Data warehousing Basics 
 
Data warehouse is a Subject oriented, Integrated, Time variant, Non
volatile collection of data in support of management's decision making process.  
Subject Oriented  
Data warehouses are designed to help you analyze data. For example, to learn more about your company's sales data, you can build a warehouse that concentrates on sales. Using this warehouse, you can answer questions like "Who was our best customer
for this item last year?" This ability to define a data warehouse by subject matter, sales in this case makes the data warehouse subject oriented.  
Integrated  
Integration is closely related to subject orientation. Data warehouses must put data
from disparate sources into a consistent format.  They must resolve such problems as naming conflicts and inconsistencies among units of measure. When they achieve this, they are said to be integrated.  
Nonvolatile  
Nonvolatile means that, once entered into the warehouse, data should not change. This is logical because the purpose of a warehouse is to enable you to analyze what has occurred. 
 
where performance requirements demand that historical data be moved to an archive. A
data warehouse's focus on change over time is what is meant by the term time variant.  
2. How many stages in Datawarehousing? 
Data warehouse generally includes two stages  
 
ETL 
Short for extract, transform, load, three database functions that are combined into one tool    Extract -- the process of reading data from a source database. 
  Transform -- the process of converting the extracted data from its previous form
into required form 
  Load -- the process of writing the data into the target database.  
 
warehouses and also to convert databases from one format to another format.  
It is used to retrieve the data from various operational databases and is transformed into useful information and finally loaded into Datawarehousing system.  
1 INFORMATICA 
2 ABINITO 
3 DATASTAGE 
4. BODI 
 
In report generation, OLAP is used (i.e.) online analytical processing. It is a set of specification which allows the client applications in retrieving the data for analytical processing.  It is a specialized tool that sits between a database and user in order to provide various analyses of the data stored in the database.  
 
OLAP Tool is a reporting tool which generates the reports that are useful for Decision support for top level management. 
1. Business Objects 
  OLTP  OLAP 
Application Oriented (e.g., purchase order it is functionality of an application)  
Subject Oriented (subject in the
sense customer, product, item, time) 
2 
3 
Large volumes accessed at a time(millions), complex query 
6  
10 
3. What are the types of datawarehousing? 
EDW (Enterprise datawarehousing) 
  It provides a central database for decision support throughout the enterprise  
  It is a collection of DATAMARTS 
DATAMART 
 
It is a subject oriented database which supports the needs of individuals depts. in an
organizations 
  It supports particular line of business like sales, marketing etc..  
ODS (Operational data store) 
 
It is defined as an integrated view of operational database designed to support operational
monitoring 
  It is a collection of operational data sources designed to support Transaction processing  
  Data is refreshed near real-time and used for business activity  
 
What are the types of Approach in DWH?  
Bottom up approach: first we need to develop data mart then we integrate these data
mart into EDW 
Top down approach: first we need to develop EDW then form that EDW we develop data mart  Bottom up 
OLTP ETL Data mart DWH OLAP 
Top down 
Top down 
 
Bottom up 
  Planning & Designing the Data Marts without waiting for the Global warehouse design  
  Immediate results from the data marts  
 
 
  It is a Best Approach 
Data Modeling Types: 
  Conceptual Data Modeling 
1. Conceptual Data Modeling 
  Conceptual data model includes all major entities and relationships and does not contain much detailed level of information about attributes and is often used in the INITIAL
PLANNING PHASE 
  Conceptual data model is created by gathering business requirements from various
sources like business documents, discussion with functional teams, business analysts, smart management experts and end users who do the reporting on the database. Data modelers create conceptual data model and forward that model to functional team for their review. 
  Conceptual data modeling gives an idea to the functional and technical team
about how business requirements would be projected in the logical data model . 
2. Logical Data Modeling 
  This is the actual implementation and extension of a conceptual data model .
Logical data model includes all required entities, attributes, key groups, and relationships that represent business information and define business rules.  
3. Physical Data Modeling 
Logical vs. Physical Data Modeling 
Logical Data Model  Physical Data Model 
Represents business information and defines business rules
 
 
Alternate Key  Unique Constraint or Unique Index 
Inversion Key Entry  Non Unique Index 
 
Relationship  Foreign Key 
  It is an approach to develop the schema DB designs  
Types of Dimensional modeling  
  Multi star schema 
What is Star Schema? 
  The Star Schema Logical database design which contains a centrally located fact table
surrounded by at least one or more dimension tables 
 
The Dimension table contains Primary keys and the textual descriptions  
  It contain de-normalized business information 
  A Fact table contains a composite key and measures  
 
Eg: Total revenue , Product sale , Discount given, no of customers  
  To generate meaningful report the report should contain at least one dimension and one
fact table 
 
Example of Star Schema:  
Snowflake Schema 
 
The de-normalized dimension tables are spitted into a normalized dimension table  
Example of Snowflake Schema: 
 
In Snowflake schema, the example diagram shown below has 4 dimension tables, 4
 
 
Since dimension tables hold less space snow flake schema approach may be avoided.  
  Bit map indexes cannot be effectively utilized  
 
In a star schema, a dimension table will not have any parent table.  
  Whereas in a snow flake schema, a dimension table will have one or more parent tables.  
 
 
Whereas hierarchies are broken into separate tables in snow flake schema. These
hierarchies help to drill down the data from topmost hierarchies to the lowermost
hierarchies.  Star flake schema (or) Hybrid Schema  
  Hybrid schema is a combination of Star and Snowflake schema  
Multi Star schema 
 
Confirmed Dimensions are nothing but Reusable Dimensions.  
  The dimensions which u r using multiple times or in multiple data marts.  
  Those are common in different data marts  
Measure Types (or) Types of Facts  
  Additive - Measures that can be summed up across all dimensions.  
o  Ex: Sales Revenue 
  Semi Additive - Measures that can be summed up across few dimensions and not with others 
o  Ex: Current Balance 
  Non Additive - Measures that cannot be summed up across any of the dimensions. 
o  Ex: Student attendance 
 
Joins between fact and dimension tables should be based on surrogate keys  
  Users should not obtain any information by looking at these keys  
  These keys should be simple integers 
A sample data warehouse schema  WHY NEED STAGING AREA FOR DWH? 
 
