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INFORMATICA INFORMATICA POWERCENTER 8.1.0 POWERCENTER 8.1.0 DESIGNER

INFORMATICA POWERCENTER 8.1.0 INFORMATICA POWERCENTER 8.1.0 DESIGNER

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Page 1: INFORMATICA POWERCENTER 8.1.0 INFORMATICA POWERCENTER 8.1.0 DESIGNER

INFORMATICA INFORMATICA POWERCENTER 8.1.0POWERCENTER 8.1.0

DESIGNER

Page 2: INFORMATICA POWERCENTER 8.1.0 INFORMATICA POWERCENTER 8.1.0 DESIGNER

2integration * intelligence * insight

ContentContent

WORKING WITH POWERCENTER 8 DESIGNER

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Designer OverviewDesigner Overview

Designer

Designer is used to create mappings that contain transformation instructions for the Integration Service. The Designer has the following tools that we use to analyze sources, design target schemas, and build source-to-target mappings.

Source Analyzer

It imports or creates source definitions. Target Designer

It imports or creates target definitions. Transformation Developer

Develop transformations to use in mappings. we can also develop user-defined functions to use in expressions.

Mapplets Designer

It Creates sets of transformations to use in mappings. Mapping Designer

It Creates mappings that the Integration Service uses to extract, transform, and load data.

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Designer OverviewDesigner Overview

The following things are displayed in Designer

Navigator It connect to repositories, and open folders within the Navigator. we can also copy objects and create shortcuts within the Navigator.

WorkspaceIt opens different tools in this window to create and edit repository objects, such as sources, targets, mapplets, transformations, and mappings.

Output View details about tasks you perform, such as saving your work or validating a mapping.

Designer Windows

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Designer OverviewDesigner Overview

Status bar It Displays the status of the operation you perform.

Overview An optional window to simplify viewing a workspace that contains a large mapping or multiple objects. Outlines the visible area in the workspace and highlights selected objects in color.

Instance dataView transformation data while you run the Debugger to debug a mapping.

Target dataView target data while you run the Debugger to debug a mapping.

Designer Windows

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Designer OverviewDesigner Overview

Informatica PowerCenter 8 can access the following data sources and load the data into the following targets .

Sources

Relational• Oracle• Sybase ASE• Informix• IBM DB2• Microsoft SQL Server• Teradata

File • Flat file• COBOL file• XML file• web log

Application• Hyperion Essbase• IBM MQSeries• IBM DB2 OLAP Server• JMS• Microsoft Message Queue

Mainframe • Adabas• Datacom• IBM DB2 OS/390• IBM DB2 OS/400

Other Microsoft Excel Microsoft Access External web services

• PeopleSoft• SAP NetWeaver• SAS• Siebel• TIBCO• WebMethods

• IDMS • IDMS-X• IMS• VSAM

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Designer OverviewDesigner Overview

Targets

Relational• Oracle• Sybase ASE• Informix• IBM DB2• Microsoft SQL Server• Teradata

File • Flat file• XML file

Application• Hyperion Essbase• IBM MQSeries• IBM DB2 OLAP Server• JMS• Microsoft Message Queue

Mainframe • IBM DB2 OS/390• IBM DB2 OS/400

Other Microsoft Access External web services

• MY SAP• PeopleSoft EPM• SAP BW• SAS• Siebel• TIBCO• WebMethods

• VSAM

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About TransformationAbout Transformation

The transfer of data is called transformation.

A transformation is a repository object that generates, modifies, or passes data.

We configure logic in a transformation that the Integration Service uses to transform data.

The Designer provides a set of transformations that perform specific functions.

Transformations in a mapping represent the operations the Integration Service performs on the data.

Data passes into and out of transformations through ports that we link in a mapping or mapplet.

Transformations can be Active or Passive.

An active transformation can change the number of rows that pass through it.

A passive transformation does not change the number of rows that pass through it.

Transformations can be connected to the data flow.

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.

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About TransformationAbout Transformation

Tasks to incorporate a transformation into a mapping

Create the transformation

Configure the transformation

Link the transformation to other transformations and target definitions

Mapping Designer

Transformation Developer

Mapplet Designer

Designer TransformationsAggregator - to do things like "group by".Expression - to use various expressions.

Filter - to filter data with single condition.

Joiner - to make joins between separate databases, file, ODBC sources.

Lookup - to create local copy of the data.

Normalizer - to transform denormalized data into normalized data.

Rank - to select only top (or bottom) ranked data.

Sequence Generator - to generate unique IDs for target tables.

Source Qualifier - to filter sources (SQL, select distinct, join, etc.)

Stored Procedure - to run stored procedures in the database - and capture their returned values.

Update Strategy - to flag records in target for insert, delete, update (defined inside a mapping).

Router - same as filter but with multiple conditions

Java Transformation- It provides a simple native programming interface to define transformation functionality with the Java programming language.

