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Informatica Interview Questions

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Question No : 0

Which transformation should we use to normalize the COBOL and relational sources?

Answer :

Normalizer Transformation. Normalizer Transformation.

Normalizer Transformation.When we drag the COBOL source in to the mapping Designer

workspace,the normalizer transformation automatically appears,creating input and output ports for

every column in the source.

Question No : 1

Difference between static cache and dynamic cache?

Answer :

In case of Dynamic catche when you are inserting a new row it looks at the lookup catche to see if

the row existing or not,If not it inserts in the target and catche as well in case of Static catche when

you are inserting a new row it checks the catche and writes to the target but not catche

If you cache the lookup table, you can choose to use a dynamic or static cache. By default, the

lookup cache remains static and does not change during the session. With a dynamic cache, the

Informatica Server inserts or updates rows in the cache during the session. When you cache the

target table as the lookup, you can look up values in the target and insert them if they do not exist,

or update them if they do.

Question No : 2

What are the join types in joiner transformation?

Answer :

Normal Join Master Join Detail Join Outer Join

the following are the join types Normal,MasterOuter,Detail Outer,Full Outer

Normal,Master Outer,Detail Outer and Full Outer

Question No : 3

In which condtions we can not use joiner transformation(Limitaions of joiner transformation)?

Answer :

no restrictions

you perform the following task before configuring the joiner transformation configure the

transformation to use sorted data and define the join condition to recieve sorted data in the same

order as the sort origin

In the conditions; Either input pipeline contains an Update Strategy transformation, You connect a

Sequence Generator transformation directly before the Joiner transformation

1.Both input pipelines originate from the same Source Qualifier transformation. 2.Both input

pipelines originate from the same Normalizer transformation. 3.Both input pipelines originate from

the same Joiner transformation. 4.Either input pipeline contains an Update Strategy

transformation. 5.We connect a Sequence Generator transformation directly before the Joiner

transformation.

1.Both input pipelines originate from the same Source Qualifier transformation. 2.Both input

pipelines originate from the same Normalizer transformation.

3.Both input pipelines originate from the same Joiner transformation.

4.Either input pipeline contains an Update Strategy transformation.

5.We connect a Sequence Generator transformation directly before the Joiner transformation.

Question No : 4

What is the look up transformation?

Answer :

Used to look up data in a reational table or view.

Lookup is a passive transformation and used to look up data in a flat file or a relational table

Question No : 5

What are the diffrence between joiner transformation and source qualifier transformation?

Answer :

1. Source Qualifier Operates only with relational sources within the same schema. Joiner can have

either heterogenous sources or relation sources in different schema 2. Source qualifier requires

atleats one matching column to perform a join. Joiner joins based on matching port. 3.

Additionally, Joiner requires two separate input pipelines and should not have an update strategy

or Sequence generator (this is no longer true from Infa 7.2).

1)Joiner can join relational sources which come from different sources whereas in source qualifier

the relational sources should come from the same data source. 2)We need matching keys to join

two relational sources in source qualifier transformation.Where as we doesn?t need matching keys

to join two sources.

Question No : 6

Why use the lookup transformation?

Answer :

Used to look up data in a relational table or view.

in Inf7.1, we can get from flat file also

look up is used to perform one of the following task: -to get related value -to perform calculation -to

update slowley changing dimension table

generally we use lookup transformation for 1) get a related value from key column value 2) check

whether the record already existing in the table 3) slowly changing dimension tables

A Lookup transformation is used for checking the matched values from the source or target

tables,used for updating the slowly changing dimensions and also performs some calculations.

Question No : 7

How can you improve session performance in aggregator transformation?

Answer :

How can you improve session performance in aggregator transformation?

By using Incremental Aggregation

create the sorter transformation before the aggregator

sorted input

Ya we can use a Sorted Input option to improve the performance. Basically aggregate

transformation reduces the performance because it uses caches.

Question No : 8

Can you use the maping parameters or variables created in one maping into any other reusable

transformation?

Answer :

Yes. Because reusable transformation is not contained with any mapplet or mapping.

Question No : 9

What is meant by lookup caches?

Answer :

Session will read all unique rows from the reference table/ file to fill the local buffer first; then for

each row received from up-stream transformation, it tries to match them against the local buffer

Informatica server builts a cache in memory when it process the first row of a cached lookup

transformation. alidwh@gmail.com

- When server runs a lookup transformation, the server builds a cache in memory, when it process

the first row of data in the transformation. - Server builds the cache and queries it for the each row

that enters the transformation. - The server creates index and data cache files in the lookup cache

drectory and used the server code page to create the files. - index cache contains conductional

values and data cache contains output values

The informatica server builds a cache in memory when it processes the first row of a data in a

cached look up transformation. It allocates memory for the cache based on the amount you

configure in the transformation or session properties. The informatica server stores condition

values in the index cache and output values in the data cache.

Question No : 10

What is source qualifier transformation?

Answer :

SQ is an active tramsformation. It performs one of the following task: to join data from the same

source database to filtr the rows when Power centre reads source data to perform an outer join to

select only distinct values from the source

In source qualifier transformatio a user can defined join conditons,filter the data and eliminating

the duplicates. The default source qualifier can over written by the above options, this is known as

SQL Override. alidwh@gmail.com

The source qualifier represents the records that the informatica server reads when it runs a

session.

When we add a relational or a flat file source definition to a mapping,we need to connect it to a

source qualifier transformation.The source qualifier transformation represents the records that the

informatica server reads when it runs a session.

Question No : 11

How the informatica server increases the session performance through partitioning the source?

