required


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Informatica Datatypes

Transformation datatypes allow mixandmatch of source and target database types When connecting ports, native and transformation datatypes must be compatible

(or must be explicitly converted)

NATIVE DATATYPES TRANSFORMATION DATATYPESSpecific to the source and targetdatabase types

PowerCenter internal datatypes

Display in source and target tableswithin Mapping Designer

Display in transformations withinMapping Designer

Native NativeTransformation


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Datatype Conversions within PowerCenter

Data can be converted from one datatype to another by: Passing data between ports with different datatypes

Passing data from an expression to a port

Using transformation functions

Using transformation arithmetic operators

Only conversions supported are:

Numeric datatypesm Other numeric datatypes

Numeric datatypesm String

Date/Timem

Date or String For further information, see the PowerCenter Client Help > Index

> port-to-port data conversion


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Mapping Validation


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Connection Validation

Examples of invalid connections in a Mapping:

Connecting ports with incompatible datatypes

Connecting output ports to a Source

Connecting a Source to anything but a SourceQualifier or Normalizer transformation

Connecting an output port to an output port or

an input port to another input port


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Mapping Validation

Mappings must:

Be valid for a Session to run

Be end-to-end complete and contain valid expressions

Pass all data flow rules

Mappings are always validated when saved; can be validatedwithout being saved

Output Window displays reason for invalidity


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Lab 2 Create a Mapping


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Workflows


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Workflows

By the end of this section, you will be familiar with:

The Workflow Manager GUI interface

Creating and configuring Workflows

Workflow properties

Workflow components

Workflow tasks


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Workflow Manager Interface

TaskTool Bar

OutputWindow

Navigator

Window

Workspace

StatusBar

WorkflowDesignerTools


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Workflow Designer

Maps the execution order and dependencies of Sessions,Tasks and Worklets, for the Informatica Server

Task Developer Create Session, Shell Command and Email tasks

Tasks created in the Task Developer are reusable

Worklet Designer

Creates objects that represent a set of tasks

Worklet objects are reusable

Workflow Manager Tools


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Workflow Structure

A Workflowis set of instructions for the InformaticaServer to perform data transformation and load

Combines the logic of Session Tasks, other types ofTasks and Worklets

The simplest Workflow is composed of a Start Task, aLink and one other Task

StartTask

SessionTask

Link


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Eight additional Tasks are available in the Workflow Designer(coveredlater)

Command

Email

Decision

Assignment

Timer

Control

Event Wait

Event Raise

Additional Workflow Tasks


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Sample Workflow

Start Task(required)

Session 1

Session 2

CommandTask


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Sequential and Concurrent Workflows

Sequential

Concurrent Combined

Note: Although only session tasks are shown, can be any tasks


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Creating a Workflow

CustomizeWorkflow name

Select aServer


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Workflow Properties

Customize WorkflowProperties

Workflow log displays

May be reusable ornon-reusable

Select a WorkflowSchedule (optional)


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Workflow Scheduler

Set and customize workflow-specific schedule


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Workflow Metadata Extensions

Metadata Extensions providefor additional user data


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Workflow Links

Required to connect Workflow Tasks

Can be used to create branches in a Workflow

All links are executed unless a link condition is used whichmakes a link false

Link 2

Link 1 Link 3


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Conditional Links

Optional linkcondition

$taskname.STATUSis a pre-defined

task variable


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Workflow Variables 1

Task-specificvariables

Built-in systemvariables

Used in decision tasks and conditional links edit task or link:

User-defined variables(see separate slide)

Pre-defined variables


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User-defined variables are set in Workflow properties,Variables tab can persist across sessions

Can be reset inan Assignment task

Workflow Variables 2


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Workflow Summary

1. Add Sessions and other Tasks to the Workflow

2. Connect all Workflow components with Links

3. Save the Workflow

Sessions in a Workflow can be executed independently

4. Start the Workflow


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Session Tasks


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Session Tasks

After this section, you will be familiar with:

How to create and configure Session Tasks

Session Task source and target properties


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Created to execute the logic of a mapping (onemapping only)

Session Tasks can be created in the Task Developer(reusable) or Workflow Developer(Workflow-specific)

To create a Session Task

Select the Session button from the Task Toolbar

OrSelect menu Tasks | Create and select Session fromthe drop-down menu

Creating a Session Task


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Session Task Properties and Parameters

Session Task

Sessionparameter

Properties Tab

Parameter file


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Session Task Setting Source Properties

Set

properties

Session Task

Selectsource

instance

Mapping Tab

Setconnection


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Session Task Setting Target Properties

Note: Heterogeneous targetsare supported

Session Task

Select target

instance

Mapping Tab

Set properties

Set connection


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Monitoring Workflows


The Workflow Monitor GUI interface

Monitoring views

Server monitoring modes

Filtering displayed items

Actions initiated from the Workflow Monitor

Truncating Monitor Logs


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Workflow Monitor

The Workflow Monitor is the tool for monitoringWorkflows and Tasks

Choose between two views:

Gantt chart

Task view

Gantt Chart view Task view


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Monitoring Current and Past Workflows

The Workflow Monitor displays only workflowsthat have been run

Displays real-time information from theInformatica Server and the Repository Server

about current workflow runs


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Monitoring Operations

Perform operations in the Workflow Monitor Stop, Abort, or Restart a Task, Workflow or Worklet Resume a suspended Workflow after a failed Task is

corrected

Reschedule orUnschedule a Workflow

View Session and Workflow logs

Abort has a 60 second timeout If the Server has not completed processing and

committing data during the timeout period, the threadsand processes associated with the Session are killed

Stopping a Session Task means the Server stops reading data


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Monitoring in Task View

Start Completion

Task Server Workflow Worklet Time Time

Status Bar

Start, Stop, Abort, ResumeTasks,Workflows and Worklets


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Filtering in Task View

Monitoring filterscan be set usingdrop down menus.Minimizes itemsdisplayed inTask View

Right-click on Session to retrieve theSession Log (from the Server to thelocal PC Client)


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Filter Toolbar

Display recent runs

Filter tasks by specified criteria

Select servers to filter

Select type of tasks to filter

T i W kfl M i L


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Truncating Workflow Monitor Logs

Workflow Monitor

Repository Manager

Repository ManagersTruncate Log optionclears the WorkflowMonitor logs


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Lab 3 Create and Run a Workflow


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Lab 4 Features and Techniques I


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Debugger

D b


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Debugger


Creating a Debug Session

Debugger windows and indicators

Debugger functionality and options

Viewing data with the Debugger

Setting and using Breakpoints

Tips for using the Debugger

D b F t


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Debugger Features

Wizard driven tool that runs a test session

View source / target data

View transformation data

Set breakpoints and evaluate expressions

Initialize variables

Manually change variable values

Data can be loaded or discarded

Debug environment can be saved for later use

D b I t f


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Debugger Interface

Target Instancewindow

TransformationInstance

Data window

Flashingyellow

SQLindicator

Debugger Modeindicator

Solid yellowarrow is current

transformationindicator

Output Window Debugger Log

EditBreakpoints

S t B k i t


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Set Breakpoints

2. Choose global orspecific transformation

3. Choose to break on

data condition or error.Optionally skip rows.

4. Add breakpoint(s)

5. Add data conditions

1. Edit breakpoint

6. Continue (to next breakpoint)

D b Ti


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Server must be running before starting a Debug Session

When the Debugger is started, a spinning icon displays.Spinning stops when the Debugger Server is ready

The flashing yellow/green arrow points to the current activeSource Qualifier. The solid yellow arrow points to the currentTransformation instance

Debugger Tips

Next Instance proceeds a single step at a time; onerow moves from transformation to transformation

Step to Instance examines one transformation at atime, following successive rows through the sametransformation


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Lab 5 The Debugger


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Filter Transformation



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Ports All input / output

Specify a Filter condition

Usage Filter rows from

input flow

Drops rows conditionally



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Lab 6 Flat File Wizard and Filter

Transformation


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Sorter Transformation


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Sorts data from any source, at any point in a data flow

Ports Input/Output Define one or more

sort keys Define sort order for

each key

Example ofUsage Sort data before

Aggregator to improve

performance

Sort Keys

Sort Order

Sorter Properties


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Sorter Properties

Cache size can be

adjusted. Default is 8 Mb. Ensure sufficient memoryis available on theInformatica Server (elseSession Task will fail)


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Aggregator Transformation



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Basic Aggregator functionality

Creating subtotals with the Aggregator

Aggregator expressions

Aggregator properties

Using sorted data



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Ports Mixed I/O ports allowed

Variable ports allowed Group By allowed

Create expressions invariable and output ports

Usage Standard aggregations

Performs aggregate calculations

Aggregate Expressions


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Aggregate Expressions

Conditional Aggregateexpressions are supported: Conditional SUM format: SUM(value, condition)

Aggregatefunctions aresupported only inthe AggregatorTransformation

Aggregator Functions


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Aggregator Functions

Return summary values for non-null datain selected ports

Use only in Aggregator transformations

Use in output ports only

Calculate a single value (and row) for allrecords in a group

Only one aggregate function can benested within an aggregate function

Conditional statements can be used with

these functions

AVGCOUNTFIRSTLASTMAXMEDIAN

MINPERCENTILESTDDEVSUMVARIANCE

Aggregator Properties


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Aggregator Properties

Sorted Input Property

Set Aggregatorcache sizes for

Informatica Servermachine

Instructs theAggregator to

expect the datato be sorted

Sorted Data


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Sorted Data

The Aggregator can handle sorted or unsorted data

Sorted data can be aggregated more efficiently, decreasing totalprocessing time

The Server will cache data from each group and

release the cached data uponreachingthe firstrecordofthenextgroup

Data mustbe sorted according to the order of theAggregators Group By ports

Performance gain will depend upon varying factors

Aggregating Unsorted Data


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Aggregating Unsorted Data

Unsorteddata

No rows are released from Aggregatoruntil all rows are aggregated

Group By:- store- department- date

Aggregating Sorted Data


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Aggregating Sorted Data

Each separate group (one row) is released assoon as the last row in the group isaggregated

