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Differences between Advanced External Procedure and External Procedure Transformations:



1) External Procedure returns single value,

whereas

Advanced External Procedure returns multiple values.


2) External Procedure supports COM and Informatica procedures

whereas

Advanced External Procedure supports only Informatica Procedures.

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External Procedure Transformation


External Procedure transformation is an Active and Connected/UnConnected transformations. Sometimes, the standard transformations such as

Expression transformation may not provide the functionality that you want.

In such cases External procedure is useful to develop complex functions within a dynamic link library (DLL) or UNIX shared library, instead of creating the necessary Expression transformations in a mapping.

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Advanced External Procedure Transformation


Advanced External Procedure transformation is an Active and Connected transformation.

It operates in conjunction with procedures, which are created outside of the Designer interface to extend PowerCenter/PowerMart functionality.

It is useful in creating external transformation applications, such as sorting and aggregation, which require all input rows to be processed before emitting any output rows.

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XML Source Qualifier Transformation

XML Source Qualifier is a Passive and Connected transformation.

XML Source Qualifier is used only with an XML source definition.

It represents the data elements that the Informatica Server reads when it executes a session with XML sources.

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Update Strategy Transformation

Update strategy transformation is an Active and Connected transformation.

It is used to update data in target table, either to maintain history of data or recent changes.

You can specify how to treat source rows in table, insert, update, delete or data driven.

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Source Qualifier Transformation

Source Qualifier transformation is an Active and Connected transformation. When adding a relational or a flat file source definition to a mapping, it is must to connect it to a Source Qualifier transformation.


The Source Qualifier performs the various tasks such as

Overriding Default SQL query,

Filtering records;

join data from two or more tables etc.

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Sorter Transformation

Sorter transformation is a Connected and an Active transformation.

It allows to sort data either in ascending or descending order according to a specified field.

Also used to configure for case-sensitive sorting, and specify whether the output rows should be distinct.

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Stored Procedure Transformation

Stored Procedure transformation is a Passive and Connected & UnConnected transformation. It is useful to automate time-consuming tasks and it is also used in error handling, to drop and recreate indexes and to determine the space in database, a specialized calculation etc.


The stored procedure must exist in the database before creating a Stored Procedure transformation, and the stored procedure can exist in a source, target, or any database with a valid connection to the Informatica Server. Stored Procedure is an executable script with SQL statements and control statements, user-defined variables and conditional statements.

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Sequence Generator Transformation

Sequence Generator transformation is a Passive and Connected transformation. It is used to create unique primary key values or cycle through a sequential range of numbers or to replace missing keys.


It has two output ports to connect transformations. By default it has two fields CURRVAL and NEXTVAL(You cannot add ports to this transformation).


NEXTVAL port generates a sequence of numbers by connecting it to a transformation or target. CURRVAL is the NEXTVAL value plus one or NEXTVAL plus the Increment By value.

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Router Transformation

Router is an Active and Connected transformation. It is similar to filter transformation.

The only difference is, filter transformation drops the data that do not meet the condition whereas router has an option to capture the data that do not meet the condition. It is useful to test multiple conditions.

It has input, output and default groups.

For example, if we want to filter data like where State=Michigan, State=California, State=New York and all other States. It’s easy to route data to different tables.

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Rank Transformation

Rank transformation is an Active and Connected transformation.

It is used to select the top or bottom rank of data.

For example,

To select top 10 Regions where the sales volume was very high

or

To select 10 lowest priced products.

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Normalizer Transformation


Normalizer Transformation is an Active and Connected transformation.

It is used mainly with COBOL sources where most of the time data is stored in de-normalized format.

Also, Normalizer transformation can be used to create multiple rows from a single row of data.

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Lookup transformation is Passive and it can be both Connected and UnConnected as well. It is used to look up data in a relational table, view, or synonym. Lookup definition can be imported either from source or from target tables.

For example, if we want to retrieve all the sales of a product with an ID 10 and assume that the sales data resides in another table. Here instead of using the sales table as one more source, use Lookup transformation to lookup the data for the product, with ID 10 in sales table.


Connected lookup receives input values directly from mapping pipeline whereas

UnConnected lookup receives values from: LKP expression from another transformation.


Connected lookup returns multiple columns from the same row whereas

UnConnected lookup has one return port and returns one column from each row.


Connected lookup supports user-defined default values whereas

UnConnected lookup does not support user defined values.

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Joiner Transformation


Joiner Transformation is an Active and Connected transformation. This can be used to join two sources coming from two different locations or from same location. For example, 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.

In order to join two sources, there must be atleast one matching port. at least one matching port. While joining two sources it is a must to specify one source as master and the other as detail.


The Joiner transformation supports the following types of joins:


1)Normal

2)Master Outer

3)Detail Outer

4)Full Outer


Normal join discards all the rows of data from the master and detail source that do not match, based on the condition.


Master outer join discards all the unmatched rows from the 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. It discards the unmatched rows from the detail source.


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

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Filter Transformation

Filter transformation is an Active and Connected transformation.

This can be used to filter rows in a mapping that do not meet the condition.

For example,

To know all the employees who are working in Department 10 or

To find out the products that falls between the rate category $500 and $1000.