Answer :

Partittionig the session improves the session performance by creating multiple connections to

sources and targets and loads data in paralel pipe lines

Question No : 12

What are the settiings that you use to cofigure the joiner transformation?

Answer :

Master group flow detail group flow join condition type of join

take less no. of rows table as master table, more no of table as detail table and join condition.

joiner will put all row from master table into chache and check condition with detail table rows.

1) Master Source 2) Detail Source 3) Type Of Join 4) Condition of Join

Question No : 13

What are the rank caches?

Answer :

the informatica server stores group information in an index catche and row data in data catche

when the server runs a session with a Rank transformation, it compares an input row with rows

with rows in data cache. If the input row out-ranks a stored row,the Informatica server replaces the

stored row with the input row.

During the session ,the informatica server compares an inout row with rows in the datacache. If

the input row out-ranks a stored row, the informatica server replaces the stored row with the input

row. The informatica server stores group information in an index cache and row data in a data

cache.

Question No : 14

What is Code Page Compatibility?

Answer :

When two code pages are compatible, the characters encoded in the two code pages are virtually

identical.

Compatibility between code pages is used for accurate data movement when the Informatica

Sever runs in the Unicode data movement mode. If the code pages are identical, then there will

not be any data loss. One code page can be a subset or superset of another. For accurate data

movement, the target code page must be a superset of the source code page.

Question No : 15

How can you create or import flat file definition in to the warehouse designer?

Answer :

By giving server connection path

Create the file in Warehouse Designer or Import the file from the location it exists or modify the

source if the structure is one and the same

first create in source designer then draginto warhouse designer you can't create a flat file target

defenition directly ramraj

There is no way to import target definition as file in Informatica designer. So while creating the

target definition for a file in the warehouse designer it is created considering it as a table, and then

in the session properties of that mapping it is specified as file.

U can not create or import flat file definition in to warehouse designer directly.Instead U must

analyze the file in source analyzer,then drag it into the warehouse designer.When U drag the flat

file source definition into warehouse designer workspace,the warehouse designer creates a

relational target definition not a file definition.If u want to load to a file,configure the session to write

to a flat file.When the informatica server runs the session,it creates and loads the flatfile.

Question No : 16

What is aggregate cache in aggregator transforamtion?

Answer :

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IT IS A CACHE

Aggregate value will stored in data cache, grouped column value will stored in index cache

Power centre server stores data in the aggregate cache until it completes aggregate calculations.

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? Aggregator Index Cache stores group by values from Group-By ports and Data Cache stores

aggregate data based on Group-By ports (variable ports, output ports, non group by ports). When

the PowerCenter Server runs a session with an Aggregator transformation, it stores data in

memory until it completes the aggregation. If you use incremental aggregation, the PowerCenter

Server saves the cache files in the cache file directory.

it is a temporary memory used by aggregator in order to improve the performance

aggregator transformation contains two caches namely data cache and index cache data cache

consists aggregator value or the detail record index cache consists grouped column value or

unique values of the records

When the PowerCenter Server runs a session with an Aggregator transformation, it stores data in

aggregator until it completes the aggregation calculation.

The aggregator stores data in the aggregate cache until it completes aggregate calculations.When

u run a session that uses an aggregator transformation,the informatica server creates index and

data caches in memory to process the transformation.If the informatica server requires more

space,it stores overflow values in cache files.

Question No : 17

How can you recognise whether or not the newly added rows in the source are gets insert in the

target?

Answer :

In the type-2 mapping we have three options to recognise the newly added rows. i) Version

Number ii) Flag Value iii) Effective Date Range

we can add a count aggregator column to the target and generate it before running the mapping

there might couple of different ways to do this or we can run a sql query after running the mapping

each time to make sure new data is inserted

From session SrcSuccessRows can be compared with TgtSuccessRows

check the seesion log or check the target table.

Question No : 18

What are the types of lookup?

Answer :

Connected look up and un-connected look up

Unconnected Lookup and Connected Lookup

connected and unconnected

1.connected 2.unconnected

connected

Connected look up and un-connected look up

Connected, unconnected, dynamic

Connected look up and un-connected look up static dynamic

two types 1.connected 2.unconnected

Static and Dynamic Lookup

There are tow tyes of lookups connected lookups and unconnected lookups

Two types of Look Ups Connected and Unconnected lookups

CONNECTED AND UNCONNECTED

Connected and unconnected cached and uncached

no kind of lookup

CONNECTED AND UNCONNECTED

Static Lookup and Dynamic Loook up...Static is agin devided into two parts connected lookup and

unconnected lookup

Mainly first three Based on connectio: 1. Connected 2. unconnected Based on sourceType: 1. Flat

file 2. Relational Based on cache: 1. Cached 2. uncached Based on cacheType: 1. Static 2.

Dynamic Based on reuse: 1. persistance 2. Non persistance Based on input: 1. Sorted 2. unsorted

connected, unconnected

mainly two types of look up...there 1.static lookup 2.dynamic lookup In static lookup ..there two

types are used one is connected and unconnected. In connected lookup means while using the

pipeline symbol... In unconnected lookup means while using the expression condition..

Question No : 19

What are the types of metadata that stores in repository?

Answer :

Data base connections,global

objects,sources,targets,mapping,mapplets,sessions,shortcuts,transfrmations

The repository stores metada that describes how to transform and load source and target data.

Data about data

Metadata can include information such as mappings describing how to transform source data,

sessions indicating when you want the Informatica Server to perform the transformations, and

connect strings for sources and targets.

Following are the types of metadata that stores in the repository Database connections Global

objects Mappings Mapplets Multidimensional metadata Reusable transformations Sessions and

batches Short cuts Source definitions Target definitions Transformations.

