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Informatica Interview Question and Answers

1. What is Data warehouse?

According to Bill Inmon, known as father of Data warehousing. A Data warehouse is a

subject oriented(Customer,Productsales), integrated(integrating multiple,hetrogenous datasource, eg database ,flatfiles), time variant(provide 5-10 years ino), non-volatile collection ofdata(a physically separate store of data transformed from operational environment) in support

of managements decision making process.

2. what are the types of data warehouses?

There are three types of data warehouses

Enterprise Data Warehouse

ODS (operational data store)

Data Mart

3. What is Data mart?

A data mart is a subset of data warehouse that is designed for a particular line of business,

such as sales, marketing, or finance. In a dependent data mart, data can be derived from an

enterprise wide data warehouse. In an independent data mart can be collected directly from

sources.

4. What is star schema?

A star schema is the simplest form of data warehouse schema that consists of one or more

dimensional and fact tables.

5. What is snow flake schema?

A Snowflake schema is nothing but one Fact table which is connected to a number of

dimension tables, The snowflake and star schema are methods of storing data which are

multidimensional in nature.

Informatica Interview Question and Answers

6. What are ETL Tools?ETL Tools are stands for Extraction, Transformation, and Loading the data into the datawarehouse for decision making. ETL refers to the methods involved in accessing and

manipulating source data and loading it into target database.

7. What are Dimensional table?

Dimension tables contain attributes that describe fact records in the fact table.

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8. What is data Modelling?

Data Modeling is representing the real world set of data structures or entities and their

relationship in their of data models, required for a database.Data Modelling consists ofvarious types like :

Conceptual data modeling

Logical data modeling

Physical data modeling

Enterprise data modeling

Relation data modeling

Dimensional data modeling.

9. What is Surrogate key?

Surrogate key is a substitution for the natural primary key. It is just a unique identifier or

number of each row that can be used for the primary key to the table.Surrogate key

Surrogate key is the primary key for the Dimensional table

Surrogate key is a numeric or integer value in a table to identify each row uniquely.

Primary key and surrogate key are same but surrogate key is a system generated value

has a define incremental valu...

Surrogate key and primary key both are same, but point of application is different.

Primary key is part of transactional system but surrogate key is part of analytical

system

Surrogate Key is the solution for critical column problems.

For example the customer purchases different items in different locations,for this

situation we have to maintain historical data.By using surrogate key we can introduce the row in the data warehouse to maintain

historical data

:Every join between dimension tables and fact tables in a data warehouse environment

should be based on surrogate keys,

Surrogate is mainly used in slowly changing dimensions,it maintaining the uniqueness in

the table.it is used to track the old value with the new one.And it is derived from

primary key.

Surrogate key is the primary key for the Dimensional table. Surrogate key is

a substitution for the natural primary key.

Data warehouses typically use a surrogate, (also known as artificial or identity key), key

for the dimension tables primary keys. They can use Infa sequence generator, or Oraclesequence, or SQL Server Identity values for the surrogate key.

It is useful because the natural primary key (i.e. Customer Number in Customer table)

can change and this makes updates more difficult and also used in SCDs to preserve

historical data.

Surkey cust_id location,sd ,ed sysdate-1

1000 100 mumbai ,10/march/2012,(11/march/2012)15/april/2012

1000 100 mumbai ,sysdate,

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1001 100 kolkatta

1050 101 hyderabad

1100 102 banglore

type2: where we track complete history either by flagging records or by having date

column in there.

eg: change of address.every time address is changed a new record is created in the target table.here there are 2

scenarios. either you have a flag column and flag the old record as N and new record as Y

indicating it as latest record or if you also want to track the changes made based on time, then

you can have start_dt and end_dt column in there which will keep updating whenever a newrecord is inserted. for the very first record you can have start_dt as some constant

date(1\1\1950- based on business rule) and end_dt as 31\12\9999. now whenevr a new record

comes, the end dt of last record is updated to the current time using sysdate-1 sec and start_dtfor the new record becomes sysdate.end_dt is same as 31\12\9999.same process is repeatedwhenever there is change in type 2 column value.

also in designer there is a scd type wizard. you can use that for the same for your furtherunderstanding

10. What is Data Mining?

A Data Mining is the process of analyzing data from different perpectives and summarizingit into useful information.

11. What is Operational Data Store?

A ODS is an operational data store which comes as a second layer in a datawarehouse

architecture. It has got the characteristics of both OLTP and DSS systems.

12. What is the Difference between OLTP and OLAP?

OLTP is nothing but OnLine Transaction Processing which contains a normalised tables

.(the process of breaking the data and storing it into different tables in order to reduce theredundancy))

But OLAP(Online Analtical Programming) contains the history of OLTP data which is non-volatile acts as a Decisions Support System.

13. How many types of dimensions are available in Informatica?

There are three types of dimensions available are :

Junk dimension

Degenerative Dimension

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Conformed Dimension

14. What is Difference between ER Modeling and Dimensional Modeling?

ER Modeling is used for normalizing the OLTP database design.

Dimesional modeling is used for de-normalizing the ROLAP / MOLAP design.

15. What is the maplet?

Maplet is a set of transformations that you build in the maplet designer and you can use inmultiple mapings.

16. What is Session and Batches?

Session: A session is a set of commands that describes the server to move data to the target.

Batch: A Batch is set of tasks that may include one or more numbar of tasks (sessions,ewent wait, email, command, etc).

17. What are slowly changing dimensions?

Dimensions that change overtime are called Slowly Changing Dimensions(SCD).

Slowly Changing Dimension-Type1 : Which has only current records.

Slowly Changing Dimension-Type2 : Which has current records + historical records.

Slowly Changing Dimension-Type3 : Which has current records + one previous

records.

18. What are 2 modes of data movement in Informatica Server?

There are two modes of data movement are:Normal Mode in which for every record a separate DML stmt will be prepared and

executed.

Bulk Mode in which for multiple records DML stmt will be preapred and executed thus

improves performance.

19. What is the difference between Active and Passive transformation?

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 thatpass through it i.e it passes all rows through the transformation.

20. What is the difference between connected and unconnected transformation?

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

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value to that transformation.

What are different types of transformationsavailable in Informatica?