Group By:- store- department- date

Data sorted by:- store- department- date

Data Flow Rules Terminology


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Data Flow Rules Terminology

Passive transformation

Operates on one row of data at a time AND

Cannot change the number of rows on the data flow

Example: Expression transformation

Active transformation

Can operate on groups of data rows AND/OR

Can change the number of rows on the data flow

Examples: Aggregator, Filter, Source Qualifier

Data Flow Rules


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Data Flow Rules

Each Source Qualifier starts a single data stream (data flow)

Transformations can send rows to more than onetransformation (split one data flow into multiple pipelines)

Two or more data flows can meet only if they originate from acommon active transformation

Example holds true with Normalizer instead of Source Qualifier.Exceptions are: Mapplet Input and sorted Joiner transformations

DISALLOWED

TT

Active

ALLOWED

T

Passive

T


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Joiner Transformation



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Jo e s o o


When to join in Source Qualifier and when in Joinertransformation

Homogeneous joins

Heterogeneous joins

Joiner properties

Joiner conditions

Nested joins

When to Join in Source Qualifier


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Q

Ifyou can perform a join on the source database, thenyou can configure it in the Source Qualifier

The SQL that the Source Qualifier generates, default orcustom, executes on the source database at runtime

Example: homogeneous join 2 database tables in samedatabase

When You Cannot Join in Source Qualifier


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Q

Ifyou cannotperform a join on the source database, thenyou cannotconfigure it in the Source Qualifier

Examples: heterogeneous joins

An Oracle table and a DB2 table

A flat file and a database table

Two flat files



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Active Transformation

Ports All input or input / output

M denotes port comesfrom master source

Examples Join two flat files Join two tables from

different databases Join a flat file with arelational table

Performs heterogeneous joins on different dataflows

Joiner Conditions


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Multiple join conditions aresupported

Joiner Properties


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p

Join types:

Normal (inner)

Master outer

Detail outer Full outer

Joiner can accept sorted data (configure the join condition to use thesort origin ports)

Set JoinerCaches

Nested Joins


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Used to join three or more heterogeneous sources

Mid-Mapping Join (Unsorted)


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pp g ( )

The unsorted Joiner does not accept input in thefollowing situations: Both input pipelines begin with the same Source Qualifier

Both input pipelines begin with the same Joiner

The sorted Joiner does not have these restrictions.


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Lab 7 Heterogeneous Join, Aggregator, and

Sorter


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Lookup Transformation



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Lookup principles

Lookup properties

Lookup conditions

Lookup techniques

Caching considerations

Persistent caches

How a Lookup Transformation Works


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For each mapping row, one or more port values are looked up in a

database table or flat file

If a match is found, one or more table values are returned to themapping. If no match is found, NULL is returned

Lookup value(s)

Return value(s)

Lookup transformation



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Looks up values in a database table or flat file andprovides data to other components in a mapping

Ports Mixed L denotes Lookup port

R denotes port used as areturn value (unconnectedLookup only see later)

Specify the Lookup Condition

Usage Get related values Verify if records exists or if

data has changed

Lookup Conditions


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Multiple conditions are supported

Lookup Properties


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Lookuptable name

Native databaseconnection object name

Lookup condition

Source type:Database orFlat File

Lookup Properties contd


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Policy on multiplematch: Use first value Use last value Report error

Lookup Caching


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Caching can significantly impact performance

Cached

Lookup table data is cached locally on the Server

Mapping rows are looked up against the cache

Only one SQL SELECT is needed

Uncached

Each Mapping row needs one SQL SELECT

Rule Of Thumb: Cache if the number (and size) of records inthe Lookup table is small relative to the number of mappingrows requiring the lookup

Persistent Caches


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By default, Lookup caches are not persistent; when thesession completes, the cache is erased

Cache can be made persistent with the Lookup properties

When Session completes, the persistent cache is storedon the server hard disk

The next time Session runs, cached data is loaded fully orpartially into RAM and reused

A named persistent cache may be shared by differentsessions

Can improve performance, but stale data may pose aproblem

Lookup Caching Properties


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Override LookupSQL option

Cachedirectory

Togglecaching

Lookup Caching Properties (contd)


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Set Lookupcache sizes

Make cachepersistent

Set prefix forpersistent cachefile name

Reloadpersistentcache


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Lab 8 Basic Lookup


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Target Options

Target Options


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Default target load type

Target properties

Update override

Constraint-based loading

Setting Default Target Load Type


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Set Target Load Type default Workflow Manager, Tools | Options Normal orBulk (client choice) Override the default in sessiontarget properties