Its the area where most of the ETL is done  
Data Cleansing 
  It is used to correct wrong email addresses  
It is used to identify missing data
 
Types of Dimensions: 
  Confirmed Dimensions 
Garbage Dimension or Junk Dimension   
Confirmed is something which can be shared by multiple Fact Tables or multiple Data
Marts. 
  Degenerative Dimension is something dimensional in nature but exist fact table.(Invoice
No) 
Which is neither fact nor strictly dimension attributes . These are useful for some kind of analysis. These are kept as attributes in fact table called degenerated
 
For ex, we have a fact table with customer_id, product_id, branch_id, employee_id, bill_no, and date in key section and price, quantity, amount in measure section. In this
fact table, bill_no from key section is a single value; it has no associated dimension table. Instead of creating a Separate dimension table for that single value, we can Include it in fact table to improve performance. SO here the column, bill_no is a degenerate dimension or line item
dimension. 
Can have single and multiple domains.  
It is a collection of nodes and services.  
Nodes 
A node is the logical representation of a machine in a domain  
One node in the domain acts as a gateway node to receive service requests from clients and route them to the appropriate service and node  
Integration Service: 
 
Integration Service does all the real job. It extracts data from sources, processes it
as per the business logic and loads data to targets.  
Repository Service: 
 
Repository Service is used to fetch the data from the repository and sends it back to
the requesting components (mostly client tools and integration service) 
Power Center Repository: 
 
Repository is nothing but a relational database which stores all the metadata created
in Power Center. 
Power Center Administration Console: 
This is simply a web-based administration tool you can use to administer the Power
Center installation. 
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 
• Custom 
• Expression 
• 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
relational or 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 calculations on a rowby-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. 
A. Yes. 
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. 
• DD_REJECT: If this is used the Update Strategy flags the row for rejection. Equivalent
numeric value of DD_REJECT is 3. 
Q. What are the types of loading in Informatica? 
There are two types of loading, 1. Normal loading and 2. 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 bulk loading, it loads number of records at a time to target database. It takes less
time to load data to target. 
Q. What is aggregate cache in aggregator transformation?
The aggregator stores data in the aggregate cache until it completes aggregate
calculations. When you 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.
Q. What type of repositories can be created using Informatica Repository
Manager? 
• Standalone Repository: A repository that functions individually and this is unrelated
to any other repositories. 
 
contain shared objects across the repositories in a domain. The objects are shared
through global shortcuts. 
• Local Repository: Local repository is within a domain and its not a global
repository. Local repository can connect to a global repository using global shortcuts and
can use objects in its shared folders.  
• Versioned Repository: This can either be local or global repository but it allows
version control for the repository. A versioned repository can store multiple copies, or
versions of an object. This feature allows efficiently developing, testing and deploying
metadata in the production environment. 
Q. What is a code page?  
A. A code page contains encoding to specify characters in a set of one or more
languages. The code page is selected based on source of the data. For example if source
contains Japanese text then the code page should be selected to support Japanese text.  
When a code page is chosen, the program or application for which the code page is set,
refers to a specific set of data that describes the characters the application recognizes.
This influences the way that application stores, receives, and sends character data.  
Q. Which all databases PowerCenter Server on Windows can connect to? 
A. PowerCenter Server on Windows can connect to following databases:  
• IBM DB2 
• Oracle 
• Sybase 
• Teradata 
Q. Which all databases PowerCenter Server on UNIX can connect to?  
A. PowerCenter Server on UNIX can connect to following databases:  
• IBM DB2 
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  
Transformation PL/SQL procedure name can be specified. Whenever the session is
executed, the session will call the pl/sql procedure.  
Q. What is Data Driven? 
The informatica server follows instructions coded into update strategy transformations
within the session mapping which determine how to flag records for insert, update,
delete or reject. If we do not choose data driven option setting, the informatica server
ignores all update strategy transformations in the mapping.  
Q. What are the types of mapping wizards that are provided in Informatica? 
The designer provide two mapping wizard. 
1. Getting Started Wizard - Creates mapping to load static facts and dimension tables
as well as slowly growing dimension tables.  
2. Slowly Changing Dimensions Wizard - Creates mappings to load slowly changing
dimension tables based on the amount of historical dimension data we want to keep and
the method we choose to handle historical dimension data.
Q. What is Load Manager? 
A. While running a Workflow, the PowerCenter Server uses the Load Manager 
process and the Data Transformation Manager Process (DTM)  to run the workflow
and carry out workflow tasks. When the PowerCenter Server runs a workflow, the Load
Manager performs the following tasks: 
1. Locks the workflow and reads workflow properties.  
2. Reads the parameter file and expands workflow variables.  
3. Creates the workflow log file.  
4. Runs workflow tasks. 
6. Starts the DTM to run sessions.  
7. Runs sessions from master servers. 
8. Sends post-session email if the DTM terminates abnormally.  
When the PowerCenter Server runs a session, the DTM performs the following tasks: 
1. Fetches session and mapping metadata from the repository.  
2. Creates and expands session variables.  
3. Creates the session log file.  
4. Validates session code pages if data code page validation is enabled. Checks  
Query conversions if data code page validation is disabled.  
5. Verifies connection object permissions. 
6. Runs pre-session shell commands. 
7. Runs pre-session stored procedures and SQL. 
8. Creates and runs mappings, reader, writer, and transformation threads to extract,  
transform, and load data.  
10. Runs post-session shell commands. 
11. Sends post-session email. 
Q. What is Data Transformation Manager?  
A. 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. The  
primary purpose of the DTM process is to create and manage threads that carry out  
the session tasks. 
• The DTM allocates process memory for the session and divide it into buffers. This  
is also known as buffer memory. It creates the main thread, which is called the  
master thread. The master thread creates and manages all other threads.  
• If we partition a session, the DTM creates a set of threads for each partition to  
allow concurrent processing.. When Informatica server writes messages to the  
session log it includes thread type and thread ID.  
Following are the types of threads that DTM creates:  
Master Thread - Main thread of the DTM process. Creates and manages all other  
threads. 
Mapping Thread - One Thread to Each Session. Fetches Session and Mapping  
Information. 
 
Pre and Post Session Thread - One Thread each to Perform Pre and Post Session 
Operations. 
Reader Thread - One Thread for Each Partition for Each Source Pipeline.  
Writer Thread - One Thread for Each Partition if target exist in the source pipeline  
write to the target. 
Transformation Thread - One or More Transformation Thread For Each Partition.  
Q. What is Session and Batches? 
Session - A Session Is A set of instructions that tells the Informatica Server How  
And When To Move Data From Sources To Targets. After creating the session, we  
can use either the server manager or the command line program pmcmd to start
or stop the session. 
Batches - It Provides A Way to Group Sessions For Either Serial Or Parallel Execution By
The Informatica Server. There Are Two Types Of Batches:  
1. Sequential - Run Session One after the Other.  
2. Concurrent - Run Session At The Same Time.  
Q. How many ways you can update a relational source definition and what  
are they? 
Q. What is a transformation? 
A. It is a repository object that generates, modifies or passes data.  
Q. What are the designer tools for creating transformations? 
A. Mapping designer 
A. Two ways 
2. Click the add button on the ports tab.  
Q. What are reusable transformations?  
A. A transformation that can be reused is called a reusable transformation  
They can be created using two methods:  
1. Using transformation developer 
Q. Is aggregate cache in aggregator transformation?  
A. 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. 
Q. What r the settings that u use to configure the joiner transformation? 
  Master and detail source  
 
A. Normal (Default) -- only matching rows from both master and detail  
Master outer -- all detail rows and only matching rows from master  
Detail outer -- all master rows and only matching rows from detail  
Full outer -- all rows from both master and detail (matching or non matching)  
Q. What are the joiner caches?  
A. When a Joiner transformation occurs in a session, the Informatica Server reads all the
records from the master source and builds index and data caches based on the master
rows. After building the caches, the Joiner transformation reads records  
from the detail source and performs joins.  
Q. What r the types of lookup caches? 
  Static cache: You can configure a static or read-only cache for only lookup table. By
default Informatica server creates a static cache. It caches the lookup table and lookup
values in the cache for each row that comes into the transformation. When the lookup
condition is true, the Informatica server does not update the cache while it processes the
lookup transformation. 
  Dynamic cache: If you want to cache the target table and insert new rows into cache
and the target, you can create a look up transformation to use dynamic cache. The
Informatica server dynamically inserts data to the target table.  
 