There are various types of transformationsavailable in Informatica :

Aggregator

ApplicationSource Qualifier

Custom

Expression

External Procedure

Filter Input

Joiner

Lookup

Normalizer

Output

Rank

Router

Sequence Generator

Sorter

Source Qualifier

Stored Procedure Transaction Control

Union

Update Strategy

XML Generator

XML Parser

XML Source Qualifier

22. What are Aggregator Transformation?

Aggregator transformation is an Active and Connected transformation. This

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

23. What are 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.

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24. What are 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.

25. What are 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.

Why we use lookup transformations?

Lookup Transformations can access data from relational tables that are not sources inmapping.

27. What are 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 denormalizedformat. Also, Normalizer transformation can be used to create multiple rows from a

single row of data.

28. What are Rank transformation?

Rank transformation is an Active and Connected transformation. It is used to selectthe top or bottom rank of data.

29. What are Router transformation?

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

filter transformation. The only difference is, filter transformation drops the data thatdo 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.

30. What are 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.

Name four output files that informations server creates during

session running?

Session Log

Workflow Log

Errors Log

Badfile

32. Why we use stored procedure transformation?

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A stored procedure transformation is an important tool for populating and maintaingdatabases.

33. What are the difference between static cache and dynamic cache?

Dynamic cache decreases the performance in comparision to static cache.Static cache do not see such things just insert data as many times as it is coming

34. Define maping and sessions?

Maping: It is a set of source and target definitions linked by transformation

objects that define the rules for transformation.

Session : It is a set of instructions that describe how and when to move data from

source to targets.

35. What is a command that used to run a batch?

pmcmd is used to start a batch.

1

36. What is Datadriven?

The informatica server follows instructions coded into update strategy

transformations with in the session maping determine how to flag records for insert,

update, delete or reject.

37. What is power center repository?

The PowerCenter repository allows you to share metadata across repositories to

create a data mart domain.

38. What is parameter file?

A parameter file is a file created by text editor such as word pad or notepad. U candefine the following values in parameter file.

Maping parameters

Maping variablessession parameters.

39. What are the types of lookup caches?

Static cache

Dynamic cache

Persistent cache

Shared cache

Recache.

40 What are Stored Procedure transformation?

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.

Stored Procedure transformation is an Passive & Connected or UnConnected

transformation. It is useful to automate time-consuming tasks and it is also used inerror handling, to drop and recreate indexes and to determine the space in database,

a specialized calculation

What is fact table?

The centralized table in a star schema is called as fact table. Fact tables

are three types

additive

non-additive

semi additive

42. What is Data warehouse?

According to Bill Inmon, known as father of Data warehousing. A Data

warehouse is a subject oriented, integrated ,time variant, non volatile

collection of data in support of managements decision making process.

43. What is Data Transformation Manager(DTM)?

After the load manager performs validations for the session, it creates the

DTM process. The DTM process is the second process associated with the

session run.

44. How can you define a transformation?

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

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

functions.

45

.What are 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.

What are Source Qualifier

transformation?

Source Qualifier transformation is an Active and

Connected transformation. When adding a

relational or a flat file source definition to a

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mapping, it is must to connect it to a SourceQualifier transformation. The Source Qualifier

performs the various tasks such as overriding

default SQL query, filtering records; join data fromtwo or more tables etc.

47. What is difference between maplet and reusable transformation?

Maplet consists of set of transformations that is reusable.

A reusable transformation is a single transformation that can be reusable.

48. What are 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.

49. How many types of dimensions are available in informatica?

There are three types of dimensions.

Star schema

Snowflake schema

Glaxy schema

50.What is difference between maplet and reusable

transformation?

Maplet : one or more transformations.

set of transformations that are reusable.

Reusable transformation: only one transformation.

Single transformation which is reusable.

What are different types of

parsing?

Quick parsing

Thorough parsing

52. What are Lookup and Fact Tables?

A lookup (Dimension) table contains information about the entities. In

general the Dimension and details objects are derived from lookup tables. A

fact table contains the statistical information about transactions.

53. What is Designer?

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Designer is the Business objects product that is intended to develop theuniverses. These universe is the semantic - layer of the database structure

that isolates from technical issues.

54. What is Surrogate Key?

Surrogate keys are keys that are maintained within the data warehouse

instead of keys taken from source data systems.

55. What are the pitfalls of DWH?

Limited value of data (Historical data not current data)

DW solutions complicate business processes

DW solutions may have too long a learning curve

Costs of cleaning, capturing and delivering data

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How do you handle large datasets?

By Using Bulk utility mode at the session

level and if possible by disabling constraintsafter consulting with DBA; Using Bulk utility

mode would mean that no writing is taking

place in Roll Back Segment so loading is

faster. However the pitfall is that recovery isnot possible.

57. What are the limitations of handling long datatypes?

When the length of a datatype (e.g varchar2(4000)) goes beyond 4000, Informaticamakes this as varchar2(2000).

58. What are the types of OLAP?

ROLAP (Relational OLAP) - Users see their data organized in cubes and

dimensions but the data is really stored in RDBMS. The performance is slow.Astoragemode that uses tables in a relational database to store multidimensional

structures.MOLAP (Multidimensional OLAP) - Users see their data organized in cubes and

dimensions but the data is really stored in MDBMS. Query performance is fast.

HOLAP (Hybrid OLAP) - It is a combination of ROLAP and HOLAP. EG:

HOLOs. In this one will find data queries on aggregated data as well as detailed data.

59. What is the difference between data mart and data warehouse?

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Data mart used on a business division/department level where as data warehouse isused on enterprise level.

60. What is Meta data?

Data about the data, contains the location and description of data warehouse systemcomponents such as name, definitions and end user views.

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How does the recoverymode work in

informatica?

In case of load failure an entry is made inOPB_SERV_ENTRY(?) table from where the extent of

loading can be determined.

62. What is Aggregate Awareness?

Aggregate awareness is a feature of DESIGNER that makes use of aggregate tables in

a database. These are tables that contain pre-calculated data. The purpose of these

tables is to enhance the performance of SQL transactions; they are thus used to speedup the execution of queries.

63. What is a difference between OLTP and OLAP?

OLTP

It focus on day to day transaction.

Data Stability

Dynamic

Highly normalized.

Access Frequency High.

OLAP

It focus on future predictions and decisions

Static until refreshed

Demoralized and replicated data

Medium to low.