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WHERE Clause for Update and Delete


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PowerCenter uses the primary keys defined in theWarehouse Designer to determine the appropriate SQLWHERE clause for updates and deletes

Update SQL

UPDATE SET = WHERE =

The only columns updated are those which have values linkedto them

All other columns in the target are unchanged

The WHERE clause can be overridden via Update Override

Delete SQL DELETE from WHERE =

SQL statement used will appear in the Session log file

Constraint-based Loading


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PK1

FK1 PK2

FK2

To maintain referential integrity, primary keys mustbe loaded before their corresponding foreign keys here in the order Target1, Target2, Target 3

Setting Constraint-based Loading


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Constraint-based Loading Terminology


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Active transformation

Can operate on groups of data rows and/orcan change the number of rows on the data flow

Examples: Source Qualifier, Aggregator, Joiner, Sorter, Filter

Active source

Active transformation that generates rows

Cannot match an output row with a distinct input row

Examples: Source Qualifier, Aggregator, Joiner, Sorter

(The Filter is NOT an active source)

Active group Group of targets in a mapping being fed by the same active

source

Constraint-Based Loading Restrictions


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Cannot have two active groups

Example 1

With onlyoneActive source,rows for Targets1, 2, and 3 willbe loaded properly and maintainreferential integrity

PK1

FK1PK2

FK2

Example 2With twoActive sources, it is notpossible to control whether rowsfor Target3 will be loaded before

or after those for Target2

PK1

FK1

PK2

FK2


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Lab 9 Deleting Rows


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Update Strategy

Transformation

Update Strategy Transformation


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Used to specify how each individual row will be used to

update target tables (insert, update, delete, reject)

Ports All input / output

Specify theU

pdateStrategy Expression IIF or DECODE logicdetermines how tohandle the record

Example

Updating SlowlyChanging Dimensions

Update Strategy Expressions


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IIF ( score > 69, DD_INSERT, DD_DELETE )

Expression is evaluated for each row

Rows are tagged according to the logic of the

expression Appropriate SQL (DML) is submitted to the target

database: insert, delete or update

DD_REJECT means the row will not have SQL written

for it. Target will not see that row Rejected rows may be forwarded through Mapping


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Lab 10 Data Driven Operations


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Lab 11 Incremental Update


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Lab 12 Features and Techniques II


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Router Transformation

Router Transformation


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Rows sent to multiple filter conditions

Ports All input/output

Specify filter conditionsfor each Group

Usage Link source data in

one pass to multiplefilter conditions

Router Groups


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Input group (always one)

User-defined groups

Each group has one condition

ALL group conditions are evaluated

for EACH row One row can pass multiple

conditions

Unlinked Group outputsare ignored

Default group (always one) cancapture rows that fail all Groupconditions

Router Transformation in a Mapping


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Lab 13Router


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Sequence Generator

Transformation

Sequence Generator Transformation


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Generates unique keys for any port on a row

Ports Two predefined output

ports, NEXTVAL andCURRVAL

No input ports allowed

Usage Generate sequence

numbers Shareable across mappings

Sequence Generator Properties


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Number ofcached values


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Mapping Parameters and

Variables

Mapping Parameters and Variables


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By the end of this section you will understand:

System variables

Mapping parameters and variables

Parameter files

System Variables

P id t d t ti th


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SESSSTARTTIME

$$$SessStartTime

Returns the system date value on theInformatica Server Used with any function that accepts

transformation date/time datatypes Not to be used in a SQL override Has a constant value

Returns the system date value asastring. Uses system clock on machinehosting Informatica Server

Format of the string is database typedependent Used in SQL override Has a constant value

SYSDATE Provides current datetime on the

Informatica Server machine Not a static value



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Apply to all transformations within one Mapping Represent declared values

Variables can change in value during run-time

Parameters remain constant during run-time

Provide increased development flexibility

Defined in Mapping menu

Format is $$VariableNameor $$ParameterName

Can be used in pre and post-SQL



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Sample declarations

Declare Mapping Variables and Parametersin the Designer Mappings/Mapplets menu

Setaggregationtype

Set optionalinitial value

User-definednames

Set datatype



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Apply parameters or variables in formula

Functions to Set Mapping Variables


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SETMAXVARIABLE($$Variable,value)

Sets the specified variable to the higher of the currentvalue or the specified value

SETMINVARIABLE($$Variable,value)Sets the specified variable to the lower of of the

current value or the specified value SETVARIABLE($$Variable,value)

Sets the specified variable to the specified value

SETCOUNTVARIABLE($$Variable)

Increases or decreases the specified variable by thenumber of rows leaving the function(+1 for eachinserted row, -1 for each deleted row, no change forupdated or rejected rows)