Question No : 20

What happens if Informatica server doesn't find the session parameter in the parameter file?

Answer :

Workflow will fail.

Question No : 21

Can you access a repository created in previous version of informatica?

Answer :

We have to migrate the repository from the older version to newer version. Then you can use that

repository.

Question No : 22

Without using ETL tool can u prepare a Data Warehouse and maintain?

Answer :

Yes we can do that using PL/ SQL or Stored procedures when all the data are in the same

databases. If you have source as flat files you can?t do it through PL/ SQL or stored procedures.

Question No : 23

How do you identify the changed records in operational data?

Answer :

In my project source system itself sending us the new records and changed records from the last

24 hrs.

Question No : 24

Why couldn't u go for Snowflake schema?

Answer :

Snowflake is less performance while compared to star schema, because it will contain multi joins

while retrieving the data.

Snowflake is preferred in two cases,

If you want to load the data into more hierarchical levels of information example yearly,

quarterly, monthly, daily, hourly, minutes of information. Prefer snowflake.

Whenever u found input data contain more low cardinality elements. You have to prefer

snowflake schema. Low cardinality example: sex , marital Status, etc., Low cardinality means no

of distinct records is very less while compared to total number of the records,

Question No : 25

Name some measures in your fact table?

Answer :

Sales amount.

Question No : 26

How many dimension tables did you had in your project and name some dimensions (columns)?

Answer :

Product Dimension : Product Key, Product id, Product Type, Product name, Batch Number.

Distributor Dimension: Distributor key, Distributor Id, Distributor Location,

Customer Dimension : Customer Key, Customer Id, CName, Age, status, Address, Contact

Account Dimension : Account Key, Acct id, acct type, Location, Balance,

Question No : 27

How many Fact and Dimension tables are there in your project?

Answer :

In my module (Sales) we have 4 Dimensions and 1 fact table.

Question No : 28

How many Data marts are there in your project?

Answer :

There are 4 Data marts, Sales, Marketing, Finance and HR. In my module we are handling only

sales data mart.

Question No : 29

What is the daily data volume (in GB/records)? What is the size of the data extracted in the

extraction process?

Answer :

Approximately average 40k records per file per day. Daily we will get 8 files from 8 source

systems.

Question No : 30

What is the size of the database in your project?

Answer :

Based on the client?s database, it might be in GB?s.

Question No : 31

What is meant by clustering?

Answer :

It will join two (or more) tables in single buffer, will retrieve the data easily.

Question No : 32

Whether are not the session can be considered to have a heterogeneous target is determined?

Answer :

It will consider (there is no primary key and foreign key relationship)

Question No : 33

Under what circumstance can a target definition are edited from the mapping designer. Within the

mapping where that target definition is being used?

Answer :

We can't edit the target definition in mapping designer. we can edit the target in warehouse

designer only. But in our projects, we haven't edited any of the targets. if any change required to

the target definition we will inform to the DBA to make the change to the target definition and then

we will import again. We don't have any permission to the edit the source and target tables.

Question No : 34

Can a source qualifier be used to perform a outer join when joining 2 database?

Answer :

No, we can't join two different databases join in SQL Override.

Question No : 35

If u r source is flat file with delimited operator.when next time u want change that delimited

operator where u can make?

Answer :

In the session properties go to mappings and click on the target instance click set file properties

we have to change the delimited option.

Question No : 36

If index cache file capacity is 2MB and datacache is 1 MB. If you enter the data of capacity for

index is 3 MB and data is 2 MB. What will happen?

Answer :

Nothing will happen based the buffer size exists in the server we can change the cache sizes. Max

size of cache is 2 GB.

Question No : 37

Difference between next value and current value ports in sequence generator?

Answer :

Assume that they r both connected to the input of another transformer?

It will gives values like nextvalue 1, currval 0.

Question No : 38

How does dynamic cache handle the duplicates rows?

Answer :

Dynamic Cache will gives the flags to the records while inserting to the cache it will gives flags to

the records, like new record assigned to insert flag as "0", updated record is assigned to updated

flag as "1", No change record assigned to rejected flag as "2"

Question No : 39

How will u find whether your mapping is correct or not without connecting session?

Answer :

Through debugging option.

Question No : 40

If you are using aggregator transformation in your mapping at that time your source contain

dimension or fact?

Answer :

According to requirements, we can use aggregator transformation. There is no limitation for the

aggregator. We should use source as dimension or fact.

Question No : 41

My input is oracle and my target is flat file shall I load it? How?

Answer :

Yes, Create flat file based on the structure match with oracle table in warehouse designer than

develop the mapping according requirement and map to that target flat file. Target file is created in

TgtFiles directory in the server system.

Question No : 42

for a session, can I use 3 mappings?

Answer :

No, for one session there should be only one mapping. We have to create separate session for

each mapping.

Question No : 43

Type of loading procedures?

Answer :

Load procedures are two types 1) Normal load 2) bulk loads if you are talking about informatica

level. If you are talking about project load procedures based on the project requirement. Daily

loads or weekly loads.

Question No : 44

Are you involved in high level r low level design? What is meant by that high level design n low

level design?

Answer :

Low Level design:

Requirements should be in the excel format which describes field to field validations and

business logic needs to present. Mostly onsite team will do this Low Level design.

High Level Design:

Describes the informatica flow chart from source qualifier to target simply we can say flow chart of

the informatica mapping. Developer will do this design document.

Question No : 45

what r the dimension load methods?

Answer :

Daily loads or weekly loads based on the project requirement.