64. When should you use a star schema and when a snowflake schema?

A star schema is a simplest data warehouse schema. Snowflake schema is similar tothe star schema. It normalizes dimension table to save data storage space. It can be

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used to represent hierarchies of information.

65. What parameters can be tweaked to get better performance from a session?

DTM shared memory, Index cache memory, Data cache memory, by indexing, using

persistent cache, increasing commit interval etc.1

What are the benefits ofDWH?

Immediate information delivery

Data Integrationfrom across, even outside the

organization

Future vision of historical trends

Tools for looking at data in new ways

Enhanced customer service.

67. Is It Possible to invoke Informatica batch or session outside Informatica UI?

PMCMD.

68. Why we are going for surrogate keys?

Data tables in various source systems may use different keys for the sameentity.

Keys may change or be reused in the source data systems.

Changes in organizational structures may move keys in the hierarchy.

69. When is more convenient to join in the database or in Informatica?

Definitely at the database level

at the source Qualifier query itself

rather than using Joiner transformation

70. How do you measure session performance?

By checking Collect performance Data check box.

What is Dimension Table?It contains data used to reference data stored in the fact table.

Fewer rows Primarily character data

One primary key (dimensional key)

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Updatable data

72. What is a database connection?

A connection is a set of parameters that provides access to an RDBMS. Theseparameters include system information such as the data account, user identification,

and the path to the database. Designer provides three types of connections: secured,

shared, and personal.

73. What are all the types of dimensions?

Informational Dimension

Structural Dimension

Categorical Dimension

Partitioning Dimension

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Top 50 Informatica Interview Questions withAnswers

Last Updated on Monday, 15 October 2012 03:35

Written by Akash Mitra

Welcome to the finest collection of Informatica Interview Questions with standard answers that you

can count on. Read and understand all the questions and their answers below and in the following

pages to get a good grasp in Informatica.

What are the differences between Connected and Unconnected Lookup?

The differences are illustrated in the below table

Connected Lookup Unconnected Lookup

Connected lookup participates in Unconnected lookup receives input

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dataflow and receives input directly

from the pipeline

values from the result of a LKP:

expression in another transformation

Connected lookup can use bothdynamic and static cache

Unconnected Lookup cache can NOTbe dynamic

Connected lookup can return more

than one column value ( output port )

Unconnected Lookup can return only

one column value i.e. output port

Connected lookup caches all lookup

columns

Unconnected lookup caches only the

lookup output ports in the lookup

conditions and the return port

Supports user-defined default values

(i.e. value to return when lookup

conditions are not satisfied)

Does not support user defined default

values

What is the difference between Router and Filter?

Following differences can be noted,

Router Filter

Router transformation divides the

incoming records into multiple groups

based on some condition. Such groupscan be mutually inclusive (Different

groups may contain same record)

Filter transformation restricts or blocks

the incoming record set based on onegiven condition.

Router transformation itself does not

block any record. If a certain record

Filter transformation does not have a

default group. If one record does not

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does not match any of the routing

conditions, the record is routed to

default group

match filter condition, the record is

blocked

Router acts like CASE.. WHEN

statement in SQL (Or Switch().. Case

statement in C)

Filter acts like WHERE condition is SQL.

What can we do to improve the performance of Informatica Aggregator

Transformation?

Aggregator performance improves dramatically if records are sorted before passing to the aggregator

and "sorted input" option under aggregator properties is checked. The record set should be sorted on

those columns that are used in Group By operation.

It is often a good idea to sort the record set in database level (click here to see why?) e.g. inside a

source qualifier transformation, unless there is a chance that already sorted records from source

qualifier can again become unsorted before reaching aggregator

You may also read this article to know how to tune the performance of aggregator transformation

What are the different lookup cache(s)?

Informatica Lookups can be cached or un-cached (No cache). And Cached lookup can be either static

or dynamic. A static cache is one which does not modify the cache once it is built and it remainssame during the session run. On the other hand, Adynamic cache is refreshed during the session runby inserting or updating the records in cache based on the incoming source data. By default,

Informatica cache is static cache.

A lookup cache can also be divided aspersistent or non-persistentbased on whether Informaticaretains the cache even after the completion of session run or deletes it

How can we update a record in target table without using Update

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strategy?

A target table can be updated without using 'Update Strategy'. For this, we need to define the key in

the target table in Informatica level and then we need to connect the key and the field we want to

update in the mapping Target. In the session level, we should set the target property as "Update as

Update" and check the "Update" check-box.

Let's assume we have a target table "Customer" with fields as "Customer ID", "Customer Name" and

"Customer Address". Suppose we want to update "Customer Address" without an Update Strategy.

Then we have to define "Customer ID" as primary key in Informatica level and we will have to connect

Customer ID and Customer Address fields in the mapping. If the session properties are set correctly

as described above, then the mapping will only update the customer address field for all matching

customer IDs.

Under what condition selecting Sorted Input in aggregator may fail the

session?

If the input data is not sorted correctly, the session will fail.

Also if the input data is properly sorted, the session may fail if the sort order by ports and the group

by ports of the aggregator are not in the same order.

Why is Sorter an Active Transformation?

This is because we can select the "distinct" option in the sorter property.

When the Sorter transformation is configured to treat output rows as distinct, it assigns all ports as

part of the sort key. The Integration Service discards duplicate rows compared during the sort

operation. The number of Input Rows will vary as compared with the Output rows and hence it is an

Active transformation.

Is lookup an active or passive transformation?

From Informatica 9x, Lookup transformation can be configured as as "Active" transformation.

Find out How to configure lookup as active transformation

However, in the older versions of Informatica, lookup is a passive transformation

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What is the difference between Static and Dynamic Lookup Cache?

We can configure a Lookup transformation to cache the underlying lookup table. In case of static or

read-only lookup cache the Integration Service caches the lookup table at the beginning of the

session and does not update the lookup cache while it processes the Lookup transformation.

In case of dynamic lookup cache the Integration Service dynamically inserts or updates data in the

lookup cache and passes the data to the target. The dynamic cache is synchronized with the target.

In case you are wondering why do we need to make lookup cache dynamic, read this article on

dynamic lookup

What is the difference between STOP and ABORT options in Workflow

Monitor?