Parameter Files


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You can specify a parameterfile for a session in thesession editor

Parameter file contains folder.session name and initializeseach parameter and variable for that session. For example:

[Production.s_m_MonthlyCalculations]$$State=MA

$$Time=10/1/2000 00:00:00$InputFile1=sales.txt$DBConnection_target=sales$PMSessionLogFile=D:/session logs/firstrun.txt

Parameters & Variables Initialization Priority


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1. Parameter file

2. Repository value

3. Declared initial value

4. Default value


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Unconnected Lookups

Unconnected Lookups


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By the end of this section you will know:

Unconnected Lookup technique

Unconnected Lookup functionality

Difference from Connected Lookup

Unconnected Lookup


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Physically unconnected from other transformations NO data flow

arrows leading to or from an unconnected Lookup Lookup data is called from the point in the Mapping that needs it Lookup function can be set within any transformation that supports

expressions

Function in the Aggregator

calls the unconnected Lookup

Unconnected Lookup Technique


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Condition is evaluated for each row but Lookup functionis called only if condition satisfied

IIF (ISNULL(customer_id),:lkp.MYLOOKUP(order_no))

Condition

Lookup function

Row keys

(passedto Lookup)

Use lookup lookup function within a conditional statement

Unconnected Lookup Advantage


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Data lookup is performed onlyfor those rows whichrequire it. Substantial performance can be gained

EXAMPLE: A Mapping will process 500,000 rows. For twopercent of those rows (10,000) the item_id value is NULL.Item_ID can be derived from the SKU_NUMB.

Net savings = 490,000 lookups

IIF (ISNULL(item_id), :lkp.MYLOOKUP(sku_numb))

Condition

(true for2 percent of all rows)

Lookup

(called only when condition is true)

Unconnected Lookup Functionality


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One Lookup port value may be returned for each Lookup

Must check aReturn port in the

Ports tab, elsefails at runtime


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Lab 14 Straight Load


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Lab 15 Conditional Lookup


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Heterogeneous Targets

Heterogeneous Targets


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Heterogeneous target types

Heterogeneous target limitations

Target conversions

Definition: Heterogeneous Targets


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Supported target definition types:

Relational database

Flat file

XML Targets supported by PowerCenter Connects

Heterogeneous targets are targets within a single

Session Task that have different types or

have differentdatabase connections

Step One: Identify Different Target Types


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Oracle table

Flat file

Oracle tableTables are EITHER in twodifferent databases, orrequire different (schema-specific) connect strings

One target is a flat file load

Step Two: Different Database Connections


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The two databaseconnections aredifferent

Flat file requires

separate locationinformation

Target Type Override (Conversion)


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Example: Mapping has SQL Server target definitions.Session Task can be set to load Oracle tables instead,using an Oracle database connection.

The following overrides are supported:

Relational target to flat file target

Relational target to any other relational database type

CAUTION: If target definition datatypes are not compatible with datatypes innewly selected database type, modify the target definition


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Mapplets

Mapplets


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By the end of this section you will be familiar with: Mapplet Designer

Mapplet advantages

Mapplet types Mapplet rules

Active and Passive Mapplets

Mapplet Parameters and Variables

Mapplet Designer


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MappletInput and OutputTransformation

Icons

Mapplet OutputTransformation

Mapplet Designer Tool

Mapplet Advantages


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Useful for repetitive tasks / logic

Represents a set of transformations

Mapplets are reusable

Use an instance of a Mapplet in a Mapping

Changes to a Mapplet are inherited by all instances

Server expands the Mapplet at runtime

AMapplet Used in a Mapping


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Unsupported Transformations


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Do not use the following in a mapplet:

XML source definitions

Target definitions

Other mapplets

Mapplet Source Options

Internal Sources


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Internal Sources

One or more Source definitions / Source Qualifierswithin the Mapplet

External Sources

Mapplet contains a Mapplet Input transformation Receives data from the Mapping it is used in

Mixed Sources

Mapplet contains one or more of either of a Mapplet

Input transformation AND one or more Source Qualifiers

Receives data from the Mapping it is used in, AND fromthe Mapplet

Use for data sources outside a Mapplet

Mapplet Input Transformation


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Use for data sources outside a Mapplet

Passive TransformationConnected

Ports

Output ports only

Usage

Only those portsconnected from anInput transformation

to anothertransformationwill display in theresulting Mapplet

Connecting thesame port to morethan onetransformation isdisallowed

Pass to anExpressiontransformationfirst

Transformation

Transformation

Data Source Outside a Mapplet

Source data is defined


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Resulting Mapplet HASinput ports

When used in a Mapping,the Mapplet may occur atany point in mid-flow


OUTSIDE the Mapplet logic

Mapplet

Mapplet Input

Transformation

Data Source Inside a Mapplet

SourceSource data is defined


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Resulting Mapplet has noinput ports

When used in a Mapping,the Mapplet is the firstobject in the data flow

Mapplet

No Input transformationis required (or allowed)

Use a Source Qualifier

instead

Qualifier


WITHIN the Mapplet logic

Mapplet Output Transformation

Use to contain the results of a Mapplet pipeline Multiple


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Passive TransformationConnected

Ports

Input ports only

Usage

Only those ports connected toan Output transformation (fromanother transformation) will

display in the resulting Mapplet

One (or more) Mapplet Outputtransformations are required in

every Mapplet

Use to contain the results of a Mapplet pipeline. Multiple

Output transformations are allowed.