Reusable transformation- is a transformation that can be used in multiple mappings

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Types Of TransformationTypes Of Transformation

Active Transformation

Filter

Router

Update Strategy

Aggregator

Sorter

Rank

Joiner

Normalizer

Passive transformations

Sequence GeneratorStored ProcedureExpressionLookup

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Aggregator TransformationAggregator Transformation

The Aggregator is an active transformation. The Aggregator transformation allow us to perform aggregate calculations, such as averages and

sums. The Aggregator transformation is unlike the Expression transformation, in that we can use the

Aggregator transformation to perform calculations on groups. The Expression transformation permit us to perform calculations on a row-by-row basis only. We can use conditional clauses to filter rows, providing more flexibility than SQL language. The Integration Services performs aggregate calculations as it reads, and stores necessary

data group and row data in an aggregate cache.Components of the Aggregator Transformation Aggregate expression Group by port Sorted input Aggregate cache

Aggregate Expression An aggregate expression can include conditional clauses and non-aggregate functions. It can

also include one aggregate function nested within another aggregate function, such as. MAX( COUNT( ITEM )

Aggregate Functions The aggregate functions can be used within an Aggregator transformation. We can nest one aggregate function within another aggregate function. AVG COUNT

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Aggregator TransformationAggregator Transformation

Aggregate Functions

FIRST LAST MEDIAN MAX MIN STDDEV PERCENTILE SUM VARIANCE

Conditional Clauses

We use conditional clauses in the aggregate expression to reduce the number of rows used in the aggregation. The conditional clause can be any clause that evaluates to TRUE or FALSE.

Null Values in Aggregate Functions

When we configure the Integration Service, we can choose how we want the Integration Service to handle null values in aggregate functions. We can choose to treat null values in aggregate functions as NULL or zero. By default, the Integration Service treats null values as NULL in aggregate functions.

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Creating Aggregator TransformationCreating Aggregator Transformation

In the Mapping Designer, click Transformation > Create. Select the Aggregator transformation. Enter a name for the Aggregator, click Create. Then click Done.

The Designer creates the Aggregator transformation. Drag the ports to the Aggregator transformation. The Designer creates input/output ports for each port we

include. Double-click the title bar of the transformation to open the

Edit Transformations dialog box . Select the Ports tab. Click the group by option for each column you want the

Aggregator to use in creating groups. Click Add and enter a name and data type for the aggregate

expression port. Make the port an output port by clearing Input (I). Click in the right corner of the Expression field to open the Expression Editor. Enter the aggregate expression, click Validate, and click OK.

Add default values for specific ports. Select the Properties tab. Enter settings as necessary. Click OK. Choose Repository-Save.

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Expression TransformationExpression Transformation

We can use the Expression transformation to calculate values in a single row before we write to the target

We can use the Expression transformation to test conditional statements To perform calculations involving multiple rows, such as sums or averages we can use

aggregator transformation We can use the Expression transformation to perform any non-aggregate calculations

Creating an Expression Transformation

In the Mapping Designer, click Transformation > Create. Select the Expression transformation and click OK.

The naming convention for Expression transformations is EXP_TransformationName

Create the input ports If we have the input transformation available, we can

select Link Columns from the Layout menu and then drag each port used in the calculation into the Expression transformation or we can open the transformation and create each port manually.

Repeat the previous step for each input port we want to add to the expression

Create the output ports we need

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Expression TransformationExpression Transformation

Setting Expression in Expression Transformation

Enter the expression in the Expression Editor we have disable to in port.

Check the expression syntax by clicking Validate.

Connect to Next Transformation

Connect the output ports to the next transformation or target.

Select a Tracing Level on the Properties Tab

Select a tracing level on the Properties tab to determine the amount of transaction detail reported in the session log file.

Choose Repository-Save.

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Filter TransformationFilter Transformation

A Filter transformation is an Active Transformation. We can filter rows in a mapping with Filter transformation. We pass all the rows from a source transformation through the Filter transformation and

then enter a filter condition for the transformation. All ports in a Filter transformation are input/output, and only rows that meet the condition

pass through the Filter transformation.

Creating a Filter Transformation

In the Mapping Designer, click Transformation > Create. Select the Filter transformation. Enter a name, and click OK.

The naming convention for Filter transformations is FIL_TransformationName.

Select and drag all the ports from a source qualifier or other transformation to add them to the Filter transformation.

After we select and drag ports, copies of these ports appear in the Filter transformation. Each column has both an input and an output port.

Double-click the title bar of the filter transformation to edit transformation properties.

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Filter TransformationFilter Transformation

Click the Value section of the condition, and then click the Open button. The Expression Editor appears. Enter the filter condition we want to apply. Use values from one of the input ports in the transformation as part of this condition

However, we can also use values from output ports in other transformations. We may have to fix syntax errors before continuing. Click OK. Select the Tracing Level, and click OK to return to the Mapping Designer. Choose Repository-Save.

Filter Transformation Tips

Use the Filter transformation early in the mapping. Use the Source Qualifier transformation to filter.

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Joiner TransformationJoiner Transformation

A Joiner transformation is an active transformation. Joiner transformation is used to join source data from two related heterogeneous sources

residing in different locations or file systems. We can also join data from the same source. The Joiner transformation joins sources with at least one matching column. The Joiner transformation uses a condition that matches one or more pairs of columns

between the two sources.