When we issue the STOP command on the executing session task, the Integration Service stops

reading data from source. It continues processing, writing and committing the data to targets. If the

Integration Service cannot finish processing and committing data, we can issue the abort command.

In contrast ABORT command has a timeout period of 60 seconds. If the Integration Service cannot

finish processing and committing data within the timeout period, it kills the DTM process and

terminates the session.

What are the new features of Informatica 9.x in developer level?

From a developer's perspective, some of the new features in Informatica 9.x are as follows:

Now Lookup can be configured as an active transformation - it can return multiple rows on

successful match

Now you can write SQL override on un-cached lookup also. Previously you could do it only on cached

lookup

You can control the size of your session log. In a real-time environment you can control the session

log file size or time

Database deadlock resilience feature - this will ensure that your session does not immediately fail if it

encounters any database deadlock, it will now retry the operation again. You can configure number of

retry attempts.

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How to Delete duplicate row using Informatica

Scenario 1: Duplicate rows are present in relational database

Suppose we have Duplicate records in Source System and we want to load only the unique records in

the Target System eliminating the duplicate rows. What will be the approach?

Assuming that the source system is a Relational Database, to eliminate duplicate records, we cancheck the Distinct option of the Source Qualifier of the source table and load the target accordingly.

Scenario 2: Deleting duplicate records from flatfileTo know the answer of the above question (and many more similar high frequency Informatica

questions) please continue to, Best Informatica Interview Questions (Page 2) >> [Only for registered

Informatica Mapping Designer

Q. How to execute PL/SQL script from Informatica mapping?

A. Stored Procedure (SP) transformation can be used to execute PL/SQL Scripts. In SP

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Transformation PL/SQL procedure name can be specified. Whenever the session is

executed, the session will call the pl/sql procedure.

Q. How can you define a transformation? What are different types of transformations

available in Informatica?

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

Designer provides a set of transformations that perform specific functions. For example, an

Aggregator transformation performs calculations on groups of data. Below are the various

transformations available in Informatica:

Aggregator

Application Source Qualifier

Custom

Expression

External Procedure

Filter

Input

Joiner

Lookup

Normalizer

Output

Rank

Router

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Sequence Generator

Sorter

Source Qualifier

Stored Procedure

Transaction Control

Union

Update Strategy

XML Generator

XML Parser

XML Source Qualifier

Q. What is a source qualifier? What is meant by Query Override?

A. Source Qualifier represents the rows that the PowerCenter Server reads from a relationalor flat file source when it runs a session. When a relational or a flat file source definition is

added to a mapping, it is connected to a Source Qualifier transformation.

PowerCenter Server generates a query for each Source Qualifier Transformation whenever it

runs the session. The default query is SELET statement containing all the source columns.

Source Qualifier has capability to override this default query by changing the default

settings of the transformation properties. The list of selected ports or the order they appear in

the default query should not be changed in overridden query.

Q. What is aggregator transformation?

A. The Aggregator transformation allows performing aggregate calculations, such as

averages and sums. Unlike Expression Transformation, the Aggregator transformation can

only be used to perform calculations on groups. The Expression transformation permits

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calculations on a row-by-row basis only.

Aggregator Transformation contains group by ports that indicate how to group the data.

While grouping the data, the aggregator transformation outputs the last row of each group

unless otherwise specified in the transformation properties.

Various group by functions available in Informatica are : AVG, COUNT, FIRST, LAST,

MAX, MEDIAN, MIN, PERCENTILE, STDDEV, SUM, VARIANCE.

Q. What is Incremental Aggregation?

A. Whenever a session is created for a mapping Aggregate Transformation, the session

option for Incremental Aggregation can be enabled. When PowerCenter performs

incremental aggregation, it passes new source data through the mapping and uses historical

cache data to perform new aggregation calculations incrementally.

Q. How Union Transformation is used?

A. The union transformation is a multiple input group transformation that can be used to

merge data from various sources (or pipelines). This transformation works just like UNION

ALL statement in SQL, that is used to combine result set of two SELECT statements.

Q. Can two flat files be joined with Joiner Transformation?

A. Yes, joiner transformation can be used to join data from two flat file sources.

Q. What is a look up transformation?

A. This transformation is used to lookup data in a flat file or a relational table, view or

synonym. It compares lookup transformation ports (input ports) to the source column values

based on the lookup condition. Later returned values can be passed to other transformations.

Q. Can a lookup be done on Flat Files?

A. Yes.

Q. What is the difference between a connected look up and unconnected look up?

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A. Connected lookup takes input values directly from other transformations in the pipleline.

Unconnected lookup doesnt take inputs directly from any other transformation, but it can be

used in any transformation (like expression) and can be invoked as a function using :LKP

expression. So, an unconnected lookup can be called multiple times in a mapping.

Q. What is a mapplet?

A. A mapplet is a reusable object that is created using mapplet designer. The mapplet

contains set of transformations and it allows us to reuse that transformation logic in multiple

mappings.

Q. What does reusable transformation mean?

A. Reusable transformations can be used multiple times in a mapping. The reusable

transformation is stored as a metadata separate from any other mapping that uses the

transformation. Whenever any changes to a reusable transformation are made, all the

mappings where the transformation is used will be invalidated.

Q. What is update strategy and what are the options for update strategy?

A. Informatica processes the source data row-by-row. By default every row is marked to be

inserted in the target table. If the row has to be updated/inserted based on some logic Update

Strategy transformation is used. The condition can be specified in Update Strategy to mark

the processed row for update or insert.

Following options are available for update strategy :

DD_INSERT : If this is used the Update Strategy flags the row for insertion.

Equivalent numeric value of DD_INSERT is 0.

DD_UPDATE : If this is used the Update Strategy flags the row for update.

Equivalent numeric value of DD_UPDATE is 1.

DD_DELETE : If this is used the Update Strategy flags the row for deletion.

Equivalent numeric value of DD_DELETE is 2.

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DD_REJECT : If this is used the Update Strategy flags the row for rejection.

Equivalent numeric value of DD_REJECT is 3.

Types of Dimensions

A dimension table consists of the attributes about the facts. Dimensions store the textual descriptions of

the business. Without the dimensions, we cannot measure the facts. The different types of dimension

tables are explained in detail below.