Persistent cache: You can save the lookup cache files and reuse them the next time
the Informatica server processes a lookup transformation configured to use the cache.  
 
Shared cache: You can share the lookup cache between multiple transactions. You can
share unnamed cache between transformations in the same mapping.  
Q. What is Transformation? 
A: Transformation is a repository object that generates, modifies, or passes data.  
Transformation performs specific function. They are two types of transformations:  
1. Active 
Rows, which are affected during the transformation or can change the no of rows that
pass through it. Eg: Aggregator, Filter, Joiner, Normalizer, Rank, Router, Source
qualifier, Update Strategy, ERP Source Qualifier, Advance External Procedure.  
2. Passive 
Does not change the number of rows that pass through it. Eg: Expression, External
Procedure, Input, Lookup, Stored Procedure, Output, Sequence Generator, XML Source
Qualifier. 
Q. What are Options/Type to run a Stored Procedure? 
A: Normal: During a session, the stored procedure runs where the 
transformation exists in the mapping on a row-by-row basis. This is useful for calling the
stored procedure for each row of data that passes through the mapping, such as running
a calculation against an input port. Connected stored procedures run only in normal
mode. 
Pre-load of the Source. Before the session retrieves data from the source, the stored
procedure runs. This is useful for verifying the existence of tables or performing joins of
data in a temporary table.  
Post-load of the Source. After the session retrieves data from the source, the stored
procedure runs. This is useful for removing temporary tables.  
 
Pre-load of the Target. Before the session sends data to the target, the stored
procedure runs. This is useful for verifying target tables or disk space on the target
system. 
Post-load of the Target. After the session sends data to the target, the stored
procedure runs. This is useful for re-creating indexes on the database. It must contain at
least one Input and one Output port.  
Q. What kinds of sources and of targets can be used in Informatica?  
  Sources may be Flat file, relational db or XML.  
 
Q: What is Session Process? 
A: The Load Manager process. Starts the session, creates the DTM process, and 
sends post-session email when the session completes. 
Q. What is DTM process? 
A: The DTM process creates threads to initialize the session, read, write, transform  
data and handle pre and post-session operations.  
Q. What is the different type of tracing levels? 
Tracing level represents the amount of information that Informatica Server writes
in a log file. Tracing levels store information about mapping and transformations. There
are 4 types of tracing levels supported  
1. Normal: It specifies the initialization and status information and summarization of the
success rows and target rows and the information about the skipped rows due to
transformation errors. 
2. Terse: Specifies Normal + Notification of data  
3. Verbose Initialization: In addition to the Normal tracing, specifies the location of
the data cache files and index cache files that are treated and detailed transformation
statistics for each and every transformation within the mapping.  
4. Verbose Data: Along with verbose initialization records each and every record
processed by the informatica server. 
Q. TYPES OF DIMENSIONS?  
A dimension table consists of the attributes about the facts. Dimensions store
the textual descriptions of the business. 
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. 
Degenerated Dimension:  
 
A degenerate dimension is a dimension which is derived from the fact table and
doesnt have its own dimension table. 
Eg: A transactional code in a fact table. 
Slowly changing dimension: 
Slowly changing dimensions are dimension tables that have slowly increasing  
data as well as updates to existing data.  
Q. What are the output files that the Informatica server creates during the 
session running? 
Informatica server log: Informatica server (on UNIX) creates a log for all status and  
error messages (default name: pm.server.log). It also creates an error log for error  
messages. These files will be created in Informatica home directory  
Session log file: Informatica server creates session log file for each session. It writes  
information about session into log files such as initialization process, creation of sql  
commands for reader and writer threads, errors encountered and load summary. The  
amount of detail in session log file depends on the tracing level that you set.  
Session detail file: This file contains load statistics for each target in mapping.  
Session detail includes information such as table name, number of rows written or  
rejected. You can view this file by double clicking on the session in monitor window.  
Performance detail file: This file contains information known as session performance  
details which helps you where performance can be improved. To generate this file  
select the performance detail option in the session property sheet.  
Reject file: This file contains the rows of data that the writer does not write to  
targets. 
Control file: Informatica server creates control file and a target file when you run a  
session that uses the external loader. The control file contains the information about  
the target flat file such as data format and loading instructions for the external  
loader. 
Post session email: Post session email allows you to automatically communicate  
information about a session run to designated recipients. You can create two  
different messages. One if the session completed successfully the other if the session  
fails. 
Indicator file: If you use the flat file as a target, you can configure the Informatica  
server to create indicator file. For each target row, the indicator file contains a  
number to indicate whether the row was marked for insert, update, delete or reject.  
Output file: If session writes to a target file, the Informatica server creates the  
target file based on file properties entered in the session property sheet.  
Cache files: When the Informatica server creates memory cache it also creates cache  
files. 
For the following circumstances Informatica server creates index and data cache  
files: 
Q. What is meant by lookup caches? 
 
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. 
Q. How do you identify existing rows of data in the target table using lookup 
transformation? 
A. There are two ways to lookup the target table to verify a row exists or not :  
1. Use connect dynamic cache lookup and then check the values of NewLookuprow  
Output port to decide whether the incoming record already exists in the table / cache  
or not. 
2. Use Unconnected lookup and call it from an expression transformation and check  
the Lookup condition port value (Null/ Not Null) to decide whether the incoming  
record already exists in the table or not.  
Q. What are Aggregate tables? 
Aggregate table contains the summary of existing warehouse data which is grouped to
certain levels of dimensions. Retrieving the required data from the actual table, which
have millions of records will take more time and also affects the server performance. To
avoid this we can aggregate the table to certain required level and can use it. This tables
reduces the load in the database server and increases the performance of the query and
can retrieve the result very fastly. 
Q. What is a level of Granularity of a fact table? 
Level of granularity means level of detail that you put into the fact table in a data
warehouse. For example: Based on design you can decide to put the sales data in each
transaction. Now, level of granularity would mean what detail you are willing to put for
each transactional fact. Product sales with respect to each minute or you want to
aggregate it upto minute and put that data.  
Q. What is session? 
A session is a set of instructions to move data from sources to targets.  
Q. What is worklet? 
Worklet are objects that represent a set of workflow tasks that allow to reuse a set of
workflow logic in several window. 
Use of Worklet: You can bind many of the tasks in one place so that they can easily get
identified and also they can be of a specific purpose. 
Q. What is workflow? 
A workflow is a set of instructions that tells the Informatica server how to execute the
tasks. 
Q. Why cannot we use sorted input option for incremental aggregation? 
In incremental aggregation, the aggregate calculations are stored in historical cache on
the server. In this historical cache the data need not be in sorted order. If you give
sorted input, the records come as presorted for that particular run but in the historical
cache the data may not be in the sorted order. That is why this option is not allowed.  
Q. What is target load order plan?  
 
