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© 2006 Cisco Systems, Inc. All rights reserved. Cisco ConfidentialPresentation_ID 1

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Chockalingam Ramiah(Chocks)

Informatica Quickstart



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Informatica - Architecture

Sources

Standard: RDBMS, Flat Files,XML, ODBC

Applications: SAP R/3, SAP BW,PeopleSoft, Siebel, JD Edwards,

i2

EAI: MQ Series, Tibco, JMS, WebServices

Legacy: Mainframes (DB2,VSAM, IMS, IDMS,

Adabas)AS400 (DB2, Flat File)

Remote Sources

Targets

Standard: RDBMS, Flat Files,XML, ODBC

Applications: SAP R/3, SAP BW,PeopleSoft, Siebel, JD Edwards,

i2

EAI: MQ Series, Tibco, JMS, WebServices

Legacy: Mainframes(DB2)AS400 (DB2)

Remote Targets




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Client Tools

Tool Description

Designer Define transformation process,known as mapping

Workflow Manager Define run-time properties for amapping, known as sessions

Workflow Monitor Monitor execution of sessions

Repository Manager Manage repository, useful for

administratorsMetadata Reporter Report Metadata




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Repository

Data inventory for - Data related to mappings, sources, targets

Single location where all the metadata stored for applications

Client tools and Informatica server fetch data

Backend of Informatica




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Types of repositories

Name Description

Standalone 1 Functions individually and this is unrelated

to any other repositories

Global 1 Centralized repository in a domain2 Can contain shared objects across the

repositories in a domain3 Objects are shared through global shortcuts

Local 1 Local repository is within a domain2 Not a global repository3 Local repository can connect to a global

repository using global shortcuts and canuse objects in it’s shared folders.

Versioned 1 Either be local or global repository2 Allows version control for the repository3 Can store multiple copies/versions of an

object.4 Allows to efficiently develop, test and deploy

metadata in the production environment.




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Server

All the executions will happen

Physical connections to sources/targets are made

Fetches data

Transformations mentioned in the mapping are applied

Loads the data in the target system


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Transformation

Repository object that generates, modifies, or passesdata

Designer provides a set of transformations that perform

specific functions

Aggregator transformation performs calculations ongroups of data

There are ~31 transformations supported in Informatica



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Transformation Types

Name Description

Active 1 Changes the number of rows that pass thru2 Changes the transaction boundary3 Changes the row type

SampleFilter, Transaction Control and Update Strategyare active transformations

Passive 1 No change in the number of rows that pass

through2 Maintains the transaction boundary3 Maintains the row type



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Transformations mapped to Data Flow

Name Description

Connected 1 Connected to other transformations2 or directly to target table in the mapping

Unconnected 1 An unconnected transformation is notconnected to other transformations in themapping.

2 Called within another transformation3 Returns a value to calling transformation



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Transformations

1 Aggregator

2 Application Source Qualifier

3 Custom

4 Data Masking

5 Expression

6 External Procedure

7 Filter

8 HTTP

9 Input

10 Java

11 Joiner

12 Lookup

13 Normalizer

14 Output

15 Rank

16Reusable

17Router18Sequence Generator19Sorter20Source Qualifier21SQL22XML Source Qualifier23Advanced External Procedure

24External25Stored Procedure26Transaction Control Transaction27Union28Unstructured Data29Update Strategy30XML Generator31XML Parser



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Aggregator Performs aggregate funtions like average, sum, count etc.

on multiple rows or groups. The Integration Service performs these calculations as it

reads and stores data group and row data in anaggregate cache. It is an Active & Connected

transformation. Aggregator transformation has following ports State,

State_Count, Previous_State and State_Counter.Components: Aggregate Cache, Aggregate Expression,

Group by port, Sorted input. VARIANCE



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Aggregator Vs Expression

Expression transformation permits you to perform

calculations row by row basis only. In Aggregator you canperform calculations on groups

Aggregate Expressions: are allowed only in aggregate

transformations. can include conditional clauses and non-aggregate functions. can also include one aggregatefunction nested into another aggregate function.Aggregate Functions: AVG, COUNT, FIRST, LAST, MAX,

MEDIAN, MIN, PERCENTILE, STDDEV, SUM,



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Appln Source Qualifier

Represents the rows that the Integration Service reads

from an application, such as an ERP source, when it runsa session.

It is an Active & Connected transformation.