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Expression Transformation

Expression transformation is a Passive and Connected transformation.

This can be used to calculate values in a single row before writing to the target.

For example, to calculate discount of each product

or to concatenate first and last names

or to convert date to a string field.

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Aggregator Transformation

Aggregator transformation is an Active and Connected transformation.

This transformation is useful to perform calculations such as averages and sums (mainly to perform calculations on multiple rows or groups).

For example, to calculate total of daily sales or to calculate average of monthly or yearly sales. Aggregate functions such as AVG, FIRST, COUNT, PERCENTILE, MAX, SUM etc. can be used in aggregate transformation.

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Processing of incremental aggregation


The first time u run an incremental aggregation session the power center server process the entire source.At the end of the session the power center server stores aggregate data from the session runs in two files, the index file and the data file .The power center server creates the files in a local directory.

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Informatica - Transformations

In Informatica, Transformations help to transform the source data according to the requirements of target system and it ensures the quality of the data being loaded into target.
Transformations are of two types: Active and Passive.


Active Transformation

An active transformation can change the number of rows that pass through it from source to target i.e it eliminates rows that do not meet the condition in transformation.


Passive Transformation

A passive transformation does not change the number of rows that pass through it i.e it passes all rows through the transformation.

Transformations can be Connected or UnConnected.


Connected Transformation

Connected transformation is connected to other transformations or directly to target table in the mapping.


UnConnected Transformation

An unconnected transformation is not connected to other transformations in the mapping. It is called within another transformation, and returns a value to that transformation.


Following are the list of Transformations available in Informatica:

Aggregator Transformation

Expression Transformation

Filter Transformation

Joiner Transformation

Lookup Transformation

Normalizer Transformation

Rank Transformation

Router Transformation


Sequence Generator Transformation

Stored Procedure Transformation

Sorter Transformation

Update Strategy Transformation

XML Source Qualifier Transformation

Advanced External Procedure Transformation

External Transformation


In the following pages, we will explain all the above Informatica Transformations and their significances in the ETL process in detail.

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Guidelines to work with Informatica Power Center

• Repository: This is where all the metadata information is stored in the Informatica suite. The Power Center Client and the Repository Server would access this repository to retrieve, store and manage metadata.

• Power Center Client: Informatica client is used for managing users, identifiying source and target systems definitions, creating mapping and mapplets, creating sessions and run workflows etc.

• Repository Server: This repository server takes care of all the connections between the repository and the Power Center Client.

• Power Center Server: Power Center server does the extraction from source and then loading data into targets.

• Designer: Source Analyzer, Mapping Designer and Warehouse Designer are tools reside within the Designer wizard. Source Analyzer is used for extracting metadata from source systems.
  Mapping Designer is used to create mapping between sources and targets. Mapping is a pictorial representation about the flow of data from source to target.
  Warehouse Designer is used for extracting metadata from target systems or metadata can be created in the Designer itself.

• Data Cleansing: The PowerCenter's data cleansing technology improves data quality by validating, correctly naming and standardization of address data. A person's address may not be same in all source systems because of typos and postal code, city name may not match with address. These errors can be corrected by using data cleansing process and standardized data can be loaded in target systems (data warehouse).

• Transformation: Transformations help to transform the source data according to the requirements of target system. Sorting, Filtering, Aggregation, Joining are some of the examples of transformation. Transformations ensure the quality of the data being loaded into target and this is done during the mapping process from source to target.

• Workflow Manager: Workflow helps to load the data from source to target in a sequential manner. For example, if the fact tables are loaded before the lookup tables, then the target system will pop up an error message since the fact table is violating the foreign key validation. To avoid this, workflows can be created to ensure the correct flow of data from source to target.

• Workflow Monitor: This monitor is helpful in monitoring and tracking the workflows created in each Power Center Server.

• Power Center Connect: This component helps to extract data and metadata from ERP systems like IBM's MQSeries, Peoplesoft, SAP, Siebel etc. and other third party applications.

• Power Center Exchange: This component helps to extract data and metadata from ERP systems like IBM's MQSeries, Peoplesoft, SAP, Siebel etc. and other third party applications.

Informatica

Informatica is a powerful ETL tool from Informatica Corporation, a leading provider of enterprise data integration software and ETL softwares.

The important Informatica Components are:

• Power Exchange

• Power Center

• Power Center Connect

• Power Exchange

• Power Channel

• Metadata Exchange

• Power Analyzer

• Super Glue

In Informatica, all the Metadata information about source systems, target systems and transformations are stored in the Informatica repository. Informatica's Power Center Client and Repository Server access this repository to store and retrieve metadata.

Source and Target:

Consider a Bank that has got many branches throughout the world. In each branch data may be stored in different source systems like oracle, sql server, terradata, etc.

When the Bank decides to integrate its data from several sources for its management decisions, it may choose one or more systems like oracle, sql server, terradata, etc. as its data warehouse target. Many organisations prefer Informatica to do that ETL process, because Informatica is more powerful in designing and building data warehouses. It can connect to several sources and targets to extract meta data from sources and targets, transform and load the data into target systems.