You specify the target loadorder based on source qualifiers in a mapping. If you have the
multiple source qualifiers connected to the multiple targets, you can designate the order
in which informatica server loads data into the targets.  
The Target load Plan defines the order in which data extract from source qualifier
transformation. In Mappings (tab) – Target Load Order Plan 
Q. What is constraint based loading? 
Constraint based load order defines the order of loading the data into the multiple
targets based on primary and foreign keys constraints. 
Set the option is: Double click the session 
Configure Object –> check the Constraint Based Loading  
Q. What is the status code in stored procedure transformation? 
Status code provides error handling for the informatica server during the session. The
stored procedure issues a status code that notifies whether or not stored procedure
completed successfully. This value cannot see by the user. It only used by the
informatica server to determine whether to continue running the session or stop.  
Q. Define Informatica Repository? 
The Informatica repository is a relational database that stores information, or metadata,
used by the Informatica Server and Client tools. 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. 
The repository also stores administrative information such as usernames and passwords,
permissions and privileges, and product version. 
Use repository manager to create the repository. The Repository Manager connects to
the repository database and runs the code needed to create the repository tables. These
tables stores metadata in specific format the informatica server, client tools use.  
Q. What is a metadata? 
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. 
 
It is a web based application that enables you to run reports against repository
metadata. With a Meta data reporter you can access information about your repository
without having knowledge of sql, transformation language or underlying tables in the
repository. 
Q. What are the types of metadata that stores in repository? 
Source definitions. Definitions of database objects (tables, views, synonyms) or files
that provide source data.
Target definitions. Definitions of database objects or files that contain the
target data. Multi-dimensional metadata. Target definitions that are configured as cubes
and dimensions.
Mappings. A set of source and target definitions along with transformations containing
business logic that you build into the transformation. These are the instructions that the
Informatica Server uses to transform and move data.
Reusable transformations. Transformations that you can use in multiple mappings.
Mapplets. A set of transformations that you can use in multiple mappings.
Sessions and workflows. Sessions and workflows store information about how and
when the Informatica Server moves data. A workflow is a set of instructions that
describes how and when to run tasks related to extracting, transforming, and loading
data. A session is a type of task that you can put in a workflow. Each session
 
  Transformations 
Q. How can we store previous session logs?  Go to Session Properties –> Config Object –> Log Options 
Select the properties as follows…. 
Save session log by –> SessionRuns 
Save session log for these runs –> Change the number that you want to save the number of log files (Default is 0)  
If you want to save all of the logfiles created by every run, and then select the option  
Save session log for these runs –> Session TimeStamp 
You can find these properties in the session/workflow Properties.  
Q. What is Changed Data Capture? 
Changed Data Capture (CDC) helps identify the data in the source system that has
changed since the last extraction. With CDC data extraction takes place at the same time
the insert update or delete operations occur in the source tables and the change data is
stored inside the database in change tables.  
The change data thus captured is then made available to the target systems in a
controlled manner. 
Q. What is an indicator file? and how it can be used? 
 
file to the directory local to the Informatica Server. Server waits for the indicator file to
appear before running the session. 
Q. What is audit table? and What are the columns in it? 
Audit Table is nothing but the table which contains about your workflow names and
session names. It contains information about workflow and session status and their
details. 
  WKFL_RUN_ID 
ROW_REJECT_CNT 
Q. If session fails after loading 10000 records in the target, how can we load
10001th record when we run the session in the next time? 
Select the Recovery Strategy in session properties as “Resume from the last check
point “. Note – Set this property before running the session 
Q. Informatica Reject File – How to identify rejection reason 
D - Valid data or Good Data. Writer passes it to the target database. The target
accepts it unless a database error occurs, such as finding a duplicate key while inserting.  
O - Overflowed Numeric Data. Numeric data exceeded the specified precision or scale
for the column. Bad data, if you configured the mapping target to reject overflow or
truncated data. 
N - Null Value. The column contains a null value. Good data. Writer passes it to the
target, which rejects it if the target database does not accept null values.  
T - Truncated String Data. String data exceeded a specified precision for the column,
so the Integration Service truncated it. Bad data, if you configured the mapping target to
reject overflow or truncated data. 
Also to be noted that the second column contains column indicator flag value „D which
signifies that the Row Indicator is valid.  
Now let us see how Data in a Bad File looks like:  
0,D,7,D,John,D,5000.375,O,,N,BrickLand Road Singapore,T 
Q. What is “Insert Else Update” and “Update Else  Insert”?  These options are used when dynamic cache is enabled.  
  Insert Else Update option applies to rows entering the lookup transformation with the
row type of insert. When this option is enabled the integration service inserts new rows in the cache and updates existing rows. When disabled, the Integration Service does not update existing rows. 
  Update Else Insert option applies to rows entering the lookup transformation with the
 
Q. What are the Different methods of loading Dimension tables? 
Conventional Load - Before loading the data, all the Table constraints will be checked
against the data. 
Direct load (Faster Loading) - All the Constraints will be disabled. Data will be loaded
directly. Later the data will be checked against the table constraints and the bad data
wont be indexed. 
The different commit intervals are:  
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.    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.  
Q. How to add source flat file header into target file? 
Edit Task-->Mapping-->Target-->Header Options--> Output field names 
Q. How to load name of the file into relation target? 
Source Definition-->Properties-->Add currently processed file name port  Q. How to return multiple columns through un-connect lookup? 
Suppose your look table has f_name,m_name,l_name and you are using unconnected lookup. In override SQL of lookup use f_name||~||m_name||~||l_name you can easily get this value using unconnected lookup in expression. Use substring function in expression transformation to separate these three columns and make then individual port for downstream transformation /Target.  ----------------------------------------------------------------------------------------- 
Q. What is Factless fact table? In which purpose we are using this in our DWH projects? Plz give me the proper answer?  
It is a fact table which does not contain any measurable data. 
EX: Student attendance fact (it contains only Boolean values, whether student
attended class or not ? Yes or No.) 
A Factless fact table contains only the keys but there is no measures or in other
way we can say that it contains no facts. Generally it is used to integrate the
fact tables 
Factless fact table contains only foreign keys. We can have two kinds of
aggregate functions from the factless fact one is count and other is distinct
count. 
1. Coverage: to indicate what did NOT happen. Like to
Like: which product did not sell well in a particular region? 
2. Event tracking: To know if the event took place or not.
Like: Fact for tracking students attendance will not contain any measures. 
Q. What is staging area? 
 