We can use the following sources

Two relational tables existing in separate databases. Two flat files in potentially different file systems. Two different ODBC sources. A relational table and an XML source. A relational table and a flat file source. Two instances of the same XML source.

Creating a Joiner Transformation

In the Mapping Designer, click Transformation > Create. Select the Joiner transformation. Enter a name, and click OK.

The naming convention for Joiner transformations is JNR_TransformationName.

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Joiner TransformationJoiner Transformation

Drag all the input/output ports from the first source into the Joiner transformation. The Designer creates input/output ports for the source fields in the Joiner transformation as

detail fields by default. We can edit this property later. Select and drag all the input/output ports from the second source into the Joiner

transformation. The Designer configures the second set of source fields and master fields by default.

Edit Transformation Double-click the title bar of the Joiner

transformation to open the Edit Transformations dialog box.

Select the port tab. Add default values for specific ports

as necessary.Setting the Condition Select the Condition tab and set the

condition. Click the Add button to add a

condition. Click the Properties tab and configure

properties for the transformation. Click OK .

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Joiner TransformationJoiner Transformation

Defining the Join Type

Join is a relational operator that combines data from multiple tables into a single result set. We define the join type on the Properties tab in the transformation. The Joiner transformation supports the following types of joins.

• Normal • Master Outer• Detail Outer• Full Outer

Joiner Transformation Tips

Perform joins in a database when possible. Join sorted data when possible. For an unsorted Joiner transformation, designate the source with fewer rows as the master

source. For a sorted Joiner transformation, designate the source with fewer duplicate key values as

the master source.

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Lookup Transformation Lookup Transformation

A Lookup transformation is a passive transformation.

Use a Lookup transformation in a mapping to look up data in a flat file or a relational table, view, or synonym.

We can import a lookup definition from any flat file or relational database to which both the PowerCenter Client and Integration Service can connect.

We can Use multiple Lookup transformations in a mapping.

The Integration Service queries the lookup source based on the lookup ports in the transformation.

It compares Lookup transformation port values to lookup source column values based on the lookup condition.

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Connected Lookup

Receives input values directly from the pipeline

Cache includes all lookup columns used in the mapping

If there is no match for the lookup condition, it returns thedefault value for all output ports

Pass multiple output values to another transformation

Supports user-defined default values

Types of Lookup Transformation

Unconnected Lookup

Receives input values from other transformation calling: LKP expression

You can use a static cache

Cache includes all lookup/output ports in the lookup condition

If there is no match for the lookup condition, returns null

Pass one output value to another transformation

Does not support user-defined default values

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Lookup TransformationLookup Transformation

Tasks Of Lookup Transformations

Get a related value.

Perform a calculation.

Update slowly changing dimension tables.

Connected or unconnected.

Cached or uncached.

Lookup ComponentsWe have to define the following components when we configure a Lookup transformation in a mapping.

Lookup source

• Ports

• Properties

• Condition

• Metadata extensions

Edit Transformation

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Lookup TransformationLookup Transformation

Creating a Lookup Transformation In the Mapping Designer, click

Transformation > Create. Select the Lookup transformation. Enter a name for the transformation and Click OK. The naming convention for Lookup transformation is LKP_Transformation Name.

In the Select Lookup Table dialog box, we can choose the following options.

• Choose an existing table or file definition.

• Choose to import a definition from a relational table or file.

• Skip to create a manual definition.

If we want to manually define the lookup transformation, click the Skip button.

Define input ports for each Lookup condition we want to define.

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Lookup TransformationLookup Transformation

For Lookup transformations that use a dynamic lookup cache, associate an input port or sequence ID with each lookup port.

On the Properties tab, set the properties for the lookup.

Click OK.

Configuring Unconnected Lookup Transformations An unconnected Lookup transformation is separate from

the pipeline in the mapping. we write an expression using the :LKP reference qualifier to call the lookup within another transformation.

Adding Input Ports. Adding the Lookup Condition.

ITEM_ID = IN_ITEM_ID PRICE <= IN_PRICE

Designating a Return Value. Calling the Lookup Through an Expression.

LKP.lookup_transformation_name(argument, argument, ...)

Double click on lookup transformation edit transformation opens. Edit Transformation

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Lookup TransformationLookup Transformation

Setting the properties to port tab And properties tab

Lookup Transformation TipsPort Tab Properties Tab

Add an index to the columns used in a lookup condition

Place conditions with an equality operator (=) first.

Cache small lookup tables.

Join tables in the database.

Use a persistent lookup cache for static lookups.

Call unconnected Lookup transformations with the :LKP reference qualifier.

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Lookup CachesLookup Caches

The Integration Service builds a cache in memory when it processes the first row of data in a cached Lookup transformation.

It allocates memory for the cache based on the amount we configure in the transformation or session properties.

The Integration Service stores condition values in the index cache and output values in the data cache.

The Integration Service queries the cache for each row that enters the transformation.

The Integration Service also creates cache files by default in the $PMCacheDir.

Types of lookup caches

Persistent cache Recache from database Static cache Dynamic cache Shared cache

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Rank TransformationRank Transformation

The Rank transformation is Active Transformation The Rank transformation allow us to select only the top

or bottom rank of data. The Rank transformation differs from the transformation

functions MAX and MIN, to select a group of top or bottom values, not just one value.