Mapplet withMultiple Output Groups


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Can output to multiple instances of the same target table

Unmapped Mapplet Output Groups


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Warning: An unlinkedMapplet Output Groupmay invalidate themapping

Active and Passive Mapplets


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Passive Mapplets contain only passive transformations

Active Mapplets contain one or more activetransformations

CAUTION: Changing a passive Mapplet into an active Mappletmay invalidate Mappings which use that Mapplet so do an impactanalysis in Repository Manager first


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Mapplet Parameters and Variables


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Same idea as mapping parameters and variables

Defined under theMapplets | Parameters and Variables

menu option A parameter or variable defined in a mapplet is not

visible in any parent mapping

A parameter or variable defined in a mapping is notvisible in any child mapplet


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Lab 17Mapplets


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Reusable Transformations



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Transformation Developer

Reusable transformation rules

Promoting transformations to reusable

Copying reusable transformations

Transformation Developer


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Reusabletransformations

Make atransformationreusable fromthe outset,

or

test it in a

mapping first


Define once, reuse many times


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, y


Can be a copy or a shortcut

Edit Ports only in Transformation Developer

Can edit Properties in the mapping

Instances dynamically inherit changes

Caution: changing reusable transformations can invalidatemappings

Note: Source Qualifier transformations cannotbe made reusable

Promoting a Transformation to Reusable


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Check theMake reusable box

(irreversible)

Copying Reusable Transformations

This copy action must be done within the same folder


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This copy action must be done within the same folder

1. Hold down Ctrl key and drag a Reusable transformation fromthe Navigator window into a mapping (Mapping Designer tool)

2. A message appears in the status bar:

3. Drop the transformation into the mapping

4. Save the changes to the Repository


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Lab 18 Reusable Transformations


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Session-Level Error Logging

Error Logging Objectives


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By the end of this section, you will be familiar with:

Setting error logging options

How data rejects and transformation errors are

handled with logging on and off

How to log errors to a flat file or relational table

When and how to use source row logging

Error Types


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Transformation error Data row has only passed partway through the mapping

transformation logic

An error occurs within a transformation

Data reject

Data row is fully transformed according to the mappinglogic

Due to a data issue, it cannot be written to the target

A data reject can be forced by an Update Strategy

Error Logging Off/On


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Error Type Logging OFF (Default) Logging ONTransformationerrors

Written to session logthen discarded

Appended to flat file orrelational tables. Onlyfatal errors written tosession log.

Data rejects Appended to reject file(one .bad file per target)

Written to row errortables or file

Setting Error Log Options

In Session task


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Log Row DataLog Source Row Data

Error Log Type

Error Logging Off Specifying Reject Files


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In Session task1 file per target

Error Logging Off Transformation Errors

Details and data are written to session log


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X

X

Transformation Error

Data row is discarded If data flows concatenated, corresponding rows in parallel

flow are also discarded

Error Logging Off Data Rejects

Conditions causing data to be rejected include:


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Target database constraint violations, out-of-space errors, logspace errors, null values not accepted

Data-driven records, containing value 3 or DD_REJECT(the reject has been forced by an Update Strategy)

Target table properties reject truncated/overflowed rows

0,D,1313,D,Regulator System,D,Air Regulators,D,250.00,D,150.00,D1,D,1314,D,Second Stage Regulator,D,Air Regulators,D,365.00,D,265.00,D2,D,1390,D,First Stage Regulator,D,Air Regulators,D,170.00,D,70.00,D3,D,2341,D,Depth/Pressure Gauge,D,Small Instruments,D,105.00,D,5.00,D

Sample reject file

Indicator describes preceding column valueD=Data, O=Overflow, N=Null or T=Truncated

First column:0=INSERTp1=UPDATEp2=DELETEp3=REJECTp

Log Row Data

Logs:


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g

Session metadata

Reader, transformation, writer and user-defined errors

For errors on input, logs row data forI and I/O ports

For errors on output, logs row data forI/O and O ports

Logging Errors to a Relational Database 1


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Relational DatabaseLog Settings

Logging Errors to a Relational Database 2


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PMERR_SESS: Stores metadata about the session runsuch as workflow name, session name, repository nameetc

PMERR_MSG: Error messages for a row of data arelogged in this table

PMERR_TRANS: Metadata about the transformation suchas transformation group name, source name, port nameswith datatypes are logged in this table