Staging area is nothing but to apply our logic to extract the data from source
and cleansing the data and put the data into meaningful and summaries of the
data for data warehouse. 
Q. What is constraint based loading  
Constraint based load order defines the order of loading the data into the
multiple targets based on primary and foreign keys constraints.  Q. Why union transformation is active transformation?  
the only condition for a transformation to bcum active is row number changes.  Now the thing is how a row number can change. Then there are  2 conditions:  1. either the no of rows coming in and going out is diff.  eg: in case of filter we have the data like  id name dept row_num 
1 aa 4 1  2 bb 3 2  3 cc 4 3  and we have a filter condition like dept=4 then the o/p wld  b like 
id name dept row_num 
So row num changed and it is an active transformation 
2. or the order of the row changes  eg: when Union transformation pulls in data, suppose we have  2 sources  sources1:  id name dept row_num 
1 aa 4 1  2 bb 3 2  3 cc 4 3  source2:  id name dept row_num 
4 aaa 4 4  5 bbb 3 5  6 ccc 4 6 
it never restricts the data from any source so the data can  come in any manner 
id name dept row_num old row_num 
 
so the row_num are changing . Thus we say that union is an active transformation  
Q. What is use of batch file in informatica? How many types of batch file
in informatica? 
With the batch file, we can run sessions either in sequential or in concurrently. 
Grouping of Sessions is known as Batch. 
Two types of batches: 
2)Concurrent: Run the Sessions at the same time. 
If u have sessions with source-target dependencies u have to go for sequential
batch to start the sessions one after another. If u have several independent
sessions u can use concurrent batches Which run all the sessions at the same
time 
Q. What is joiner cache? 
When we use the joiner transformation an integration service maintains the
cache, all the records are stored in joiner cache. Joiner caches have 2 types of
cache 1.Index cache 2. Joiner cache.
Index cache stores all the port values which are participated in the join condition
and data cache have stored all ports which are not participated in the join
condition. Q. What is the location of parameter file in Informatica?  
$PMBWPARAM 
Q. How can you display only hidden files in UNIX 
$ ls -la  total 16  8 drwxrwxrwx 2 zzz yyy 4096 Apr 26 12:00 ./  8 drwxrwxrwx 9 zzz yyy 4096 Jul 31 16:59 ../ 
Correct answer is 
ls -a|grep "^\."  $ls -a 
Q. How to delete the data in the target table after loaded. 
SQ---> Properties tab-->Post SQL delete from target_tablename
SQL statements executed using the source database connection, after a pipeline is run write post sql in target table as truncate table name. we have the property in session truncate option. 
Q. What is polling in informatica? 
It displays the updated information about the session in the monitor window.
The monitor window displays the status of each session when you poll the
 
Session level property error handling mention condition stop on errors: 10
--->Config object –> Error Handling –> Stop on errors  Q. How can we calculate fact table size?  
A fact table is multiple of combination of dimension tables
ie if we want 2 find the fact table size of 3years of historical date with 200 products and 200 stores  3*365*200*200=fact table size  Q. Without using emailtask how will send a mail from informatica?  
by using 'mailx' command in unix of shell scripting  Q. How will compare two mappings in two different repositories? 
in the designer client , goto mapping tab there is one option that is 'compare', here we will compare two mappings in two different
repository 
in informatica designer go to mapping tab--->compare.. 
we can compare 2 folders within the same repository ..  we can compare 2 folders within different repository .. 
Q. What is constraint based load order  
Constraint based load order defines the order in which data loads into the
multiple targets based on primary key and foreign key relationship.  Q. What is target load plan 
Suppose i have 3 pipelines in a single mapping designer 
emp source--->sq--->tar1  dept source--->sq--->tar2  bonus source--->sq--->tar3 
my requirement is to load first in tar2 then tar1 and then finally tar3 
for this type of loading to control the extraction of data from source by source qualifier we use target load plan. 
Q. What is meant by data driven.. in which scenario we use that..? 
Data driven is available at session level. it says that when we r using update strategy t/r ,how the integration service fetches the data and how to update/insert row in the database log.  Data driven is nothing but instruct the source rows that should take action on target i.e(update,delete,reject,insert). If we use the update strategy transformation in a mapping then will select the data driven option in session.  Q. How to run workflow in unix?
Syntax: pmcmd startworkflow -sv <service name> -d <domain name> -u <user name> -p <password> -f <folder name> <workflow name> 
Example  Pmcmd start workflow –service  ${INFA_SERVICE} -domain ${INFA_DOMAIN} -uv xxx_PMCMD_ID -pv PSWD -folder
 
${ETLFolder} -wait ${ETLWorkflow} \   Q. What is the main difference between a Joiner Transformation and Union
Transformation? 
Joiner Transformation merge horizontally  Union Transformation merge vertically 
A joiner Transformation is used to join data from hertogenous database ie (Sql database and flat file) where has Union transformation is used to join data from the same relational sources.....(oracle table and another Oracle table) 
Join Transformation combines data record horizontally based on join condition.  And combine data from two different sources having different metadata.  Join transformation supports heterogeneous, homogeneous data source. 
Union Transformation combines data record vertically from multiple sources,
having same metadata.  Union transformation also support heterogeneous data source.  Union transformation functions as UNION ALL set operator. 
Q. What is constraint based loading exactly? And how to do this? I think it is when we have primary key-foreign key relationship. Is it correct? 
Constraint Based Load order defines load the data into multiple targets depend on the primary key foreign key relation. 
set the option is: Double click the session  Configure Object check the Constraint Based Loading 
Q. Difference between top down(w.h inmon)and bottom up(ralph kimball)approach?  Top Down approach:- 
As per W.H.INWON, first we need to build the Data warehouse after that we need to build up the DataMart but this is so what difficult to maintain the DWH. 
Bottom up approach;- 
As per Ralph Kimbal, first we need to build up the Data Marts then we need to build up the Datawarehouse..  this approach is most useful in real time while creating the Data warehouse. 
Q. What are the different caches used in informatica? 
  Static cache 
  Dynamic cache 
  Shared cache 
  Persistent cache 
 
Q. What is the command to get the list of files in a directory in unix?  
$ls -lrt 
Q. How to import multiple flat files in to single target where there is no common column in the flat files  
in workflow session properties in Mapping tab in properties choose Source filetype - Indirect  Give the Source filename : <file_path> 
This <file_path> file should contain all the multiple files which you want to Load  Q. How to connect two or more table with single source qualifier? 
Create a Oracle source with how much ever column you want and write the join query in SQL query override. But the column order and data type should be same as in the SQL query.  Q. How to call unconnected lookup in expression transformation?  
:LKP.LKP_NAME(PORTS)  Q. What is diff between connected and unconnected lookup? 
Connected lookup: 
It is used to join the two tables  it returns multiple rows  it must be in mapping pipeline  u can implement lookup condition using connect lookup u can generate sequence numbers by enabling dynamic lookup cache. 
Unconnected lookup:  it returns single output through return port  it acts as a lookup function(:lkp)  it is called by another t/r.  not connected either source r target.  ------ 
CONNECTED LOOKUP:  >> It will participated in data pipeline  >> It contains multiple inputs and multiple outputs.  >> It supported static and dynamic cache. 
UNCONNECTED LOOKUP:  >> It will not participated in data pipeline  >> It contains multiple inputs and single output.  >> It supported static cache only. 
Q. Types of partitioning in Informatica?
Partition 5 types 
 
1.  Lookup transformation 2.  Aggregator transformation  3.  Rank transformation  4.  Sorter transformation  5.  Joiner transformation 
Q. Explain about union transformation? 
A union transformation is a multiple input group transformation, which is used to
merge the data from multiple sources similar to UNION All SQL statements to
combine the results from 2 or more sql statements.
Similar to UNION All statement, the union transformation doesn't remove
duplicate rows. It is an active transformation. 
Q. Explain about Joiner transformation? 
Joiner transformation is used to join source data from two related heterogeneous
sources. However this can also be used to join data from the same source.
Joiner t/r join sources with at least one matching column. It uses a condition
that matches one or more pair of columns between the 2 sources. 
To configure a Joiner t/r various settings that we do are as below: 
1) Master and detail source 
2) Types of join 
3) Condition of the join 
Q. Explain about Lookup transformation? 
Lookup t/r is used in a mapping to look up data in a relational table, flat file,
view or synonym. 
The informatica server queries the look up source based on the look up ports in
the transformation. It compares look up t/r port values to look up source column
values based on the look up condition. 
Look up t/r is used to perform the below mentioned tasks: 
1) To get a related value. 
2) To perform a calculation. 
3) To update SCD tables. 
Q. How to identify this row for insert and this row for update in dynamic lookup
cache? 
Based on NEW LOOKUP ROW.. Informatica server indicates which one is insert and which one is update.  Newlookuprow- 0...no change  Newlookuprow- 1...Insert  Newlookuprow- 2...update 
 