Conformed Dimension:

Conformed dimensions mean the exact same thing with every possible fact table to which they are joined.

Eg: The date dimension table connected to the sales facts is identical to the date dimension connected to

the inventory facts.

Junk Dimension:

A junk dimension is a collection of random transactional codes flags and/or text attributes that are

unrelated to any particular dimension. The junk dimension is simply a structure that provides a convenient

place to store the junk attributes.

Eg: Assume that we have a gender dimension and marital status dimension. In the fact table we need to

maintain two keys referring to these dimensions. Instead of that create a junk dimension which has all the

combinations of gender and marital status (cross join gender and marital status table and create a junk

table). Now we can maintain only one key in the fact table.

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Degenerated Dimension:

A degenerate dimension is a dimension which is derived from the fact table and doesn't have its own

dimension table.

Eg: A transactional code in a fact table.

Role-playing dimension:

Dimensions which are often used for multiple purposes within the same database are called role-playing

dimensions. For example, a date dimension can be used for date of sale", as well as "date of delivery", or

"date of hire".

Types of Facts

http://4.bp.blogspot.com/-

G3hdJ8giIT8/T1icxAa2iSI/AAAAAAAAAQA/hfL7dR3FuoE/s1600/data_warehouse.jpg

A fact table is the one which consists of the measurements, metrics or facts of business process. These

measurable facts are used to know the business value and to forecast the future business. The different

types of facts are explained in detail below.

Additive:

Additive facts are facts that can be summed up through all of the dimensions in the fact table. A sales fact

is a good example for additive fact.

Semi-Additive:

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Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not

the others.

Eg: Daily balances fact can be summed up through the customers dimension but not through the time

dimension.

Non-Additive:

Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table.

Eg: Facts which have percentages, ratios calculated.

Factless Fact Table:

In the real world, it is possible to have a fact table that contains no measures or facts. These tables arecalled "Factless Fact tables".

Eg: A fact table which has only product key and date key is a factless fact. There are no measures in this

table. But still you can get the number products sold over a period of time.

A fact tables that contain aggregated facts are often called summary tables

Dimension Table features

1. It provides the context /descriptive information for fact table measurements.

2. Provides entry points to data.

3. Structure of Dimension - Surrogate key , one or more other fields that compose the natural key (nk) and

set of Attributes.

4. Size of Dimension Table is smaller than Fact Table.

5. In a schema more number of dimensions are presented than Fact Table.

6. Surrogate Key is used to prevent the primary key (pk) violation(store historical data).

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7. Values of fields are in numeric and text representation.

Fact Table features

1. It provides measurement of an enterprise.

2. Measurement is the amount determined by observation.

3. Structure of Fact Table - foreign key (fk), Degenerated Dimension and Measurements.

4. Size of Fact Table is larger than Dimension Table.

5. In a schema less number of Fact Tables observed compared to Dimension Tables.

6. Compose of Degenerate Dimension fields act as Primary Key.

7. Values of the fields always in numeric or integer form.

Types of Facts -

Additive:Additive facts are facts that can be summed up through all of the dimensions in

the fact table. A sales fact is a good example for additive fact.

Semi-Additive:Semi-additive facts are facts that can be summed up for some of the dimensions in

the fact table, but not the others.

Eg: Daily balances fact can be summed up through the customers dimension but

not through the time dimension.Non-Additive:

Non-additive facts are facts that cannot be summed up for any of the dimensions

present in the fact table.

Eg: Facts which have percentages, ratios calculated.

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Factless Fact Table:In the real world, it is possible to have a fact table that contains no measures or

facts. These tables are called Factless Fact tables.Eg: A fact table which has only product key and date key is a factless fact. There

are no measures in this table. But still you can get the number products sold over a

period of time.Based on the above classifications, fact tables are categorized into two:Cumulative:

This type of fact table describes what has happened over a period of time. For

example, this fact table may describe the total sales by product by store by day.

The facts for this type of fact tables are mostly additive facts. The first example

presented here is a cumulative fact table.Snapshot:

This type of fact table describes the state of things in a particular instance of time,

and usually includes more semi-additive and non-additive facts. The second

example presented here is a snapshot fact table.

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50 Frequently asked Informatica Interview Questions with

Answers

April 7, 2012 by admin

1. What do you mean by Enterprise Data Warehousing?

When the organization data is created at a single point of access it is called as enterprise data

warehousing. Data can be provided with a global view to the server via a single source

store. One can do periodic analysis on that same source. It gives better results but however the

time required is high.

2. What the difference is between a database, a data warehouse and a data mart?

Database includes a set of sensibly affiliated data which is normally small in size as compared todata warehouse. While in data warehouse there are assortments of all sorts of data and data is

taken out only according to the customers needs. On the otherhand datamart is also a set of data

which is designed to cater the needs of different domains. For instance an organization having

different chunk of data for its different departments i.e. sales, finance, marketing etc.

3. What is meant by a domain?

When all related relationships and nodes are covered by a sole organizational point, its called

domain. Through this data management can be improved.

4. What is the difference between a repository server and a powerhouse?

Repository server controls the complete repository which includes tables, charts, and various

procedures etc. Its main function is to assure the repository integrity and consistency. While a

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powerhouse server governs the implementation of various processes among the factors of

servers database repository.

5. How many repositories can be created in informatica?

There can be any number of repositories in informatica but eventually it depends on number of

ports.

6. What is the benefit of partitioning a session?

Partitioning a session means solo implementation sequences within the session. Its main

purpose is to improve servers operation and efficiency. Other transformations includingextractions and other outputs of single partitions are carried out in parallel.

7. How are indexes created after completing the load process?

For the purpose of creating indexes after the load process, command tasks at session level can be

used. Index creating scripts can be brought in line with the sessions workflow or the postsession implementation sequence. Moreover this type of index creation cannot be controlled after

the load process at transformation level.

8. Explain sessions. Explain how batches are used to combine executions?

A teaching set that needs to be implemented to convert data from a source to a target is called a

session. Session can be carried out using the sessions manager or pmcmd command. Batch

execution can be used to combine sessions executions either in serial manner or in a parallel.

Batches can have different sessions carrying forward in a parallel or serial manner.

9. How many number of sessions can one group in batches?

One can group any number of sessions but it would be easier for migration if the number of

sessions are lesser in a batch.