Question No : 46

where we are using lkp b/n source to stage or stage to target?

Answer :

Depend on the requirement. There is no rule we have to use in this stage only.

Question No : 47

How will you do SQL tuning?

Answer :

We can do SQL tuning using Oracle Optimizer, TOAD software

Question No : 48

did u use any other tools for scheduling purpose other than workflow manager or pmcmd?

Answer :

Using third party tools like "Control M",

Question No : 49

What is SQL mass updating?

Answer :

A)

Update (select hs1.col1 as hs1_col1

, hs1.col2 as hs1_col2

, hs1.col3 as hs1_col3

, hs2.col1 as hs2_col1

, hs2.col2 as hs2_col2

, hs2.col3 as hs2_col3

From hs1, hs2

Where hs1.sno = hs2.sno)

set hs1_col1 = hs2_col1

, hs1_col2 = hs2_col2

, hs1_col3 = hs2_col3;

Question No : 50

what is unbounded exception in source qualifier?

Answer :

"TE_7020 Unbound field in Source Qualifier" when running session

A) Problem Description:

When running a session the session fails with the following error:

TE_7020 Unbound field <field_name> in Source Qualifier <SQ_name>"

Solution:

This error will occur when there is an inconsistency between the Source Qualifier and the source

table.

Either there is a field in the Source Qualifier that is not in the physical table or there is a column

of the source object that has no link to the corresponding port in the Source Qualifier.

To resolve this, re-import the source definition into the Source Analyzer in Designer.

Bring the new Source definition into the mapping.This will also re-create the Source Qualifier.

Connect the new Source Qualifier to the rest of the mapping as before.

Question No : 51

Using unconnected lookup how we you remove nulls n duplicates?

Answer :

We can't handle nulls and duplicates in the unconnected lookup. We can handle in dynamic

connected lookup.

Question No : 52

I have 20 lookup, 10 joiners, 1 normalizer how will you improve the session performance?

Answer :

We have to calculate lookup & joiner caches size.

Question No : 53

What is version controlling?

Answer :

It is the method to differentiate the old build and the new build after changes made to the existing

code. For the old code v001 and next time u have to increase the version number as v002 like

that. In my last company we haven't use any version controlling. We just delete the old build and

replace with the new code.

We don't maintain version controlling in informatica. We are maintaining the code in VSS (Virtual

visual Source) that is the software with maintain the code with versioning. Whenever client made

change request came once the production starts we have to create another build.

Question No : 54

How is the Sequence Generator transformation different from other transformations?

Answer :

The Sequence Generator is unique among all transformations because we cannot add, edit, or

delete its default ports (NEXTVAL and CURRVAL).

Unlike other transformations we cannot override the Sequence Generator transformation

properties at the session level. This protecxts the integrity of the sequence values generated.

Question No : 55

What are the advantages of Sequence generator? Is it necessary, if so why?

Answer :

We can make a Sequence Generator reusable, and use it in multiple mappings. We might reuse a

Sequence Generator when we perform multiple loads to a single target.

For example, if we have a large input file that we 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 Informatica Server might accidentally generate duplicate key values. Instead, we

can use the same reusable Sequence Generator for all three sessions to provide a unique value

for each target row.

Question No : 56

What are the uses of a Sequence Generator transformation?

Answer :

We can perform the following tasks with a Sequence Generator transformation:

oCreate keys

oReplace missing values

oCycle through a sequential range of numbers

Question No : 57

What is Sequence Generator Transformation?

Answer :

The Sequence Generator transformation generates numeric values. We can use the Sequence

Generator to create unique primary key values, replace missing primary keys, or cycle through a

sequential range of numbers.

The Sequence Generation transformation is a connected transformation. It contains two output

ports that we can connect to one or more transformations.

Question No : 58

What is the difference between connected lookup and unconnected lookup?

Answer :

Differences between Connected and Unconnected Lookups:

Connected LookupUnconnected 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 cacheWe can use a static cache

Supports user-defined default valuesDoes not support user-defined default values

Question No : 59

What are connected and unconnected Lookup transformations?

Answer :

We can configure a connected Lookup transformation to receive input directly from the mapping

pipeline, or we can configure an unconnected Lookup transformation to receive input from the

result of an expression in another transformation.

An unconnected Lookup transformation exists separate from the pipeline in the mapping. We write

an expression using the :LKP reference qualifier to call the lookup within another transformation.

A common use for unconnected Lookup transformations is to update slowly changing dimension

tables.

Question No : 60

What is a Lookup transformation and what are its uses?

Answer :

We use a Lookup transformation in our mapping to look up data in a relational table, view or

synonym.

We can use the Lookup transformation for the following purposes:

&#61558;Get a related value. For example, if our source table includes employee ID, but we want

to include the employee name in our target table to make our summary data easier to read.

&#61558;Perform a calculation. Many normalized tables include values used in a calculation, such

as gross sales per invoice or sales tax, but not the calculated value (such as net sales).

&#61558;Update slowly changing dimension tables. We can use a Lookup transformation to

determine whether records already exist in the target.

Question No : 61

What is a lookup table?

Answer :

The lookup table can be a single table, or we can join multiple tables in the same database using a

lookup query override. The Informatica Server queries the lookup table or an in-memory cache of

the table for all incoming rows into the Lookup transformation.

If your mapping includes heterogeneous joins, we can use any of the mapping sources or mapping

targets as the lookup table.

Question No : 62

Where do you define update strategy?

Answer :

We can set the Update strategy at two different levels:

?Within a session. When you configure a session, you can instruct the Informatica Server to either

treat all records in the same way (for example, treat all records as inserts), or use instructions

coded into the session mapping to flag records for different database operations.