Q. How will you check the bottle necks in informatica? From where do you start checking?  You start as per this order 
1.  Target  2.  Source  3.  Mapping  4.  Session  5.  System 
Q. What is incremental aggregation?  When the aggregator transformation executes all the output data will get stored in the temporary location called aggregator cache. When the next time the mapping runs the aggregator transformation runs for the new records loaded after the first run. These output values will get incremented with the values in the aggregator cache. This is called incremental aggregation. By this way we can improve performance...  ---------------------------  Incremental aggregation means applying only the captured changes in the source to aggregate calculations in a session. 
When the source changes only incrementally and if we can capture those changes, then we can configure the session to process only those changes. This allows informatica server to update target table incrementally, rather than forcing it to process the entire source and recalculate the same calculations each time you run the session. By doing this obviously the session performance increases. 
Q. How can i explain my project architecture in interview..? Tell me your project flow from source to target..? 
Project architecture is like 
1. Source Systems: Like Mainframe,Oracle,People soft,DB2. 
2. Landing tables: These are tables act like source. Used for easy to access, for
backup purpose, as reusable for other mappings. 
3. Staging tables: From landing tables we extract the data into staging tables
after all validations done on the data. 
4. Dimension/Facts: These are the tables those are used for analysis and
make decisions by analyzing the data. 
5. Aggregation tables: These tables have summarized data useful for
managers who wants to view monthly wise sales, year wise sales etc.
6. Reporting layer: 4 and 5 phases are useful for reporting developers to
generate reports. I hope this answer helps you.
Q. What type of transformation is not supported by mapplets? 
  Normalizer transformation 
  Other mapplets 
All are organized by Integration service. 
Power center talks to Integration Service and Integration service talk to session.
Session has mapping Structure. These are flow of Execution.
Q. Can every transformation reusable? How? 
Except source qualifier transformation, all transformations support reusable
property. Reusable transformation developed in two ways. 
1. In mapping which transformation do you want to reuse, select the
transformation and double click on it, there you got option like make it as
reusable transformation
option. There you need to check the option for converting non reusable to
reusable transformation. but except for source qualifier trans. 
2. By using transformation developer 
Q. What is Pre Sql and Post Sql? 
Pre SQL means that the integration service runs SQL commands against the
source database before it reads the data from source. 
Post SQL means integration service runs SQL commands against target
database after it writes to the target. 
Q. Insert else update option in which situation we will use? 
if the source table contain multiple records .if the record specified in the
associated port to insert into lookup cache. it does not find a record in the
lookup cache when it is used find the particular record & change the data in the
associated port.  ---------------------- 
We set this property when the lookup TRFM uses dynamic cache and the session property TREAT SOURCE ROWS AS "Insert" has been set.  -------------------- 
This option we use when we want to maintain the history. 
If records are not available in target table then it inserts the records in to target and records are available in target table then it updates the records. 
Q. What is an incremental loading? in which situations we will use incremental loading? 
Incremental Loading is an approach. Let suppose you a mapping for load the
data from employee table to a employee_target table on the hire date basis.
Again let suppose you already move the employee data from source to target up
 
on employee_target today. Your target already have the data of that employees
having hire date up to 31-12-2009.so you now pickup the source data which are
hiring from 1-1-2010 to till date. That's why you needn't take the data before
than that date, if you do that wrongly it is overhead for loading data again in
target which is already exists. So in source qualifier you filter the records as per
hire date and you can also parameterized the hire date that help from which
date you want to load data upon target. 
This is the concept of Incremental loading. 
Q. What is target update override? 
By Default the integration service updates the target based on key columns. But
we might want to update non-key columns also, at that point of time we can
override the
UPDATE statement for each target in the mapping. The target override affects
only when the source rows are marked as update by an update strategy in the
mapping. 
Mapping parameter: Mapping parameter is constant values that can be
defined before mapping run. A mapping parameter reuses the mapping for
various constant values.
Mapping variable: Mapping variable is represent a value that can be change
during the mapping run that can be stored in repository the integration service
retrieve that value from repository and incremental value for next run. 
 
  for eg: the file contains the records with column  empno sal  100 1000  200(repeated rows) 2000  200 3000  300 4000  400 5000 500 6000
Rank : 
select rank() over (partition by empno order by sal) from emp 
1  2  2  4  5  6 
Dense Rank  select dense_rank() over (partition by empno order by sal) from emp  and dense rank gives 
1  2  2  3  4  5 
Q. What is the incremental aggregation? 
The first time you run an upgraded session using incremental aggregation, the
Integration Service upgrades the index and data cache files. If you want to
partition a session using a mapping with incremental aggregation, the
Integration Service realigns the index and data cache files. 
Q. What is session parameter? 
Parameter file is a text file where we can define the values to the parameters
.session parameters are used for assign the database connection values 
Q. What is mapping parameter? 
A mapping parameter represents a constant value that can be defined before
mapping run. A mapping parameter defines a parameter file which is saved with
an extension.prm a mapping parameter reuse the various constant values. 
Q. What is parameter file? 
A parameter file can be a text file. Parameter file is to define the values for
 