10. Explain the difference between mapping parameter and mapping variable?

When values change during the sessions execution its called a mapping variable. Upon

completion the Informatica server stores the end value of a variable and is reused when session

restarts. Moreover those values that do not change during the sessions execution are calledmapping parameters. Mapping procedure explains mapping parameters and their usage. Values

are allocated to these parameters before starting the session.

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11.What is complex mapping?

Following are the features of complex mapping.

Difficult requirements

Many numbers of transformations Complex business logic

12. How can one identify whether mapping is correct or not without connecting session?

One can find whether the session is correct or not without connecting the session is with the help

of debugging option.

13. Can one use mapping parameter or variables created in one mapping into any other

reusable transformation?

Yes, One can do because reusable transformation does not contain any mapplet or mapping.

14. Explain the use of aggregator cache file?

Aggregator transformations are handled in chunks of instructions during each run. It

stores transitional values which are found in local buffer memory. Aggregators provides extra

cache files for storing the transformation values if extra memory is required.

15. Briefly describe lookup transformation?

Lookup transformations are those transformations which have admission right to RDBMS baseddata set. The server makes the access faster by using the lookup tables to look at explicit tabledata or the database. Concluding data is achieved by matching the look up condition for all look

up ports delivered during transformations.

16. What does role playing dimension mean?

The dimensions that are utilized for playing diversified roles while remaining in the same

database domain are called role playing dimensions.

17. How can repository reports be accessed without SQL or other transformations?

Ans:Repositoryreports are established by metadata reporter. There is no need of SQL or other

transformation since it is a web app.

18. What are the types of metadata that stores in repository?

The types of metadata includes Source definition, Target definition, Mappings, Mapplet,

Transformations.

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19. Explain the code page compatibility?

When data moves from one code page to another provided that both code pages have the same

character sets then data loss cannot occur. All the characteristics of source page must beavailable in the target page. Moreover if all the characters of source page are not present in the

target page then it would be a subset and data loss will definitely occur during transformationdue the fact the two code pages are not compatible.

20. How can you validate all mappings in the repository simultaneously?

All the mappings cannot be validated simultaneously because each time only one mapping can

be validated.

21. Briefly explain the Aggregator transformation?

It allows one to do aggregate calculations such as sums, averages etc. It is unlike expression

transformation in which one can do calculations in groups.

22. Describe Expression transformation?

Values can be calculated in single row before writing on the target in this form of transformation.

It can be used to perform non aggregate calculations. Conditional statements can also be tested

before output results go to target tables.

23. What do you mean by filter transformation?

It is a medium of filtering rows in a mapping. Data needs to be transformed through filtertransformation and then filter condition is applied. Filter transformation contains all ports of

input/output, and the rows which meet the condition can only pass through that filter.

24. What is Joiner transformation?

Joiner transformation combines two affiliated heterogeneous sources living in different locations

while a source qualifier transformation can combine data emerging from a common source.

25. What is Lookup transformation?

It is used for looking up data in a relational table through mapping. Lookup definition from anyrelational database is imported from a source which has tendency of connecting client and server.

One can use multiple lookup transformation in a mapping.

26. How Union Transformation is used?

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Ans: It is a diverse input group transformation which can be used to combine data from different

sources. It works like UNION All statement in SQL that is used to combine result set of two

SELECT statements.

27. What do you mean Incremental Aggregation?

Option for incremental aggregation is enabled whenever a session is created for a mapping

aggregate. Power center performs incremental aggregation through the mapping and historical

cache data to perform new aggregation calculations incrementally.

28. What is the difference between a connected look up and unconnected look up?

When the inputs are taken directly from other transformations in the pipeline it is called

connected lookup. While unconnected lookup doesnt take inputs directly from other

transformations, but it can be used in any transformations and can be raised as a function using

LKP expression. So it can be said that an unconnected lookup can be called multiple times in

mapping.

29. What is a mapplet?

A recyclable object that is using mapplet designer is called a mapplet. It permits one to reuse the

transformation logic in multitude mappings moreover it also contains set of transformations.

30.Briefly define reusable transformation?

Reusable transformation is used numerous times in mapping. It is different from other mappings

which use the transformation since it is stored as a metadata. The transformations will benullified in the mappings whenever any change in the reusable transformation is made.

31. What does update strategy mean, and what are the different option of it?

Row by row processing is done by informatica. Every row is inserted in the target table becauseit is marked as default. Update strategy is used whenever the row has to be updated or inserted

based on some sequence. Moreover the condition must be specified in update strategy for the

processed row to be marked as updated or inserted.

32. What is the scenario which compels informatica server to reject files?

This happens when it faces DD_Reject in update strategy transformation. Moreover it disrupts

the database constraint filed in the rows was condensed.

33. What is surrogate key?

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Surrogate key is a replacement for the natural prime key. It is a unique identification for each

row in the table. It is very beneficial because the natural primary key can change which

eventually makes update more difficult. They are always used in form of a digit or integer.

34.What are the prerequisite tasks to achieve the session partition?

In order to perform session partition one need to configure the session to partition source data

and then installing the Informatica server machine in multifold CPUs.

35. Which files are created during the session rums by informatics server?

During session runs, the files created are namely Errors log, Bad file, Workflow low and session

log.

36. Briefly define a session task?

It is a chunk of instruction the guides Power center server about how and when to transfer data

from sources to targets.

37,What does command task mean?

This specific task permits one or more than one shell commands in UNIX or DOS in windows to

run during the workflow.

38. What is standalone command task?

This task can be used anywhere in the workflow to run the shell commands.

39. What is meant by pre and post session shell command?

Command task can be called as the pre or post session shell command for a session task. One can

run it as pre session command r post session success command or post session failure command.

40.What is predefined event?

It is a file-watch event. It waits for a specific file to arrive at a specific location.

41. How can you define user defied event?

User defined event can be described as a flow of tasks in the workflow. Events can be created

and then raised as need arises.

42. What is a work flow?

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Ans: Work flow is a bunch of instructions that communicates server about how to implement

tasks.

43. What are the different tools in workflow manager?

Following are the different tools in workflow manager namely

Task Designer

Task Developer

Workflow Designer

44. Tell me any other tools for scheduling purpose other than workflow manager pmcmd?

The tool for scheduling purpose other than workflow manager can be a third party tool like

CONTROL M.