?Within a mapping. Within a mapping, you use the Update Strategy transformation to flag records

for insert, delete, update, or reject.

Question No : 63

What is Update Strategy?

Answer :

When we design our data warehouse, we need to decide what type of information to store in

targets. As part of our target table design, we need to determine whether to maintain all the

historic data or just the most recent changes.

The model we choose constitutes our update strategy, how to handle changes to existing records.

Update strategy flags a record for update, insert, delete, or reject. We use this transformation

when we want to exert fine control over updates to a target, based on some condition we apply.

For example, we might use the Update Strategy transformation to flag all customer records for

update when the mailing address has changed, or flag all employee records for reject for people

no longer working for the company.

Question No : 64

What are the different types of Transformations?

Answer :

a) Aggregator transformation: The Aggregator transformation allows you to perform aggregate

calculations, such as averages and sums. The Aggregator transformation is unlike the Expression

transformation, in that you can use the Aggregator transformation to perform calculations on

groups. The Expression transformation permits you to perform calculations on a row-by-row basis

only. (Mascot)

b) Expression transformation: You can use the Expression transformations to calculate values in a

single row before you write to the target. For example, you might need to adjust employee

salaries, concatenate first and last names, or convert strings to numbers. You can use the

Expression transformation to perform any non-aggregate calculations. You can also use the

Expression transformation to test conditional statements before you output the results to target

tables or other transformations.

c) Filter transformation: The Filter transformation provides the means for filtering rows in a

mapping. You 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.

d) Joiner transformation: While a Source Qualifier transformation can join data originating from a

common source database, the Joiner transformation joins two related heterogeneous sources

residing in different locations or file systems.

e) Lookup transformation: Use a Lookup transformation in your mapping to look up data in a

relational table, view, or synonym. Import a lookup definition from any relational database to which

both the Informatica Client and Server can connect. You can use multiple Lookup transformations

in a mapping.

The Informatica Server queries the lookup table based on the lookup ports in the transformation. It

compares Lookup transformation port values to lookup table column values based on the lookup

condition. Use the result of the lookup to pass to other transformations and the target.

Question No : 65

What is a transformation?

Answer :

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

logic in a transformation that the Informatica Server uses to transform data. The Designer provides

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

transformation performs calculations on groups of data.

Each transformation has rules for configuring and connecting in a mapping. For more information

about working with a specific transformation, refer to the chapter in this book that discusses that

particular transformation.

You can create transformations to use once in a mapping, or you can create reusable

transformations to use in multiple mappings.

Question No : 66

What are the tools provided by Designer?

Answer :

The Designer provides the following tools:

?Source Analyzer. Use to import or create source definitions for flat file, XML, Cobol, ERP, and

relational sources.

?Warehouse Designer. Use to import or create target definitions.

?Transformation Developer. Use to create reusable transformations.

?Mapplet Designer. Use to create mapplets.

?Mapping Designer. Use to create mappings.

Question No : 67

What are the different types of Commit intervals?

Answer :

The different commit intervals are:

?Target-based commit. The Informatica Server commits data based on the number of target rows

and the key constraints on the target table. The commit point also depends on the buffer block

size and the commit interval.

?Source-based commit. The Informatica Server commits data based on the number of source

rows. The commit point is the commit interval you configure in the session properties.

Question No : 68

What is Event-Based Scheduling?

Answer :

When you use event-based scheduling, the Informatica Server starts a session when it locates the

specified indicator file. To use event-based scheduling, you need a shell command, script, or

batch file to create an indicator file when all sources are available. The file must be created or sent

to a directory local to the Informatica Server. The file can be of any format recognized by the

Informatica Server operating system. The Informatica Server deletes the indicator file once the

session starts.

Use the following syntax to ping the Informatica Server on a UNIX system:

pmcmd ping [{user_name | %user_env_var} {password | %password_env_var}] [hostname:]portno

Use the following syntax to start a session or batch on a UNIX system:

pmcmd start {user_name | %user_env_var} {password | %password_env_var} [hostname:]portno

[folder_name:]{session_name | batch_name} [:pf=param_file] session_flag wait_flag

Use the following syntax to stop a session or batch on a UNIX system:

pmcmd stop {user_name | %user_env_var} {password | %password_env_var}

[hostname:]portno[folder_name:]{session_name | batch_name} session_flag

Use the following syntax to stop the Informatica Server on a UNIX system:

pmcmd stopserver {user_name | %user_env_var} {password | %password_env_var}

[hostname:]portno

Question No : 69

I have the Administer Repository Privilege, but I cannot access a repository using the Repository

Manager.

Answer :

To perform administration tasks in the Repository Manager with the Administer Repository

privilege, you must also have the default privilege Browse Repository. You can assign Browse

Repository directly to a user login, or you can inherit Browse Repository from a group.

Question No : 70

My privileges indicate I should be able to edit objects in the repository, but I cannot edit any

metadata.

Answer :

You may be working in a folder with restrictive permissions. Check the folder permissions to see if

you belong to a group whose privileges are restricted by the folder owner.

Question No : 71

How does read permission affect the use of the command line program, pmcmd?

Answer :

To use pmcmd, you do not need to view a folder before starting a session or batch within the

folder. Therefore, you do not need read permission to start sessions or batches with pmcmd. You

must, however, know the exact name of the session or batch and the folder in which it exists.

With pmcmd, you can start any session or batch in the repository if you have the Session Operator

privilege or execute permission on the folder.

Question No : 72

I do not want a user group to create or edit sessions and batches, but I need them to access the

Server Manager to stop the Informatica Server.