Creating Rank Transformation• In the Mapping Designer, click Transformation >

Create. Select the Rank transformation. Enter a name for the Rank. The naming convention for Rank transformations is RNK_TransformationName.

• Enter a description for the transformation. This description appears in the Repository Manager.

• Click Create, and then click Done.• The Designer creates the Rank transformation. • Link columns from an input transformation to the

Rank transformation.• Click the Ports tab, and then select the Rank (R)

option for the port used to measure ranks.• If we want to create groups for ranked rows,

select Group By for the port that defines the group. Port Tab

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Click the Properties tab and select whether we want the top or bottom rank

For the Number of Ranks option, enter the number of rows we want to select for the rank.

Change the other Rank transformation properties, if necessary.

Click OK. Click Repository > Save.

Properties Tab

Rank TransformationRank Transformation

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Sequence Generator TransformationSequence Generator Transformation

A Sequence Generator transformation is a passive transformation. The Sequence Generator transformation generates numeric values. We can use the Sequence Generator to create unique primary key values, cycle through a

sequential range of numbers. The Sequence Generator transformation is a connected transformation. The Integration Service generates a value each time a row enters a connected

transformation, even if that value is not used. When NEXTVAL is connected to the input port of another transformation, the Integration

Service generates a sequence of numbers. When CURRVAL is connected to the input port of another transformation, the Integration

Service generates the NEXTVAL value plus one. We can make a Sequence Generator reusable, and use it in multiple mappings. Web might reuse a Sequence Generator when we perform multiple loads to a single target. If we have a large input file we can separate into three sessions running in parallel, we can

use a Sequence Generator to generate primary key values. If we use different Sequence Generators, the Integration Service might accidentally

generate duplicate key values. Instead, we can use the reusable Sequence Generator for all three sessions to provide a

unique value for each target row.

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Sequence Generator TransformationSequence Generator Transformation

Tasks with a Sequence Generator Transformation

Create keys Replace missing values Cycle through a sequential range of numbers

Creating a Sequence Generator Transformation In the Mapping Designer, select Transformation-Create. Select

the Sequence Generator transformation. The naming convention for Sequence Generator transformations is SEQ_TransformationName.

Enter a name for the Sequence Generator, and click Create. Click Done.

The Designer creates the Sequence Generator transformation.Edit Transformation Double-click the title bar of the transformation to open the Edit

Transformations dialog box.Properties Tab Select the Properties tab. Enter settings as necessary. Click OK. To generate new sequences during a session, connect the

NEXTVAL port to at least one transformation in the mapping. Choose Repository-Save.

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Sequence Generator TransformationSequence Generator Transformation

Sequence Generator Ports The Sequence Generator provides two output ports:

NEXTVAL and CURRVAL. Use the NEXTVAL port to generate a sequence of

numbers by connecting it to a transformation or target. We connect the NEXTVAL port to a downstream

transformation to generate the sequence based on the Current Value and Increment By properties.

Connect NEXTVAL to multiple transformations to generate unique values for each row in each transformation.

We might connect NEXTVAL to two target tables in a mapping to generate unique primary key values.

NEXTVAL to Two Target Tables in a Mapping We configure the Sequence Generator transformation as

follows: Current Value = 1, Increment By = 1. When we run the workflow, the Integration Service

generates the following primary key values for the T_ORDERS_PRIMARY andT_ORDERS_FOREIGN target tables.

T_ORDERS_PRIMARY TABLE:PRIMARY KEY

T_ORDERS_FOREIGN TABLE: PRIMARY KEY

1 2

3 4

5 6

7 8

9 10

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Sequence Generator TransformationSequence Generator Transformation

Sequence Generator and Expression Transformation

We configure the Sequence Generator transformation as follows: Current Value = 1, Increment By = 1

Output key values for the

T_ORDERS_PRIMARY and T_ORDERS_FOREIGN target tables

T_ORDERS_PRIMARY TABLE:PRIMARY KEY

T_ORDERS_FOREIGN TABLE:PRIMARY KEY

1 1

2 2

3 3

4 4

5 5

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Sequence Generator TransformationSequence Generator Transformation

CURRVAL is the NEXTVAL value plus one or NEXTVAL plus the Increment By value.

We typically only connect the CURRVAL port when the NEXTVAL port is already connected to a downstream transformation.

When a row enters the transformation connected to the CURRVAL port, the Informatica Server passes the last-created NEXTVAL value plus one.

Connecting CURRVAL and NEXTVAL Ports to a Target

We configure the Sequence Generator transformation as follows: Current Value = 1, Increment By = 1.

When we run the workflow, the Integration Service generates the following values for NEXTVAL and CURRVAL.

OUT PUT When we run the workflow, the Integration Service

generates the following values for NEXTVAL and CURRVAL.

If we connect the CURRVAL port without connecting the NEXTVAL port, the Integration Service passes a constant value for each row.

NEXTVAL CURRVAL

1 2

2 3

3 4

4 5

5 6

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Sequence Generator TransformationSequence Generator Transformation

Only the CURRVAL Port to a Target

For example, we configure the Sequence Generator transformation as follows.