45. What is OLAP (On-Line Analytical Processing?

A method by which multi-dimensional analysis occurs.

46. What are the different types of OLAP? Give an example?

ROLAP eg.BO, MOLAP eg.Cognos, HOLAP, DOLAP

47. What do you mean by worklet?

When the workflow tasks are grouped in a set, it is called as worklet. Workflow tasks includestimer, decision, command, event wait, mail, session, link, assignment, control etc.

48. What is the use of target designer?

Target Definition is created with the help of target designer.

49. Where can we find the throughput option in informatica?

Throughput option can be found in informatica in workflow monitor. In workflow monitor, right

click on session, then click on get run properties and under source/target statistics we can find

throughput option.

50. What is target load order?

Ans: Target load order is specified on the basis of source qualifiers in a mapping. If there aremultifold source qualifiers linked to different targets then one can entitle order in which

informatica server loads data into targets.

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Informatica Interview Questions with Answers

Thu Aug 12, 2010 3:42pm

bhanuyenna

Joined: 12 Aug 2010Posts: 10

Informatica Interview Questions with Answers

Q3) Tell me what exactly, what was your role ?A3) I worked as ETL Developer. I was also involved in requirement gathering,developing mappings,checking source data. I did Unit testing (using TOAD), helped in UserAcceptance Testing.

Q4) What kind of challenges did you come across in your project ?A4) Mostly the challenges were to finalize the requirements in such a way so

that different stakeholderscome to a common agreement about the scope and expectations from theproject.

Q5) Tell me what was the size of your database ?A5) Around 3 TB. There were other separate systems, but the one I was mainlyusing was around 3 TB.

Q6) what was the daily volume of records ?A6) It used to vary, We processed around 100K-200K records on a daily basis,

on weekends, it used to behigher sometimes around 1+ Million records.

Q7) So tell me what were your sources ?A7) Our Sources were mainly flat files, relational databases.

Q What tools did you use for FTP/UNIX ?

A For UNIX, I used Open Source tool called Putty and for FTP, I used

WINSCP, Filezilla.

Q9) Tell me how did you gather requirements?A9) We used to have meetings and design sessions with end users. The usersused to give us sketchyrequirements and after that we used to do further analysis and used to createdetailed RequirementSpecification Documents (RSD).

Q10) Did you follow any formal process or methodology for Requirementgathering ?A10) As such we did not follow strict SDLC approach because requirementgathering is an iterative process.But after creating the detailed Requirement Specification Documents, we used

to take User signoff.

Q11) Tell me what are the steps involved inApplicationDevelopment ?

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A11) In Application Development, we usually follow following steps:

ADDTIP.

a) A - Analysis or User Requirement Gatheringb) D - Designing and Architecturec) D - Development

d) T - Testing (which involves Unit Testing,

System IntegrationTesting,

UAT - User Acceptance Testing

)e) I - Implementation (also called deployment to production)f) P - Production Support / Warranty

Q12) What are the drawbacks of Waterfall Approach ?A12) This approaches assumes that all the User Requirements will be perfectbefore start of designand development. That is not the case most of the time.Users can change theirmind to add few more detailedrequirements or worse change the requirements drastically. So in those casesthis approach (waterfall) is

likely to cause a delay in project which is a RISK to the project.

Q13) what is mapping design document ?A13) In a mapping design document, we map source to target field, alsodocument any special business logicthat needs to be implemented in the mapping.

Q14) What are diferent Data Warehousing Methodologies that you are familiar

with ?A14) In Data Warehousing, two methodologies are poopulare, 1st one is RalphKimbal and 2nd one is Bill Inmon.

We mainly followed Ralph Kimball's methodlogy in my last project.

In this methodlogy, we have a fact tables in the middle, surrounded bydimension tables.

This is also a basic STAR Schema which is the basic dimensional model.A Snowflake schema. In a snowflake schema, we normalize one of thedimension tables.

Q15) What do you do in Bill Inmon Approach ?A15) In Bill Inmon's approach, we try to create an Enterprise Data Warehouseusing 3rd NF, and then

Data Marts are mainly STAR Schemas in 2nd NF.

Q16) How many mappings have you done ?A16) I did over 35+ mappings, around 10+ were complex mappings.

Q17) What are Test cases or how did you do testing of Informatica Mappings ?

A17) Basically we take the SQL from Source Qualifier and check the source /target data in Toad.

Then we try to spot check data for various conditions according to mappingdocument and look for

any error in mappings.

For example, there may be a condition that if customer account does not existthen filter out that recordand write it to a reject file.

Q18) What are the other error handlings that you did in mappings?

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A18) I mainly looked for non-numeric data in numeric fields, layout of a flat file

may be different.Also dates from flat file come as a string

Q19) How did you debug your mappings ?A19) I used Informatica Debugger to check for any flags being set incorrectly.We see if the

logic / expressions are working or not. We may be expecting data

We use Wizard to configure the debugger.

Q20) Give me an example of a tough situation that you came across inInformatica Mappings

and how did you handle it ?A20) Basically one of our colleagues had created a mapping that was usingJoiner and mapping was taking a lotof time to run, but the Join was in such a way that we could do the Join atDatabase Level (Oracle Level).So I suggested and implemented that change and it reduced the run time by40%.

Q21) Tell me what are various transformations that you have used ?A21) I have used Lookup, Joiner, Update Strategy, Aggregator, Sorter etc.

Q22) How will you categorize various types of transformation ?A22) Transformations can be connected or unconnected. Active or passive.

Q23) What are the different types of Transformations ?A23) Transformations can be active transformation or passive transformations.If the number of outputrows are different than number of input rows then the transformation is anactive transformation.

Like a Filter / Aggregator Transformation. Filter Transformation can filter outsome records based

on condition defined in filter transformation.

Similarly, in an aggregator transformation, number of output rows can be lessthan input rows as

afterapplyingthe aggregate function like SUM, we could have less records.

Q24) What is a lookup transformation ?

A24) We can use a Lookup transformation to look up data in a flat file or arelational table,view, or synonym.

We can use multiple Lookup transformations in a mapping.

The PowerCenter Server queries the lookup source based on the lookup ports inthe

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

We can use the Lookup transformation to perform many tasks, including:1) Get a related value.2) Perform a calculation.3) Update slowly changing dimension tables.

