Informatica Interview Question Part -10 - ETL- iNFORMATICA DEVELOPER

Sunday, June 23, 2019

Informatica Interview Question Part -10

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Connected Lookup and Unconnected Lookup

Connected Lookup
Unconnected Lookup
Receives input values directly from the pipeline.
Receives input values from the result of a :LKP expression in another transformation.
We can use a dynamic or static cache.
We can use a static cache.
Cache includes all lookup columns used in the mapping.
Cache includes all lookup/output ports in the lookup condition and the lookup/return port.
If there is no match for the lookup condition, the Power Center Server returns the default value for all output ports.
If there is no match for the lookup condition, the Power Center Server returns NULL.
If there is a match for the lookup condition, the Power Center Server returns the result of the lookup condition for all lookup/output ports.
If there is a match for the lookup condition, the Power Center Server returns the result of the lookup condition into the return port.
Pass multiple output values to another transformation.
Pass one output value to another transformation.
Supports user-defined default values
Does not support user-defined default values.


Cache Comparison


Persistence and Dynamic Caches

Dynamic
1) When you use a dynamic cache, the Informatica Server updates the lookup cache as it passes rows to the target.
2) In Dynamic, we can update catch will new data also.
3) Dynamic cache, Not Reusable.
(When we need updated cache data, That only we need Dynamic Cache)
Persistent
1) A Lookup transformation to use a non-persistent or persistent cache. The PowerCenter Server saves or deletes lookup cache files after a successful session based on the Lookup Cache Persistent property.
2) Persistent, we are not able to update the catch with new data.
3) Persistent catch is Reusable.
(When we need previous cache data, that only we need Persistent Cache)


Star Schema And Snow Flake Schema


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

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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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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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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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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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 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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Lookup transformation 


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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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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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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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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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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Sorter Transformation

Sorter transformation is a Connected and an Active transformation.

It allows sorting 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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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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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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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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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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