OUTPUT

Current Value = 1, Increment By = 1 When we run the workflow, the Integration

Service generates the following constant values for CURRVAL.

CURRVAL

1

1

1

1

1

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Source Qualifier TransformationSource Qualifier Transformation

A Source Qualifier is an active transformation. The Source Qualifier represents the rows that the Integration

Service reads when it executes a session. When we add a relational or a flat file source definition to a

mapping source Qualifier transformation automatically comes.

Task of Source Qualifier TransformationWe can use the Source Qualifier to perform the following tasks.

Join data originating from the same source database. Filter records when the Integration Service reads source data. Specify an outer join rather than the default inner join Specify sorted ports. Select only distinct values from the source. Create a custom query to issue a special SELECT statement

for the Integration Service to read source data.Default Query of Source Qualifier For relational sources, the Integration Service generates a

query for each Source Qualifier when it runs a session. The default query is a SELECT statement for each source

column used in the mapping.

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Source Qualifier TransformationSource Qualifier Transformation

To view the Default Query To view the default query.

• From the Properties tab, select SQL Query • Click Generate SQL • Click Cancel to exit

Example of source Qualifier Transformation We might see all the orders for the month, including

order number, order amount, and customer name. The ORDERS table includes the order number and

amount of each order, but not the customer name. To include the customer name, we need to join the ORDERS and CUSTOMERS tables.

Setting the properties to Source Qualifier Double-click the title bar of the transformation to

open the Edit Transformations dialog box. Select the Properties tab. Enter settings as

necessary.

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Source Qualifier TransformationSource Qualifier Transformation

SQL Query• We can give query in the Source Qualifier

transformation. • From the Properties tab, select SQL Query The SQL

Editor displays. Click Generate SQL.Joining Source Data We can use one Source Qualifier transformation to join

data from multiple relational tables. These tables must be accessible from the same instance or database server.

Use the Joiner transformation for heterogeneous sources and to join flat files.

Sorted Ports In the Mapping Designer, open a Source Qualifier

transformation, and click the Properties tab. Click in Number of Sorted Ports and enter the number of

ports we want to sort. The Integration Service adds the configured number of

columns to an ORDER BY clause, starting from the top of the Source Qualifier transformation.

The source database sort order must correspond to the session.

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Stored procedure TransformationStored procedure Transformation

A Stored Procedure is a passive transformation

A Stored Procedure transformation is an important tool for populating and maintaining databases. Database administrators create stored procedures to automate tasks that are too complicated for standard SQL statements.

Stored procedures run in either connected or unconnected mode. The mode we use depends on what the stored procedure does and how we plan to use it in a session. we can configure connected and unconnected Stored Procedure transformations in a mapping.

• Connected: The flow of data through a mapping in connected mode also passes through the Stored Procedure transformation. All data entering the transformation through the input ports affects the stored procedure. We should use a connected Stored Procedure transformation when we need data from an input port sent as an input parameter to the stored procedure, or the results of a stored procedure sent as an output parameter to another transformation.

• Unconnected: The unconnected Stored Procedure transformation is not connected directly to the flow of the mapping. It either runs before or after the session, or is called by an expression in another transformation in the mapping.

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Stored procedure TransformationStored procedure Transformation

Creating a Stored Procedure TransformationAfter we configure and test a stored procedure in the database, we must create the Stored Procedure transformation in the Mapping Designer

To import a stored procedure In the Mapping Designer, click Transformation >Import Stored

Procedure. Select the database that contains the stored procedure from

the list of ODBC sources. Enter the user name, owner name, and password to connect to the database and click Connect

Select the procedure to import and click OK.. The Stored Procedure transformation appears in the mapping.

The Stored Procedure transformation name is the same as the stored procedure we selected.

Open the transformation, and click the Properties tab Select the database where the stored procedure exists from

the Connection Information row. If we changed the name of the Stored Procedure transformation to something other than the name of the stored procedure, enter the Stored Procedure Name.

Click OK. Click Repository > Save to save changes to the mapping.

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Update StrategyUpdate Strategy

An Update Strategy is an active transformation . When we design a data warehouse, we need to decide what type of information to store in

targets. As part of the target table design, we need to determine whether to maintain all the historic data or just the most recent changes.

The model we choose determines how we handle changes to existing rows. In PowerCenter, we set the update strategy at two different levels.

Within a session Within a mapping

Setting the Update Strategy We use the following steps to define an update strategy To control how rows are flagged for insert, update, delete, or reject within a mapping, add

an Update Strategy transformation to the mapping. Update Strategy transformations are essential if we want to flag rows destined for the same target for different database operations, or if we want to reject rows.

Define how to flag rows when we configure a session. We can flag all rows for insert, delete, or update, or we can select the data driven option, where the Integration Service follows instructions coded into Update Strategy transformations within the session mapping.

Define insert, update, and delete options for each target when we configure a session. On a target-by-target basis, we can allow or disallow inserts and deletes.

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Update StrategyUpdate Strategy

Creating an Update Transformation In the Mapping Designer, select Transformation-Create. Select the

Update transformation. The naming convention for Update transformations is UPD_TransformationName.