text editor such as word pad or notepad. You can define the following values in
parameter file 
  Mapping parameters 
  Mapping variables 
  Session parameters 
Q. What is session override? 
Session override is an option in informatica at session level. Here we can
manually give a sql query which is issued to the database when the session
runs. It is nothing but over riding the default sql which is generated by a
particular transformation at mapping level. 
Q. What are the diff. b/w informatica versions 8.1.1 and 8.6.1? 
Little change in the Administrator Console. In 8.1.1 we can do all the creation of
IS and repository Service, web service, Domain, node, grid ( if we have licensed
version),In 8.6.1 the Informatica Admin console we can manage both Domain
page and security page. Domain Page means all the above like creation of IS
and repository Service, web service, Domain, node, grid ( if we have licensed
version) etc. Security page means creation of users, privileges, LDAP
configuration, Export Import user and Privileges etc. 
Q. What are the uses of a Parameter file? 
Parameter file is one which contains the values of mapping variables. 
type this in notepad.save it . 
foldername.sessionname 
$$inputvalue1= 
Parameter files are created with an extension of .PRM 
These are created to pass values those can be changed for Mapping Parameter
and Session Parameter during mapping run.
Mapping Parameters: 
A Parameter is defined in a parameter file for which a Parameter is create
already in the Mapping with Data Type , Precision and scale. 
The Mapping parameter file syntax (xxxx.prm).
[FolderName.WF:WorkFlowName.ST:SessionName]  
$$ParameterName1=Value
$$ParameterName2=Value 
After that we have to select the properties Tab of Session and Set Parameter file
name including physical path of this xxxx.prm file. 
Session Parameters: 
[FolderName.SessionName]  
$InputFileValue1=Path of the source Flat file 
After that we have to select the properties Tab of Session and Set Parameter file
name including physical path of this yyyy.prm file. 
Do following changes in Mapping Tab of Source Qualifier's
Properties section 
Attributes values
Q. What is the default data driven operation in informatica? 
This is default option for update strategy transformation. 
The integration service follows instructions coded in update strategy within
session mapping determine how to flag records for insert,delete,update,reject. If
you do not data driven option setting, the integration service ignores update
strategy transformations in the mapping. 
Q. What is threshold error in informatica? 
When the target is used by the update strategy DD_REJECT,DD_UPDATE and
some limited count, then if it the number of rejected records exceed the count
then the
session ends with failed status. This error is called Threshold Error. 
Q. SO many times i saw "$PM parser error ". What is meant by PM?  
PM: POWER MART 
1) Parsing error will come for the input parameter to the lookup.
2) Informatica is not able to resolve the input parameter CLASS for your lookup. 
3) Check the Port CLASS exists as either input port or a variable port in your
expression. 
4) Check data type of CLASS and the data type of input parameter for your
lookup. 
Q. What is a candidate key? 
A candidate key is a combination of attributes that can be uniquely used to
identify a database record without any extraneous data (unique). Each table
may have one or more candidate keys. One of these candidate keys is selected
as the table primary key else are called Alternate Key. 
Q. What is the difference between Bitmap and Btree index? 
Bitmap index is used for repeating values. 
ex: Gender: male/female 
 
Q. What is ThroughPut in Informatica? 
Thoughtput is the rate at which power centre server read the rows in bytes from
source or writes the rows in bytes into the target per second. 
You can find this option in workflow monitor. Right click on session choose
properties and Source/Target Statictics tab you can find thoughtput details
for each instance of source and target. 
Q. What are set operators in Oracle 
UNION 
MINUS 
INTERSECT 
Q. How i can Schedule the Informatica job in "Unix Cron scheduling
tool"?
Crontab 
The crontab (cron derives from chronos, Greek for time; tab stands for table)
command, found in Unix and Unix-like operating systems, is used to schedule
commands to be executed periodically. To see what crontabs are currently
running on your system, you can open a terminal and run: 
sudo crontab -l 
sudo crontab -e 
This will open a the default editor (could be vi or pico, if you want you can
change the default editor) to let us manipulate the crontab. If you save and exit
the editor, all your cronjobs are saved into crontab. Cronjobs are written in the
following format: 
Scheduling explained 
As you can see there are 5 stars. The stars represent different date parts in the
following order: 
3. day of month (from 1 to 31)
4. month (from 1 to 12)
5. day of week (from 0 to 6) (0=Sunday)
Execute every minute 
If you leave the star, or asterisk, it means every. Maybe
that's a bit unclear. Let's use the the previous example
again: 
* * * * * /bin/execute/this/script.sh 
execute /bin/execute/this/script.sh: 
4. of every month
In short: This script is being executed every minute.
Without exception. 
Execute every Friday 1AM 
So if we want to schedule the script to run at 1AM every
Friday, we would need the following cronjob: 
0 1 * * 5 /bin/execute/this/script.sh 
Get it? The script is now being executed when the system
clock hits: 
4. of month: * (every month)
5. and weekday: 5 (=Friday)
Execute on weekdays 1AM 
So if we want to schedule the script to run at 1AM every Friday, we would need
the following cronjob: 
0 1 * * 1-5 /bin/execute/this/script.sh 
Get it? The script is now being executed when the system
clock hits: 
4. of month: * (every month)
5. and weekday: 1-5 (=Monday til Friday)
Execute 10 past after every hour on the 1st of every month 
Here's another one, just for practicing 
10 * 1 * * /bin/execute/this/script.sh 
Fair enough, it takes some getting used to, but it offers great flexibility. 
Q. Can anyone tell me the difference between persistence and dynamic
caches? On which conditions we are using these caches? 
Dynamic:-- 
1)When you use a dynamic cache, the Informatica Server updates the lookup
cache as it passes rows to the target.
2)In Dynamic, we can update catch will New data also. 
3) Dynamic cache, Not Reusable 
(when we need Updated cache data, That only we need Dynamic Cache) 
Persistent:-- 
 
1)a Lookup transformation to use a non-persistent or persistent cache. The
PowerCenter Server saves or deletes lookup cache files after a successful session
based on the Lookup Cache Persistent property. 
2) Persistent, we are not able to update the catch with New data. 
3) Persistent catch is Reusable. 
---------------------------------- 
few more additions to the above answer..... 
1. Dynamic lookup allows modifying cache where as Persistent lookup does not
allow us to modify cache. 
2. Dynamic lookup use 'newlookup row', a default port in the cache but
persistent does use any default ports in cache. 
3.As session completes dynamic cache removed but the persistent cache saved
in informatica power centre server. 
Q. How to obtain performance data for individual transformations? 
There is a property at session level “Collect Performance Data “, you can select that
property. It gives you performance details for all the transformations.  
Q. List of Active and Passive Transformations in Informatica? 
Active Transformation - An active transformation changes the number of rows that
pass through the mapping. 
  Advanced External Procedure Transformation 
Passive Transformation - Passive transformations do not change the number of rows
that pass through the mapping. 
  Expression Transformation 
Q. Eliminating of duplicate records without using dynamic lookups?  
 
Select id, count (*) from seq1 group by id having count (*)>1; 
Below are the ways to eliminate the duplicate records: 
1. By enabling the option in Source Qualifier transformation as select
distinct.
2. By enabling the option in sorter transformation as select distinct. 3. By enabling all the values as group by in Aggregator transformation.  
Q. Can anyone give idea on how do we perform test load in informatica? What do we test as part of test load in informatica? 
With a test load, the Informatica Server reads and transforms data without writing to
targets. The Informatica Server does everything, as if running the full session. The
Informatica Server writes data to relational targets, but rolls back the data when the
session completes. So, you can enable collect performance details property and analyze
the how efficient your mapping is. If the session is running for a long time, you may like
to find out the bottlenecks that are existing. It may be bottleneck of type target, source,
mapping etc. 
The basic idea behind test load is to see the behavior of Informatica Server with your
session. 
Q. What is ODS (Operational Data Store)? 
A collection of operation or bases data that is extracted from operation
databases and standardized, cleansed, consolidated, transformed, and loaded
into enterprise data architecture. 
An ODS is used to support data mining of operational data, or as the store for
base data that is summarized for a data warehouse. 
The ODS may also be used to audit the data warehouse to assure summarized and
derived data is calculated properly. The ODS may further become the enterprise shared
operational database, allowing operational systems that are being reengineered to use
the ODS as there operation databases. 
Q. How many tasks are there in informatica? 
 