Q25) Did you use unconnected Lookup Transformation ? If yes, then explain.

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A25) Yes. An Unconnected Lookup receives input value as a result of :LKP

Expression in anothertransformation. It is not connected to any other transformation. Instead, it hasinput ports,output ports and a Return Port.

An Unconnected Lookup can have ONLY ONE Return PORT.

Q26) What is Lookup Cache ?A26) The PowerCenter Server builds a cache in memory when it processes thefirst row of data in acached Lookup transformation.

It allocates the memory based on amount configured in the session. Default is2M Bytes for Data Cache and 1M bytes for Index Cache.

We can change the default Cache size if needed.

Condition values are stored in Index Cache and output values in Data cache.

Q27) What happens if the Lookup table is larger than the Lookup Cache ?A27) If the data does not fit in the memory cache, the PowerCenter Serverstores the overflow valuesin the cache files.

To avoid writing the overflow values to cache files, we can increase the defaultcache size.

When the session completes, the PowerCenter Server releases cache memoryand deletes the cache files.

If you use a flat file lookup, the PowerCenter Server always caches the lookupsource.

Q28) What is meant by "Lookup caching enabled" ?

A28) By checking "Lookup caching enabled" option, we are instructingInformatica Server to Cache lookupvalues during the session.

Q29) What are the different types of Lookup ?A29) When configuring a lookup cache, you can specify any of the followingoptions:

a) Persistent cache.You can save the lookup cache files and reuse them the nexttime the

PowerCenter Server processes a Lookup transformation configured to use thecache.

b) Recache from source. If the persistent cache is not synchronized with thelookup table,

you can configure the Lookup transformation to rebuild the lookup cache.

c) Static cache. You can configure a static, or read-only, cache for any lookupsource.

By default, the PowerCenter Server creates a static cache. It caches the lookupfile or tableand looks up values in the cache for each row that comes into thetransformation.

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When the lookup condition is true, the PowerCenter Server returns a value from

the lookupcache. The PowerCenter Server does not update the cache while it processes theLookuptransformation.

d) Dynamic cache. If you want to cache the target table and insert new rows or

updateexisting rows in the cache and the target, you can create a Lookuptransformation touse a dynamic cache.

The PowerCenter Server dynamically inserts or updates data in the lookup cache

and passesdata to the target table.

You cannot use a dynamic cache with a flat file lookup.

e) Shared cache. You can share the lookup cache between multipletransformations. You canshare an unnamed cache between transformations in the same mapping. Youcan share anamed cache between transformations in the same or different mappings.

Q30) What is a Router Transformation ?A30) A Router transformation is similar to a Filter transformation because both

transformationsallow you to use a condition to test data. A Filter transformation tests data forone conditionand drops the rows of data that do not meet the condition.

However, a Router transformation tests data for one or more conditions andgives you theoption to route rows of data that do not meet any of the conditions to a defaultoutput group.

Q31) What is a sorter transformation ?A31) The Sorter transformation allows you to sort data. You can sort data inascending ordescending order according to a specified sort key. You can also configure theSortertransformation for case-sensitive sorting, and specify whether the output rowsshould bedistinct. The Sorter transformation is an active transformation.

It must be connected to the data flow.

Q32) What is a UNION Transformation ?A32) The Union transformation is a multiple input group transformation that you

can use tomerge data from multiple pipelines or pipeline branches into one pipelinebranch. It mergesdata from multiple sources similar to the UNION ALL SQL statement to combinethe resultsfrom two or more SQL statements. Similar to the UNION ALL statement, theUniontransformation does not remove duplicate rows.

You can connect heterogeneous sources to a Union transformation. The Union

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transformation merges sources with matching ports and outputs the data from

one outputgroup with the same ports as the input groups.

Q33) What is Update Strategy ?A33) Update strategy is used to decide on how you will handle updates in yourproject.

When you design your data warehouse, you need to decide what type ofinformation to storein targets. As part of your target table design, you need to determine whetherto maintain allthe historic data or just the most recent changes.

For example, you might have a target table, T_CUSTOMERS, that containscustomer data.

When a customer address changes, you may want to save the original addressin the tableinstead of updating that portion of the customer row. In this case, you wouldcreate a new rowcontaining the updated address, and preserve the original row with the oldcustomer address.

This illustrates how you might store historical information in a target table.

However, if youwant the T_CUSTOMERS table to be a snapshot of current customer data, you

wouldupdate the existing customer row and lose the original address.

The model you choose determines how you handle changes to existing rows.

In PowerCenter, you set your update strategy at two different levels:1) Within a session. When you configure a session, you can instruct thePowerCenter Serverto either treat all rows in the same way (for example, treat all rows as inserts),

or useinstructions coded into the session mapping to flag rows for different databaseoperations.2) Within a mapping. Within a mapping, you use the Update Strategytransformation to flagrows for insert, delete, update, or reject.

Note: You can also use the Custom transformation to flag rows for insert,delete, update, or reject.

Q34) Joiner transformation?A34) A Joiner transformation joins two related heterogenous sources residing in

different location. The combination ofsources can be varied like- two relational tables existing in seperate database.

- two flat files in potentially different file systems.- two different ODBC sources.- two instances of the same XML sources.- a relational table and a flat file source.- a relational table ans a XML source.

Q35) How many types of Joins can you use in a Joiner ?A35) There can be 4 types of joins

a) Normal Join (Equi Join)

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b) Master Outer Join - In master outer join you get all rows from Detail table

c) Detail Outer Join - In Detail Outer Join you get all rows from Master tabled) FULL Outer Join

Q36) What are Mapping Parameter & variables ?A36) We Use Mapping parameter and variables to make mappings more flexible.

Value of a parameter does not change during session, whereas the value storedin a variable can change.

Q37) TELL ME ABOUT PERFORMANCE TUNING IN INFORMATICA?A37) Basically Performance Tuning is an Iterative process, we can do lot of

tuning at database level andif database queries are faster then Informatica workflows will be automaticallyfaster.

For Performance tuning, first we try to identify the source / target bottlenecks.Meaning that first wesee what can be do so that Source data is being retrieved as fast possible.

We try to filter as much data in SOURCE QUALIFIER as possible. If we have touse a filter