Enter a name for the Update transformation , and click Create. Click Done.

The Designer creates the Update transformation. Drag all ports from another transformation representing data we want

to pass through the Update Strategy transformation. In the Update Strategy transformation, the Designer creates a copy

of each port we drag. The Designer also connects the new port to the original port. Each port in the Update Strategy transformation is a combination of input/output port.

Normally, we would select all of the columns destined for a particular target. After they pass through the Update Strategy transformation, this information is flagged for update, insert, delete, or reject.

Double-click the title bar of the transformation to open the Edit Transformations dialog box.

Click the Properties tab. Click the button in the Update Strategy Expression field. The Expression Editor appears.

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Update StrategyUpdate Strategy

Enter an update strategy expression to flag rows as inserts, deletes, updates, or rejects.

Validate the expression and click OK. Click OK to save the changes. Connect the ports in the Update Strategy

transformation to another transformation or a target instance.

Click Repository > SaveSetting the Update Strategy for a Session When we configure a session, we have

several options for handling specific database operations, including updates.

Specifying an Operation for All Rows When we configure a session, we can select

a single database operation for all rows using the Treat Source Rows As setting.

Configure the Treat Source Rows As session property.

Treat Source Rows displays the options like. Insert Delete Update Data Driven

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Update StrategyUpdate Strategy

Specifying Operations for Individual Target Tables

Once we determine how to treat all rows in the session, we also need to set update strategy options for individual targets. Define the update strategy options in the Transformations view on Mapping tab of the session properties.

We can set the following update strategy options for Individual Target Tables.

Insert. Select this option to insert a row into a target table.

Delete. Select this option to delete a row from a table..

Update. You have the following options in this situation.

• Update as Update. Update each row flagged for update if it exists in the target table.

• Update as Insert. Inset each row flagged for update.

• Update else Insert. Update the row if it exists. Otherwise, insert it.

Truncate table. Select this option to truncate the target table before loading data.

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Router TransformationRouter Transformation

A Router transformation is an Active Transformation. A Router transformation is similar to a Filter transformation because both transformations

allow us to use a condition to test data. A Filter transformation tests data for one condition and drops the rows of data that do not

meet the condition. However, a Router transformation tests data for one or more conditions and gives us the option to route rows of data that do not meet any of the conditions to a default output group.

If we need to test the same input data based on multiple conditions, use a Router transformation in a mapping instead of creating multiple Filter transformations to perform the same task.Creating a Router Transformation

In the Mapping Designer, click Transformation > Create. Select the Router transformation. Enter a name for the transformation and Click OK.

The naming convention for router transformation is

RTR_TransformationName.

Input values in the Router Transformation• Select and drag all the desired ports from a

transformation to add them to the Router transformation.

Double-click the title bar of the Router transformation to edit transformation properties.

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Router TransformationRouter Transformation

Setting the properties to port tab And properties tab

Port Tab Properties Tab

Group tab in Router Transformation

Click the Group Filter Condition field to open the Expression Editor.

Enter a group filter condition. Click Validate to check the syntax

of the conditions we entered. Click OK. Connect group output ports to

transformations or targets. Choose Repository-Save.

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Router TransformationRouter Transformation

Router Transformation Components

A Router transformation has the following types of groups.

Input Output

There are two types of output groups.

User-defined groups Default group

Working with Ports

A Router transformation has input ports and output ports.

Input ports reside in the input group, and output ports reside in the output groups.

We can create input ports by copying them from another transformation or by manually creating them on the Ports tab. Port tab in Router Transformation

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Connecting Router Transformations in a Mapping

When we connect transformations to a Router transformation in a mapping consider the following rules.

We can connect one group to one transformation or target.

Connect one port to Multiple Target

We can connect one output port in a group to multiple transformations or targets.

Connect Multiple out ports to Multiple Target

We can connect multiple output ports in one group to multiple transformations or targets.

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Reusable TransformationReusable Transformation

Reusable transformation is a transformation that can be used in multiple mappings. We can create most transformations as a non-reusable or reusable but only create the

External Procedure transformation as a reusable transformation . When we add a reusable transformation to a mapping, we add an instance of the

transformation. The definition of the transformation still exists outside the mapping.

Methods To Create Reusable Transformation

Design it in the Transformation Developer

In the Transformation Developer, we can build new reusable transformations.

Promote a non-reusable transformation from the Mapping Designer

After we add a transformation to a mapping, we can promote it to the status of reusable transformation. The transformation designed in the mapping then becomes an instance of a reusable transformation maintained elsewhere in the repository.

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Reusable TransformationReusable Transformation

Creating Reusable Transformation Goto transformation

developer<Transformation <create. To promote an existing transformation to

re-usable: Goto mapping designer>double click on transformation>>transformation tab>make reusable.

Changes that can invalidate mapping

When we delete a port or multiple ports in a transformation.

When we change a port datatype, you make it impossible to map data from that port to another port using an incompatible datatype.

When we change a port name, expressions that refer to the port are no longer valid.