PMERR_DATA: The row data of the error row as well as

the source row data is logged here. The row data is in astring format such as [indicator1: data1 | indicator2: data2]

Error Logging to a Flat File 1

Creates delimited Flat File with || as column delimiter


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Flat File LogSettings (Defaults

shown)

Logging Errors to a Flat File 2

Format: Session metadata followed by de-normalized error information

Sample session metadata


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**********************************************************************

Repository GID: 510e6f02-8733-11d7-9db7-00e01823c14d

Repository: RowErrorLogging

Folder: ErrorLogging

Workflow: w_unitTests

Session: s_customers

Mapping: m_customersWorkflow Run ID: 6079

Worklet Run ID: 0

Session Instance ID: 806

Session Start Time: 10/19/2003 11:24:16

Session Start Time (UTC): 1066587856

**********************************************************************

Row data formatTransformation || Transformation Mapplet Name || Transformation Group || PartitionIndex || Transformation Row ID || Error Sequence || Error Timestamp || Error UTCTime || Error Code || Error Message || Error Type || Transformation Data || SourceMapplet Name || Source Name || Source Row ID || Source Row Type || Source Data

Log Source Row Data 1


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Separate checkbox in session task

Logs the source row associated with the error row

Logs metadata about source, e.g. Source Qualifier,

source row id, and source row type


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Workflow Configuration

Workflow Configuration Objectives


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By the end of this section, you will be able to create:

Workflow Server Connections

Reusable Schedules

Reusable Session Configurations


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Workflow Server Connections


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Relational Connections (Native )

Create a relational [database] connection

I t ti t th S t l t l ti l t bl


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Instructions to the Server to locate relational tables Used in Session Tasks

Relational Connection Properties

Define native

l ti l d t b


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relational databaseconnection

Optional Environment SQL(executed with each use ofdatabase connection)

User Name/Password

Database connectivityinformation

Rollback Segmentassignment (optional)

FTP Connection

Create an FTP connection

Instructions to the Server to ftp flat files


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Used in Session Tasks

External Loader Connection

Create an External Loader connection

I t t th S t i k t l d t b l d


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Instructs the Server to invoke an external database loader Used in Session Tasks


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Reusable Workflow Schedules

Set up reusable schedules to associate with multiple Workflows

D fi d t f ld l l



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Defined at folder level Must have the Workflow Designer tool open



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Reusable Session Configurations

Session Configuration

Define properties to be reusable across different


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Define properties to be reusable across differentsessions

Defined at folder level

Must have one of these toolsopen in order to access


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Session Configuration (contd)


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Session TaskConfig Object


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Within Session task properties, choose desiredconfiguration

Session TaskConfig Object Attributes


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Attributes

may beoverriddenwithin theSession task


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Reusable Tasks

Reusable Tasks

Three types of reusable Tasks


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Three types ofreusable TasksSession Set of instructions

to execute a specificMapping

Command Specific shellcommands to run duringany Workflow

Email Sends email duringthe Workflow

Reusable Tasks

Use the TaskDeveloperto

create reusable tasks


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create reusable tasks

These tasks will then appearin the Navigator and can bedragged and dropped intoany workflow

Reusable Tasks in a Workflow

In a workflow a reusable task is represented


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In a workflow, a reusable task is representedwith the symbol

ReusableNon-reusable

Command Task

Specify one or more Unix shell or DOS commands to

run during the Workflow


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run during the Workflow Runs in the Informatica Server (UNIX or Windows)

environment

Command task status (successful completion or

failure) is held in the pre-defined task variable$command_task_name.STATUS

Each Command Task shell command can executebefore the Session begins or after the InformaticaServer executes a Session

Command Task

Specify one (or more) Unix shell or DOS (NT, Win2000)commands to run at a specific point in the workflow


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commands to run at a specific point in the workflow

Becomes a component of a workflow (or worklet)

If created in the Task Developer, the Command task isreusable

If created in the Workflow Designer, the Command task isnot reusable

Commands can also be invoked under the Componentstab of a Session task to run pre- or post-session


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Command Task (contd)


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Add Cmd

Remove Cmd

Email Task

Configure to have the Informatica Server to send email

at any point in the Workflow


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at any point in the Workflow

Becomes a component in a Workflow (or Worklet)

If configured in the Task Developer, the Email Task isreusable (optional)

Emails can also be invoked under the Components tabof a Session task to run pre- or post-session

Email Task (contd)


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Lab 20 Command Task


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Non-Reusable Tasks


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Decision Task

Specifies a condition to be evaluated in the Workflow

Use the Decision Task in branches of a Workflow


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Use link conditions downstream to control execution flow bytesting the Decision result