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Custom

Develop the transformation logic in a procedure

Some of the PowerCenter transformations are built usingthe Custom transformation

Rules that apply to Custom transformations, such asblocking rules, also apply to transformations built using

Custom transformations



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Custom

PowerCenter provides two sets of functions called

generated and API functions. The Integration Service uses generated functions to

interface with the procedure.

When you create a Custom transformation and generate

the source code files, the Designer includes thegenerated functions in the files.

Use the API functions in the procedure code to developthe transformation logic.



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Custom Vs External Procedure

In Custom transformation, input and output functions

occur separately. The Integration Service passes the input data to the

procedure using an input function.

The output function is a separate function that you must

enter in the procedure code to pass output data to theIntegration Service.

In contrast, in the External Procedure transformation, anexternal procedure function does both input and output,

and its parameters consist of all the ports of thetransformation.



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Data Masking

Passive & Connected. Used to change sensitive

production data to realistic test data for non productionenvironments

Creates masked data for development, testing, trainingand data mining

Data relationship and referential integrity are maintainedin the masked data

google_protectAndRun("ads_core.google_render_ad",google_handleError, google_render_ad); For example: It

returns masked value that has a realistic format for SSN,Credit card number, birthdate, phone number, etc. But isnot a valid value.



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Masking Types

Key Masking

Random Masking

Expression Masking

Special Mask format

Default is no masking.



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Expression

Passive & Connected. Used to perform non-aggregate

functions, i.e to calculate values in a single row. Example:to calculate discount of each product or to concatenatefirst and last names or to convert date to a string field.

You can create an Expression transformation in the

Transformation Developer or the Mapping Designer.Components: Transformation, Ports, Properties,Metadata Extensions.



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External Procedure

Passive & Connected or Unconnected.

Works with procedures you create outside of theDesigner interface to extend PowerCenter functionality

You can create complex functions within a DLL or in theCOM layer of windows and bind it to external procedure

transformation

To get this kind of extensibility, use the TransformationExchange (TX) dynamic invocation interface built intoPowerCenter



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Filter

Active & Connected

Allows rows that meet the specified filter condition andremoves the rows that do not meet the condition

For example, to find all the employees who are working inNewYork or to find out all the faculty member teaching

Chemistry in a state

The input ports for the filter must come from a singletransformation. You cannot concatenate ports from morethan one transformation into the Filter transformation.

Components: Transformation, Ports, Properties,Metadata Extensions.



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HTTP

Passive & Connected

Allows you to connect to an HTTP server to use itsservices and applications

With an HTTP transformation, the Integration Serviceconnects to the HTTP server, and issues a request to

retrieves data or posts data to the target or downstreamtransformation in the mapping.google_protectAndRun("ads_core.google_render_ad",google_handleError, google_render_ad); Authentication

types: Basic, Digest and NTLM. Examples: GET, POSTand SIMPLE POST.



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Java

Active or Passive & Connected

It provides a simple native programming interface todefine transformation functionality with the Javaprogramming language

You can use the Java transformation to quickly define

simple or moderately complex transformation functionalitywithout advanced knowledge of the Java programminglanguage or an external Java development environment



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Joiner

Active & Connected

Used to join data from two related heterogeneoussources residing in different locations or to join data fromthe same source

In order to join two sources, there must be at least one or

more pairs of matching column between the sources anda must to specify one source as master and the other asdetail

E.g. to join a flat file and a relational source or to join two

flat files or to join a relational source and a XML source.The Joiner transformation supports the following types of

joins:




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Types of Joiner

Normal join discards all the rows of data from the master

and detail source that do not match, based on thecondition.

Master outer join discards all the unmatched rows fromthe master source and keeps all the rows from the detail

source and the matching rows from the master source. Detail outer join keeps all rows of data from the master

source and the matching rows from the detail source. Itdiscards the unmatched rows from the detail source.

Full outer join keeps all rows of data from both themaster and detail sources.




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Lookup

Passive & Connected or UnConnected

It is used to look up data in a flat file, relational table,view, or synonym

It compares lookup transformation ports (input ports) tothe source column values based on the lookup condition

Later returned values can be passed to othertransformations

You can create a lookup definition from a source qualifier

and can also use multiple Lookup transformations in amapping.




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Types of Lookup

1) Relational or flat file lookup

2) Pipeline lookup

3) Cached or uncached lookup

1) Connected or unconnected lookup




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Executing PL/SQL from transformation

Stored Procedure (SP) transformation can be used toexecute PL/SQL Scripts.

In SP Transformation PL/SQL procedure name can be

specified. Whenever the session is executed, the sessionwill call the pl/sql procedure





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