When we enter an invalid expression in the reusable transformation, mappings that use the transformation are no longer valid. The Integration Service cannot run sessions based on invalid mappings

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Java TransformationJava Transformation

The Java transformation is a Active/Passive Connected transformation that provides a simple native programming interface to define transformation functionality with the Java programming language.

You create Java transformations by writing Java code snippets that define transformation logic.

The Power Center Client uses the Java Development Kit (JDK) to compile the Java code and generate byte code for the transformation. The Integration Service uses the Java Runtime Environment (JRE) to execute generated byte code at run time.

Steps To Define Java Transformation Create the transformation in the Transformation Developer or Mapping Designer. Configure input and output ports and groups for the transformation. Use port names as

variables in Java code snippets. Configure the transformation properties. Use the code entry tabs in the transformation to write and compile the Java code for the

transformation. Locate and fix compilation errors in the Java code for the transformation.

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Java TransformationJava Transformation

Enter the ports and use that ports as identifier in java code.

Go to java code and enter the java code and click compile and check the output in the output window.

Create session and workflow and run the session.

Functions

Some functions used in designer are AVG

Syntax : AVG( numeric_value [, filter_condition ] ) MAX

Syntax: MAX( value [, filter_condition ] ) MIN

Syntax :MIN( value [, filter_condition ] ) INSTR

Syntax :INSTR( string, search_value [, start [, occurrence ] ] )

SUBSTR

Syntax :SUBSTR( string, start [, length ] ) IS_DATE

Syntax:IS_DATE( value )

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Working With Flat FilesWorking With Flat Files

To use flat files as sources, targets, and lookups in a mapping we must import or create the definitions in the repository .

We can import or create flat file source definitions in the Source Analyzer or create flat file target definitions in the Target Designer or import flat files lookups or use existing file definitions in a Lookup transformation.

When we create a session with a file source, we specify a source file location different from the location we use , when we import the file source definition.

Importing a flat file Goto sources<import from file<select the file. Click on delimited and next. Name the different columns and change the

datatype if needed. Click finish.

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Working With Flat FilesWorking With Flat Files

Editing a flat file definition

Table tabEdit properties such as table name, business name, and flat file properties.

Columns tabEdit column information such as column names, datatypes, precision, and formats.

Properties tabWe can edit the default numeric and datetime format properties in the Source Analyzer and the Target Designer.

Metadata Extensions tabWe can extend the metadata stored in the repository by associating information with repository objects, such as flat file definitions.

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User Defined FunctionsUser Defined Functions

We can create user-defined functions using the PowerCenter transformation language. Create user-defined functions to reuse expression logic and build complex expressions. User-defined functions are available to other users in a repository.

Once you create user-defined functions, we can manage them from the User-Defined Function Browser dialog box. We can also use them as functions in the Expression Editor. They display on the User-Defined Functions tab of the Expression Editor.

We create a user-defined function in the Transformation Developer. Configure the following information when we create a user-defined function.

• Name• Type• Description• Arguments• Syntax

Steps to Create User-Defined Functions In the Transformation Developer, click

Tools > User-Defined Functions. Click New The Edit User-Defined Function dialog

box appears Enter a function name Select a function type If we create a public user-defined

function, we cannot change the function to private when we edit the function.

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User Defined FunctionsUser Defined Functions

Optionally, enter a description of the user-defined function. We can enter up to 2,000 characters.

Create arguments for the user-defined function. When we create arguments, configure the argument name, data type, precision, and scale.

We can select transformation data types.

Click Launch Editor to create an expression that contains the arguments we defined.

Click OK The Designer assigns the data type of the data the expression returns. The data types have

the precision and scale of transformation data types.

Click OK The expression displays in the User-Defined Function Browser dialog box.

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Mapplet DesignerMapplet Designer

A mapplet is a reusable object that we create in the Mapplet Designer. It contains a set of transformations and we reuse that transformation logic in multiple mappings.

When we use a mapplet in a mapping, we use an instance of the mapplet. Like a reusable transformation, any change made to the mapplet is inherited by all instances of the mapplet.

Usage of Mapplets

Include source definitions

Use multiple source definitions and source qualifiers to provide source data for a mapping. Accept data from sources in a mapping

If we want the mapplet to receive data from the mapping, we use an Input transformation to receive source data.

Include multiple transformations

A mapplet can contain as many transformations as you need. Pass data to multiple transformations

We can create a mapplet to feed data to multiple transformations. Contain unused ports

We do not have to connect all mapplet input and output ports in a mapping

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Mapplet DesignerMapplet Designer

Limitations of Mapplets We cannot connect a single port in the Input transformation to multiple transformations in

the mapplet.

An input transformation must receive data from a single active source.

A mapplet must contain at least one Input transformation or source definition with at least one port connected to a transformation in the mapplet and same applies for output transformation.

When a mapplet contains a source qualifier that has an override for the default SQL query, we must connect all of the source qualifier output ports to the next transformation within the mapplet.

We cannot include PowerMart 3.5-style LOOKUP functions in a mapplet.

We cannot include the following objects : Normalizer transformations, Cobol sources, XML Source Qualifier transformations, XML sources and targets, Pre- and post- session stored procedures and other mapplets.