Answer :

To permit a user to access the Server Manager to stop the Informatica Server, you must grant

them both the Create Sessions and Batches, and Administer Server privileges. To restrict the user

from creating or editing sessions and batches, you must restrict the user's write permissions on a

folder level.

Alternatively, the user can use pmcmd to stop the Informatica Server with the Administer Server

privilege alone.

Question No : 73

I created a new group and removed the Browse Repository privilege from the group. Why does

every user in the group still have that privilege?

Answer :

Privileges granted to individual users take precedence over any group restrictions. Browse

Repository is a default privilege granted to all new users and groups. Therefore, to remove the

privilege from users in a group, you must remove the privilege from the group, and every user in

the group.

Question No : 74

After creating users and user groups, and granting different sets of privileges, I find that none of

the repository users can perform certain tasks, even the Administrator.

Answer :

Repository privileges are limited by the database privileges granted to the database user who

created the repository. If the database user (one of the default users created in the Administrators

group) does not have full database privileges in the repository database, you need to edit the

database user to allow all privileges in the database.

Question No : 75

What are the different types of locks?

Answer :

There are five kinds of locks on repository objects:

?Read lock. Created when you open a repository object in a folder for which you do not have write

permission. Also created when you open an object with an existing write lock.

?Write lock. Created when you create or edit a repository object in a folder for which you have

write permission.

?Execute lock. Created when you start a session or batch, or when the Informatica Server starts a

scheduled session or batch.

?Fetch lock. Created when the repository reads information about repository objects from the

database.

?Save lock. Created when you save information to the repository.

Question No : 76

What is Local Repository?

Answer :

Each local repository in the domain can connect to the global repository and use objects in its

shared folders. A folder in a local repository can be copied to other local repositories while keeping

all local and global shortcuts intact.

Question No : 77

What is a Global repository?

Answer :

The centralized repository in a domain, a group of connected repositories. Each domain can

contain one global repository. The global repository can contain common objects to be shared

throughout the domain through global shortcuts. Once created, you cannot change a global

repository to a local repository. You can promote an existing local repository to a global repository.

Question No : 78

When should you create the dynamic data store? Do you need a DDS at all?

Answer :

To decide whether you should create a dynamic data store (DDS), consider the following issues:

?How much data do you need to store in the DDS? The one principal advantage of data marts is

the selectivity of information included in it. Instead of a copy of everything potentially relevant from

the OLTP database and flat files, data marts contain only the information needed to answer

specific questions for a specific audience (for example, sales performance data used by the sales

division). A dynamic data store is a hybrid of the galactic warehouse and the individual data mart,

since it includes all the data needed for all the data marts it supplies. If the dynamic data store

contains nearly as much information as the OLTP source, you might not need the intermediate

step of the dynamic data store. However, if the dynamic data store includes substantially less than

all the data in the source databases and flat files, you should consider creating a DDS staging

area.

?

?What kind of standards do you need to enforce in your data marts? Creating a DDS is an

important technique in enforcing standards. If data marts depend on the DDS for information, you

can provide that data in the range and format you want everyone to use. For example, if you want

all data marts to include the same information on customers, you can put all the data needed for

this standard customer profile in the DDS. Any data mart that reads customer data from the DDS

should include all the information in this profile.

?

?How often do you update the contents of the DDS? If you plan to frequently update data in data

marts, you need to update the contents of the DDS at least as often as you update the individual

data marts that the DDS feeds. You may find it easier to read data directly from source databases

and flat file systems if it becomes burdensome to update the DDS fast enough to keep up with the

needs of individual data marts. Or, if particular data marts need updates significantly faster than

others, you can bypass the DDS for these fast update data marts.

?

?Is the data in the DDS simply a copy of data from source systems, or do you plan to reformat this

information before storing it in the DDS? One advantage of the dynamic data store is that, if you

plan on reformatting information in the same fashion for several data marts, you only need to

format it once for the dynamic data store. Part of this question is whether you keep the data

normalized when you copy it to the DDS.

?

?How often do you need to join data from different systems? On occasion, you may need to join

records queried from different databases or read from different flat file systems. The more

frequently you need to perform this type of heterogeneous join, the more advantageous it would

be to perform all such joins within the DDS, then make the results available to all data marts that

use the DDS as a source.

Question No : 79

What is Dynamic Data Store?

Answer :

The need to share data is just as pressing as the need to share metadata. Often, several data

marts in the same organization need the same information. For example, several data marts may

need to read the same product data from operational sources, perform the same profitability

calculations, and format this information to make it easy to review.

If each data mart reads, transforms, and writes this product data separately, the throughput for the

entire organization is lower than it could be. A more efficient approach would be to read,

transform, and write the data to one central data store shared by all data marts. Transformation is

a processing-intensive task, so performing the profitability calculations once saves time.

Therefore, this kind of dynamic data store (DDS) improves throughput at the level of the entire

organization, including all data marts. To improve performance further, you might want to capture

incremental changes to sources. For example, rather than reading all the product data each time

you update the DDS, you can improve performance by capturing only the inserts, deletes, and

updates that have occurred in the PRODUCTS table since the last time you updated the DDS.

The DDS has one additional advantage beyond performance: when you move data into the DDS,

you can format it in a standard fashion. For example, you can prune sensitive employee data that

should not be stored in any data mart. Or you can display date and time values in a standard

format. You can perform these and other data cleansing tasks when you move data into the DDS

instead of performing them repeatedly in separate data marts.

Question No : 80

What are Target definitions?

