The document outlines methods for creating target definitions in Informatica, including importing data from relational databases, flat files, and XML. It describes various types of transformations such as active and passive transformations, their functions, and examples including filter transformations, aggregators, and joiners. Additionally, it details the properties and usage of transformation ports and emphasizes optimizing performance by placing filter transformations close to data sources.

1. Informatica :
• TARGET OBJECTS
• TARGET ODBC CONNECTION CREATION
• TARGT IMPORT
• MANUAL TARGET CRETION
• AUTOMATIC TARET CRATION
• TRANSFORMATIONS
• DIFFERENT TYPES OF TRANSFORMATIONS
• FILTER TRANSFORMATION
• SECOND MAPPING
• CREATE RELATIONAL CONNECTION
• SOURCE QUALIFIER OVERVIEW

3. Creating Target Definitions
Methods of creating Target Definitions
 Import from relational database ( Table)
 Import from Flat File
 Import from XML object
 Create automatically from a source definition
 Create manually (flat file or relational database)

4. Creating Target Definition
Methods of creating Target Definitions
 Import from Database
 Import from an Flat file
 Manual Creation
 Automatic Creation
Repository
Relational Flat file COBOL file
XML file
Warehouse
Designer

5. 2. Add desired columns
Manual Target Creation
1. Create empty definition
3. Finished target definition

6. Create tables that do not already exist in target database
 Connect - connect to the target database
 Generate SQL file - create DDL in a script file
 Edit SQL file - modify DDL script as needed
 Execute SQL file - create physical tables in target database
Use Preview Data to verify
the results (right mouse click
on object)
Creating Physical Tables

7. What is a transformation?
 A transformation is repository object that generates, modifies and/or
passes data to other repository object.
 The Designer provides a set of transformations that perform specific
functions.
 Transformations in a mapping represent the operations the Integration
Service performs on data.
 Data passes into and out of transformations through ports that you
connect in a Mapping or Mapplet.
 Transformations can be active or passive and Connected or
unconnected.

8. Transformation Types
 Active Transformation
 The number of rows that pass through this transformation change, i.e.
Number of rows in the transformation may or may not be equal to
number of rows out of the transformation
 Example – Number of rows coming in Filter transformation may be 10.
But depending on condition, number of rows out of Filter can be
anywhere between Zero and 10
 Passive Transformation
 The number of rows into the transformation is always equal to
number of rows out of the transformation
 Example – Number of rows into Expression is always equal to number
of rows out of the transformation

9. Transformation Types
 Connected Transformation
 The transformation is which connected to other Transformation in the
data flow Mapping.
 Example – All The transformations are connected transformations.
 Unconnected Transformation
 An unconnected transformation is not connected to other
transformations in the mapping. An unconnected transformation is
called within another transformation, and returns a value to that
transformation.
 Example – Lookup and Stored Procedure Transformation can be used
as unconnected Transformations.

10. Transformation Types

11. Transformation Type Description
Aggregator Active & Connected Performs aggregate calculations.
Expression Passive & Connected Calculates a value.
Filter Active & Connected Filters data.
Joiner Active & Connected Joins data from different databases or flat file
systems.
Rank Active & Connected Limits records to a top or bottom range.
Router Active & Connected Routes data into multiple transformations based on
group conditions.
Sequence Generator Passive & Connected Generates primary keys.
Sorter Active & Connected Sorts data based on a sort key.
Source Qualifier Active & Connected Represents the rows that the Integration Service
reads from a relational or flat file source when it
runs a session.
Lookup Active or Passive & Connected
or Unconnected
Look up and return data from a flat file, relational
table, view, or synonym.
Transformations

12. Transformation Type Description
Stored Procedure Passive & Connected or
Unconnected
Calls a stored procedure.
Transaction Control Active & Connected Defines commit and rollback transactions.
Union Active & Connected Merges data from different databases or flat file
systems.
Update Strategy Active & Connected Determines whether to insert, delete, update, or reject
rows.
XML Generator Active & Connected Reads data from one or more input ports and outputs
XML through a single output port.
XML Parser Active & Connected Reads XML from one input port and outputs data to
one or more output ports.
XML Source Qualifier Active & Connected Represents the rows that the Integration Service reads
from an XML source when it runs a session.
Normalizer Active & Connected Source qualifier for COBOL sources. Can also use in the
pipeline to normalize data from relational or flat file
sources.
Transformations

13. Transformation Views
A transformation has
three views:
 Iconized - shows the
transformation in relation
to the rest of the mapping
 Normal - shows the flow
of data through the
transformation
 Edit - shows
transformation ports and
properties; allows editing

14. Transformation Normal View
Shows data flow through the transformation
Data passes
through
I/O ports
unchanged
 DATE_ENTERED passes in to the transformation
through an input port
 It is used in the MONTH port to extract the month
 The month is passed through MONTH output port

15. Transformation Edit Mode
Allows users with folder “write” permissions to change or
create transformation ports and properties
Switch between
transformations
Define transformation level
properties
Define port level handling
Enter comments
Make reusable

16. Transformations - Properties
 Port Name
Copied ports will inherit the name of contributing port
Copied ports with the same name will be appended with a number
Types Of Ports:
Input: Data Input from previous stage.
Output: Data Output to the next stage.
Lookup: Port to be used to compare Data.
Return: The Port (Value) returned from Looking up.
Variable: The port that stores value temporarily.
 Data types
Transformations use internal data types.
Data types of input ports must be compatible with data types of the
feeding output port.
 Port Default values - can be set to handle nulls and errors
 Description - can enter port comments

17. Filter Transformation

18. Filter Transformation
 It provides the means for filtering rows in a mapping.
 All ports in a Filter transformation are input/output.
 Only rows that meet the condition pass through it.
 Cannot concatenate ports from more than one transformation into the Filter transformation.
 To maximize session performance, include the Filter transformation as close to the sources
in the mapping as possible.
 Does not allow setting output default values.
!! Filter should always be used as close to the Source, so that the Load of
data carried ahead is decreased at / or near to the Source Itself.

19. Ports
• All input / output
Specify a Filter condition
Usage
• Filter rows from
input flow
Drops rows conditionally
Filter Transformation

20. • SALARY > 30000
• SALARY > 30000 AND SALARY < 100000
• IIF(ISNULL(FIRST_NAME),FALSE,TRUE)
• To filter rows containing null values or spaces, use
the ISNULL and IS_SPACES functions to test the
value of the port. For example, if you want to filter
out rows that contain NULL value in the
FIRST_NAME port, use the following condition:
• IIF(ISNULL(FIRST_NAME),FALSE,TRUE)This
condition states that if the FIRST_NAME port is
NULL, the return value is FALSE and the row should
be discarded. Otherwise, the row passes through to
the next transformation
Filter Transformation Examples