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Data ProfilingData Profiling

Data profiling is a technique used to analyze source data. PowerCenter Data Profiling can help us to evaluate source data and detect patterns and exceptions. we can profile source data to suggest candidate keys, detect data patterns and evaluate join criteria.

Use Data Profiling to analyze source data in the following situations. During mapping development . During production to maintain data quality. To profile source data, we create a data profile. we can create a data profile based on a

source or mapplet in the repository. Data profiles contain functions that perform calculations on the source data.

The repository stores the data profile as an object. we can apply profile functions to a column within a source, to a single source, or to multiple sources.

We can create the following types of data profiles.

Auto profileContains a predefined set of functions for profiling source data. Use an auto profile during mapping development.

Custom profileUse a custom profile during mapping development to validate documented business rules about the source data. we can also use a custom profile to monitor data quality or validate the results of BI reports.

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Data ProfilingData Profiling

Steps To Create Auto Profile When we create an auto profile, we can

profile groups or columns in the source. Or, we can profile the entire source.

To create an auto profile. Select the source definition in the

Source Analyzer or mapplet in the Mapplet Designer you want to profile.

Launch the Profile Wizard from the following Designer tools.

• Source Analyzer. Click Sources > Profiling > Create Auto Profile.

• Mapplet Designer. Click Mapplets > Profiling > Create Auto Profile.

• You set the default data profile options to open the Auto Profile Column Selection dialog box when you create an auto profile.

• The source definition contains 25 or more columns.

Optionally, click Description to add a description for the data profile. Click OK.

Enter a description up to 200 characters. Optionally, select the groups or columns in the

source that you want to profile.

By default, all columns or groups are selected Select Load Verbose Data if you want the

Integration Service to write verbose data to the Data Profiling warehouse during the profile session. By default, Load Verbose Data option is disabled.

Click Next. Select additional functions to include in the auto

profile. We can also clear functions we do not want to include.

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Optionally, click Save As Default to create new default functions based on the functions selected here.

Optionally, click Profile Settings to enter settings for domain inference and structure inference tuning.

Optionally, modify the default profile settings and click OK. Click Configure Session to configure the session properties after you create the data profile. Click Next if you selected Configure Session, or click Finish if you disabled Configure Session. The Designer generates a data profile and profile mapping based on the profile functions. Configure the Profile Run options and click Next. Configure the Session Setup options. Click Finish.

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Data ProfilingData Profiling

We can create a custom profile from the following Designer tools.• Source Analyzer. Click Sources >

Profiling > Create Custom Profile.• Mapplet Designer. Click Mapplets

> Profiling > Create Custom Profile.

• Profile Manager. Click Profile > Create Custom.

To create a custom profile, complete the following. • Enter a data profile name and

optionally add a description.• Add sources to the data profile.

Add, edit, or delete a profile function and enable session configuration.

Configure profile functions.

Configure the profile session if we enable session

configuration.

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Profile ManagerProfile Manager

Profile Manager is a tool that helps to manage data profiles. It is used to set default data profile options, work with data profiles in the repository, run profile sessions, view profile results, and view sources and mapplets with at least one profile defined for them. When we launch the Profile Manager, we can access profile information for the open folders in the repository.

There are two views in the Profile Manager

• Profile View: The Profile View tab displays the data profiles in the open folders in the repository.

• Source View: The Source View tab displays the source definitions in the open folders in the repository for which we have defined data profiles.

Profile View

Source View

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Debugger OverviewDebugger Overview

We can debug a valid mapping to gain troubleshooting information about data and error conditions.

Debugger used in the following situations

• Before we run a session

After we save a mapping, we can run some initial tests with a debug session before we create and configure a session in the Workflow Manager.

• After we run a session

If a session fails or if we receive unexpected results in the target, we can run the Debugger against the session. we might also run the Debugger against a session if we want to debug the mapping using the configured session properties.

Create breakpoints. Create breakpoints in a mapping where we want the Integration Service to evaluate data and error conditions.

Configure the Debugger. Use the Debugger Wizard to configure the Debugger for the mapping. Select the session type the Integration Service uses when it runs Debugger.

Run the Debugger. Run the Debugger from within the Mapping Designer. When we run the Debugger the Designer connects to the Integration Service. The Integration Service initializes the Debugger and runs the debugging session and workflow.

Monitor the Debugger. While we run the Debugger, we can monitor the target data, transformation and mapplet output data, the debug log, and the session log.

Modify data and breakpoints. When the Debugger pauses, we can modify data and see the effect on transformations, mapplets, and targets as the data moves through the pipeline. we can also modify breakpoint information.

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Debugger OverviewDebugger Overview

Create Breakpoints

Goto mapping<<debugger<<edit transformations.

Choose the instant name, breakpoint type.

And then ADD to add the breakpoints.

Give the condition for data breakpoint type.

Give no. of errors before we want to stop.

Run The Debugger

Got mapping<debugger<start debugger

Click next and then choose the session as ‘create debug session’ other wise choose ‘existing session’

Click on next

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Debugger OverviewDebugger Overview

Choose connections of target and source and click next.

Click on next

Debug Indicators

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The End