Answer :

Detailed descriptions for database objects, flat files, Cobol files, or XML files to receive

transformed data. During a session, the Informatica Server writes the resulting data to session

targets. Use the Warehouse Designer tool in the Designer to import or create target definitions.

Question No : 81

What are Source definitions?

Answer :

Detailed descriptions of database objects (tables, views, synonyms), flat files, XML files, or Cobol

files that provide source data. For example, a source definition might be the complete structure of

the EMPLOYEES table, including the table name, column names and datatypes, and any

constraints applied to these columns, such as NOT NULL or PRIMARY KEY. Use the Source

Analyzer tool in the Designer to import and create source definitions.

Question No : 82

What are Shortcuts?

Answer :

We can create shortcuts to objects in shared folders. Shortcuts provide the easiest way to reuse

objects. We use a shortcut as if it were the actual object, and when we make a change to the

original object, all shortcuts inherit the change.

Shortcuts to folders in the same repository are known as local shortcuts. Shortcuts to the global

repository are called global shortcuts.

We use the Designer to create shortcuts.

Question No : 83

What are Sessions and Batches?

Answer :

Sessions and batches store information about how and when the Informatica Server moves data

through mappings. You create a session for each mapping you want to run. You can group several

sessions together in a batch. Use the Server Manager to create sessions and batches.

Question No : 84

What are Reusable transformations?

Answer :

You can design a transformation to be reused in multiple mappings within a folder, a repository, or

a domain. Rather than recreate the same transformation each time, you can make the

transformation reusable, then add instances of the transformation to individual mappings. Use the

Transformation Developer tool in the Designer to create reusable transformations.

Question No : 85

What are Transformations?

Answer :

A transformation generates, modifies, or passes data through ports that you connect in a mapping

or mapplet. When you build a mapping, you add transformations and configure them to handle

data according to your business purpose. Use the Transformation Developer tool in the Designer

to create transformations.

Question No : 86

What are mapplets?

Answer :

You can design a mapplet to contain sets of transformation logic to be reused in multiple

mappings within a folder, a repository, or a domain. Rather than recreate the same set of

transformations each time, you can create a mapplet containing the transformations, then add

instances of the mapplet to individual mappings. Use the Mapplet Designer tool in the Designer to

create mapplets.

Question No : 87

What are mappings?

Answer :

A mapping specifies how to move and transform data from sources to targets. Mappings include

source and target definitions and transformations. Transformations describe how the Informatica

Server transforms data. Mappings can also include shortcuts, reusable transformations, and

mapplets. Use the Mapping Designer tool in the Designer to create mappings.

Question No : 88

What are folders?

Answer :

Folders let you organize your work in the repository, providing a way to separate different types of

metadata or different projects into easily identifiable areas.

Question No : 89

What is a metadata?

Answer :

Designing a data mart involves writing and storing a complex set of instructions. You need to know

where to get data (sources), how to change it, and where to write the information (targets).

PowerMart and PowerCenter call this set of instructions metadata. Each piece of metadata (for

example, the description of a source table in an operational database) can contain comments

about it.

In summary, Metadata can include information such as mappings describing how to transform

source data, sessions indicating when you want the Informatica Server to perform the

transformations, and connect strings for sources and targets.

Question No : 90

What are different kinds of repository objects? And what it will contain?

Answer :

Repository objects displayed in the Navigator can include sources, targets, transformations,

mappings, mapplets, shortcuts, sessions, batches, and session logs.

Question No : 91

What are different kinds of repository objects? And what it will contain?

Answer :

Repository objects displayed in the Navigator can include sources, targets, transformations,

mappings, mapplets, shortcuts, sessions, batches, and session logs.

Question No : 92

What is a repository?

Answer :

The Informatica repository is a relational database that stores information, or metadata, used by

the Informatica Server and Client tools. The repository also stores administrative information such

as usernames and passwords, permissions and privileges, and product version.

We create and maintain the repository with the Repository Manager client tool. With the

Repository Manager, we can also create folders to organize metadata and groups to organize

users.

Question No : 93

What are the new features and enhancements in PowerCenter 5.1?

Answer :

The major features and enhancements to PowerCenter 5.1 are:

a) Performance Enhancements

?High precision decimal arithmetic. The Informatica Server optimizes data throughput to increase

performance of sessions using the Enable Decimal Arithmetic option.

?To_Decimal and Aggregate functions. The Informatica Server uses improved algorithms to

increase performance of To_Decimal and all aggregate functions such as percentile, median, and

average.

?Cache management. The Informatica Server uses better cache management to increase

performance of Aggregator, Joiner, Lookup, and Rank transformations.

?Partition sessions with sorted aggregation. You can partition sessions with Aggregator

transformation that use sorted input. This improves memory usage and increases performance of

sessions that have sorted data.

b) Relaxed Data Code Page Validation

When enabled, the Informatica Client and Informatica Server lift code page selection and

validation restrictions. You can select any supported code page for source, target, lookup, and

stored procedure data.

c) Designer Features and Enhancements

?Debug mapplets. You can debug a mapplet within a mapping in the Mapping Designer. You can

set breakpoints in transformations in the mapplet.

?Support for slash character (/) in table and field names. You can use the Designer to import

source and target definitions with table and field names containing the slash character (/). This

allows you to import SAP BW source definitions by connecting directly to the underlying database

tables.

d) Server Manager Features and Enhancements

?Continuous sessions. You can schedule a session to run continuously. A continuous session

starts automatically when the Load Manager starts. When the session stops, it restarts

immediately without rescheduling. Use continuous sessions when reading real time sources, such

as IBM MQSeries.

?Partition sessions with sorted aggregators. You can partition sessions with sorted aggregators in

a mapping.