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Timer Task

Waits for a specified period of time to execute the

next Task


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e t asGeneral Tab

Absolute Time

Datetime Variable

Relative Time

Timer Tab

Control Task

Stop or ABORT the Workflow

Properties Tab


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GeneralTab

Event Wait Task

Pauses processing of the pipeline until aspecified event occurs


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specified event occurs

Events can be:

Pre-defined file watch

U

ser-defined created by an Event Raise task elsewhere inthe workflow

Event Wait Task (contd)

General TabProperties Tab


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Event Wait Task (contd)

Events Tab


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User-defined event configuredin the Workflow object

Event Raise Task

Represents the location of a user-defined event

The Event Raise Task triggers the user-defined event when theInformatica Ser er e ec tes the E ent Raise Task


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Informatica Server executes the Event Raise Task

Used with the Event Wait Task

General Tab Properties Tab


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Worklets

Worklets

An object representing a set or grouping of Tasks

Can contain any Task available in the Workflow


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Can contain any Task available in the WorkflowManager

Worklets expand and execute inside a Workflow

A Workflow which contains a Worklet is called theparent Workflow

Worklets CAN be nested

Reusable Worklets create in the Worklet Designer

Non-reusable Worklets create in the WorkflowDesigner

Re-usable Worklet

In the Worklet Designer, select Worklets | Create


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Tasks in a Worklet

WorkletsNode

Using a Reusable Worklet in a Workflow


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Workletused in a

Workflow

Non-Reusable Worklet

1. Create worklet task inWorkflow Designer

2. Right-click on new worklet


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gand select Open Worklet

3. Workspace switches toWorklet Designer

NOTE: Worklet

shows only underWorkflows node


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Lab 21 Reusable Worklet and Decision Task


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Lab 23 User Defined Event Event Raise


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Lab 23 User-Defined Event, Event Raise,

and Event Wait


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Parameters and VariablesReview

Types of Parameters and Variables

TYPE HOW DEFINED WHERE USED EXAMPLES

Mapping/

MappletVariables

Mapping/mapplet

properties. Reset byvariable functions.

Transformation port

expressions

$$LastUpdateTime

$$MaxValue


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Mapping/MappletParameters

Mapping/mappletproperties. Constantfor session.

Transformation portexpressions

$$FixedCosts$$DiscountRate

SystemVariables

Built-in, pre-defined. Transformation portexpressions,

Workflow decisiontasks andconditional links.

SYSDATESESSSTARTIME

WORKFLOWSTARTTIME

TaskVariables

Built-in, pre-defined. Workflow decisiontasks andconditional links

$session1. Status$session1.ErrorCode

Workflow/

WorkletVariables

Workflow or worklet

properties. Reset inAssignment tasks.

Workflow decision

tasks andconditional links

$$NewStartTime

SessionParameters

Parameter file.Constant for session.

Session properties $DBConnectionORCL$InputFile1

Mappings& Mapplets

Workflows& Worklets


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PowerCenter7.1 Options andData Access Products

PowerCenter 7.1 Options

Profile wizards, rules definitions, profile results tables,and standard reportsData ProfilingData Profiling

Allows export/import of metadata to or from businessintelligence tools like Business Objects and CognosMetadata Exchange with BIMetadata Exchange with BI


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PowerCenterPowerCenter

RealReal--Time/Web ServicesTime/Web ServicesZ

L Engine, always-on non-stop sessions, JMSconnectivity, and real-time Web Services provider

Data CleansingData CleansingName and address cleansing functionality, includingdirectories forUS and certain international countries

PartitioningPartitioningData smart parallelism, pipeline and data parallelism,partitioning

Server engine, metadata repository, unlimited designers,workflow scheduler, all APIs and SDKs, unlimited XML andflat file sourcing and targeting, object export to XML file,LDAP authentication, role-based object-level security,metadata reporter, centralized monitoring

Server group management, automatic workflow distributionacross multiple heterogeneous serversServer GridServer Grid

Version control, deployment groups, configurationmanagement, automatic promotion

TeamTeam--Based DevelopmentBased Development

Virtual Classes

Watch for short web-based virtualclasses on most PowerCenter


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options and XML support

Data Access PowerExchange

Provides access to all critical enterprise data systems,

including mainframe, midrange relational databases,and file-based systems


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and file based systems

Offers batch, change capture and real-time options

PowerExchange 5.2 provides tight integration withPowerCenter 7.1.1 through the PowerExchange Clientfor PowerCenter

Supporting VSAM, IMS, DB2 (OS/390, AS/400), Oracle, ODBC

Data Access PowerCenter Connect

PowerCenter Connect options are currently available for:

Transactional Applications Real-time Services


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Transactional Applications Hyperion Essbase PeopleSoft SAP R/3

SAP BW SAS Siebel

Real time Services HTTP JMS MSMQ

MQSeries TIBCOWebMethodsWeb Services

PowerCenter Connect SDK

Allows development of new PowerCenter Connect productsAvailable on the Informatica Developer Network


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informatica official

Documents

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