  Domains
  Nodes
  Services 
Q. WHAT IS VERSIONING?  
Its used to keep history of changes done on the mappings and workflows
1.  Check in: You check in when you are done with your changes so that everyone can see
those changes. 
2.  
Check out: You check out from the main stream when you want to make any change to
the mapping/workflow. 
3.  Version history: It will show you all the changes made and who made it.  
Q. Diff between $$$sessstarttime and sessstarttime? 
 
$$$SessStartTime - Returns session start time as a string value (String datatype)
SESSSTARTTIME - Returns the date along with date timestamp (Date datatype)  
Q. Difference between $,$$,$$$ in Informatica? 
 
file, $output file, $DB connection,$source,$target etc..
2. $$ Refers 
$$Business_Date, $$SRC,etc.
3. $$$ Refers 
System Parameters like $$$SessStartTime 
$$$SessStartTime returns the session start time as a string value. The format of the
string depends on the database you are using.  
$$$SessStartTime returns the session start time as a string value --> The format of the
string depends on the database you are using.  
Q. Finding Duplicate Rows based on Multiple Columns?  
SELECT firstname, COUNT(firstname), surname, COUNT(surname), email, COUNT(email)
FROM employee 
HAVING (COUNT(firstname) > 1) AND (COUNT(surname) > 1) AND (COUNT(email) >
1); 
Q. Finding Nth Highest Salary in Oracle? 
Pick out the Nth highest salary, say the 4th highest salary.  
Select * from 
(select ename,sal,dense_rank() over (order by sal desc) emp_rank from emp) 
where emp_rank=4; 
SELECT MIN(sal) FROM emp WHERE
sal IN (SELECT distinct TOP 3 sal FROM emp ORDER BY sal DESC); 
Q. How do you handle error logic in Informatica? What are the
transformations that you used while handling errors? How did you
reload those error records in target?
Row indicator: It generally happens when working with update strategy
transformation. The writer/target rejects the rows going to the target 
Column indicator: 
D -Valid 
o - Overflow 
n - Null 
t - Truncate 
When the data is with nulls, or overflow it will be rejected to write the data to
the target 
The reject data is stored on reject files. You can check the data and reload the
data in to the target using reject reload utility. 
Q. Difference between STOP and ABORT? 
Stop - If the Integration Service is executing a Session task when you issue the stop
command, the Integration Service stops reading data. It continues processing and
writing data and committing data to targets. If the Integration Service cannot finish
processing and committing data, you can issue the abort command.  
Abort - The Integration Service handles the abort command for the Session task like the
stop command, except it 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. 
Q. WHAT IS INLINE VIEW?  
An inline view is term given to sub query in FROM clause of query which can be
used as table. Inline view effectively is a named sub query 
Ex : Select Tab1.col1,Tab1.col.2,Inview.col1,Inview.Col2
Where Tab1.col1=Inview.col1 
WHERE A.DEPTNO = B.DEPTNO 
In the above query (SELECT DNAME, DEPTNO FROM DEPT) D is the inline view. 
Inline views are determined at runtime, and in contrast to normal view they are
not stored in the data dictionary, 
Disadvantage of using this is  
1. Separate view need to be created which is an overhead
2. Extra time taken in parsing of view 
This problem is solved by inline view by using select statement in sub query and
using that as table. 
1. Better query performance
1. Joining Grouped data with non grouped data
2. Getting data to use in another query 
Q. WHAT IS GENERATED KEY AND GENERATED COLUMN ID IN
The integration service increments the generated key (GK) sequence number each time
it process a source row. When the source row contains a multiple-occurring column or a
 
The normalizer transformation has a generated column ID (GCID) port for each
multiple-occurring column. The GCID is an index for the instance of the multiple-
occurring data. For example, if a column occurs 3 times in a source record, the
normalizer returns a value of 1, 2 or 3 in the generated column ID.  
Q. WHAT IS DIFFERENCE BETWEEN SUBSTR AND INSTR? 
INSTR  function search string for sub-string and returns an integer indicating the
position of the character in string that is the first character of this occurrence. 
SUBSTR  function returns a portion of string, beginning at character position,
substring_length characters long. SUBSTR calculates lengths using characters as
defined by the input character set. 
Q. WHAT ARE DIFFERENT ORACLE DATABASE OBJECTS? 
 
Q. WHAT IS @@ERROR?  
The @@ERROR automatic variable returns the error code of the last Transact-
SQL statement. If there was no error, @@ERROR returns zero. Because @@ERROR is
reset after each Transact-SQL statement, it must be saved to a variable if it is needed to
process it further after checking it. 
Q. WHAT IS DIFFERENCE BETWEEN CO-RELATED SUB QUERY AND
 
 
Correlated subquery runs once for each row selected by the outer query. It
contains a reference to a value from the row selected by the outer query. 
Nested subquery runs only once for the entire nesting (outer) query. It does
not contain any reference to the outer query row. 
For example, 
Correlated Subquery: 
(select max(basicsal) from emp e2 where e2.deptno = e1.deptno) 
Nested Subquery: 
Select empname, basicsal, deptno from emp where (deptno, basicsal) in (select
deptno, max(basicsal) from emp group by deptno) 
Q. HOW DOES ONE ESCAPE SPECIAL CHARACTERS WHEN BUILDING SQL QUERIES? 
 
The LIKE keyword allows for string searches. The „_ wild card character is used
to match exactly one character,  „% is used to match zero or more occurrences
of any characters. These characters can be escaped in SQL. Example: 
SELECT name FROM emp WHERE id LIKE „%\ _% ESCAPE „\; 
Use two quotes for every one displayed. Example: 
SELECT „Franks”s Oracle site FROM DUAL; 
SELECT „A ”quoted” word. FROM DUAL; 
SELECT „A ””double quoted”” word. FROM DUAL; 
Q. DIFFERENCE BETWEEN SURROGATE KEY AND PRIMARY KEY?  
Surrogate key:  1.  Query processing is fast. 
2.  It is only numeric 
3.  Developer develops the surrogate key using sequence generator transformation.  4.
 
4.  Eg: C10999 
Q. HOW DOES ONE ELIMINATE DUPLICATE ROWS IN AN ORACLE TABLE?  
Method 1: 
B.key_values); 
drop table table_name1;
rename table table_name2 as table_name1; 
In this method, all the indexes,constraints,triggers etc have to be re-created. 
Method 3: 
t1.key_value=t2.key_value and t1.rowid > t2.rowid) 
Method 4: 
DELETE from table_name where rowid not in (select max(rowid) from my_table
group by key_value ) 
 
select * from my_table where rownum <= n  
MINUS 
Q. How does the server recognize the source and target databases? 
If it is relational - By using ODBC connection  
FTP connection - By using flat file  
Q. WHAT ARE THE DIFFERENT TYPES OF INDEXES SUPPORTED BY ORACLE? 
1.  
There are two types of Normalizer transformation. 
VSAM Normalizer transformation 
A non-reusable transformation that is a Source Qualifier transformation for a
COBOL source. The Mapping Designer creates VSAM Normalizer columns from a
COBOL source in a mapping. The column attributes are read-only. The VSAM
Normalizer receives a multiple-occurring source column through one input port. 
Pipeline Normalizer transformation  
A transformation that processes multiple-occurring data from relational tables or
flat files. You might choose this option when you want to process multiple-
occurring data from another transformation in the mapping. 
A VSAM Normalizer transformation has one input port for a multiple-occurring
column. A pipeline Normalizer transformation