?Register multiple servers against a local repository. You can register multiple PowerCenter

Servers against a local repository.

Question No : 94

What is the difference between PowerCenter and PowerMart?

Answer :

With PowerCenter, you receive all product functionality, including the ability to register multiple

servers, share metadata across repositories, and partition data.

A PowerCenter license lets you create a single repository that you can configure as a global

repository, the core component of a data warehouse.

PowerMart includes all features except distributed metadata, multiple registered servers, and data

partitioning. Also, the various options available with PowerCenter (such as PowerCenter

Integration Server for BW, PowerConnect for IBM DB2, PowerConnect for IBM MQSeries,

PowerConnect for SAP R/3, PowerConnect for Siebel, and PowerConnect for PeopleSoft) are not

available with PowerMart.

Question No : 95

Why do we need SQL overrides in Lookup transformations?

Answer :

In order to lookup more than one value from one table, we go for SQL overrides in Lookups.

Question No : 96

What is session?

Answer :

A session is a set of instructions to move data from sources to targets.

Question No : 97

What is workflow?

Answer :

A workflow is a set of instructions that tells the Informatica server how to execute the tasks.

Question No : 98

What is worklet?

Answer :

Worklet is an object that represents a set of tasks.

Question No : 99

Which ETL tool is more preferable Informatica or Data Stage and why?

Answer :

Preference of an ETL tool depends on affordability and functionality. It is mostly a tradeoff

between the price and feature. While Informatica has been a market leader since the past many

years, DataStage is beginning to pick up momentum.

Question No : 100

What is a mapplet?

Answer :

Mapplet is the set of reusable transformation.

Question No : 101

What is the use of auxiliary mapping?

Answer :

Auxiliary mapping reflects change in one table whenever there is a change in the other table.

Question No : 102

What is authenticator?

Answer :

It validates user name and password to access the PowerCenter repository.

Question No : 103

How do we create primary key only on odd numbers?

Answer :

To create primary key, we use sequence generator and set the 'Increment by' property of

sequence generator to 2

Question No : 104

What is the difference between source qualifier transformation and application source qualifier

transformation?

Answer :

Source qualifier transformation extracts data from RDBMS or from a single flat file system.

Application source qualifier transformation extracts data from application sources like ERP.

Question No : 105

What are the types of loading in Informatica?

Answer :

There are two types of loading, normal loading and bulk loading. In normal loading, it loads record

by record and writes log for that. It takes comparatively a longer time to load data to the target in

normal loading. But in bulk loading, it loads number of records at a time to target database. It

takes less time to load data to target.

Question No : 106

What is the use of control break statements?

Answer :

They execute a set of codes within the loop and endloop.

Question No : 107

What is the difference between active transformation and passive transformation?

Answer :

An active transformation can change the number of rows that pass through it, but a passive

transformation can not change the number of rows that pass through it.

Question No : 108

What are the various types of transformation?

Answer :

Various types of transformation are: Aggregator Transformation, Expression Transformation, Filter

Transformation, Joiner Transformation, Lookup Transformation, Normalizer Transformation, Rank

Transformation, Router Transformation, Sequence Generator Transformation, Stored Procedure

Transformation, Sorter Transformation, Update Strategy Transformation, XML Source Qualifier

Transformation, Advanced External Procedure Transformation, External Transformation.

Question No : 109

What is the use of tracing levels in transformation?

Answer :

Tracing levels store information about mapping and transformations.

Question No : 110

What is the difference between a Database and a Datawarehouse?

Answer :

Database is a place where data is taken as base to data access to retrieve and load data,

whereas, a data warehouse is a place where application data is managed for analysis and

reporting services. Database stores data in the form of tables and columns. On the contrary, in a

data warehouse, data is subject oriented and stored in the form of dimensions and packages

which are used for analysis purpose. In short, we must understand that a database is used for

running an enterprise but a data warehouse helps in how to run an enterprise.

Question No : 111

What are the different types of OLAP TECHNOLOGY?

Answer :

Online Analytical process is of three types, they are MOLAP, HOLAP and ROLAP. MOLAP

Mulidimensional online analytical process. It is used for fast retrival of data and also for slicing and

dicing operations. It plays a vital role in easing complex calculations. ROLAP Relational online

analytical process. It has the ability to handle large amount of data. HOLAP Hybrid online

analytical process. It is a combination of both HOLAP and MOLAP.

Question No : 112

What is Data Modeling? What are the different types of Data Modeling?

Answer :

Data modeling is a process of creating data models. In other words, it is structuring and organizing

data in a uniform manner where constraints are placed within the structure.The Data structure

formed are maintained in a database management system. The Different types of Data Modeling

are: 1. Dimension Modelling 2. E-R Modelling

Question No : 113

What is the need of building a data warehouse?

Answer :

The need of building a data warehouse is that, it acts as a storage fill for a large amount of data. It

also provides end user access to a wide varity of data, helps in analyzing data more effectively

and also in generating reports. It acts as a huge repository for integrated information.

Question No : 114

What is drill-down and drill-up?

Answer :

Both drill-down and drill-up are used to explore different levels of dimensionally modeled data.

Drill-down allows the users view lower level (i.e. more detailed level) of data and drill-up allows the

users to view higher level (i.e. more summarized level) of data.

Question No : 115

What is cube?

Answer :

Cube is a multidimensional representation of data. It is used for analysis purpose. A cube gives

multiple views of data.

Question No : 116

1. What is a Data warehouse?

Answer :

A Data warehouse is a denormalized database, which stores historical data in summary level

format. It is specifically meant for heavy duty querying and analysis.

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