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Introduction of Informatica

Introduction of Informatica

In 1993 a software company Informatica was founded which used to provide data integration solutions. A lot of times when people say Informatica they actually mean Informatica PowerCenter. The growth trajectory of Informatica clearly depicts that It has become one of  the most important ETL tools which has taken over the market in a very short span of time.

It provides applications for the following Data Integration areas :

  • Data Migration – ERP and legacy systems consolidation, new application implementation
  • Data Synchronization – business-to-business data transfer
  • Data Warehousing
  • Data Hubs, Data Marts
  • Master Data Management (MDM)
  • Business Intelligence Reporting
  • Business Activity Monitoring (BAM)

Informatica Concepts

Following are some of the important concepts of Informatica –

Informatica Concepts

Data warehousing

data warehousing is a process of building a data warehouse which includes:

  • Business requirement analysis
  • Database design
  • ETL development and testing
  • Report development and testing

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Data acquisition

It is a process of extracting the relevant business information. Transforming data into a required business format and loading into the target system. A data acquisition is as a process containing three steps- Data extraction, Data transformation, and Data loading (ETL process).

Data extraction

It is a process of reading the data from various types of source systems. The following are type of sources which are used to define extraction.

ERP Source

  • SAP
  • Oracle applications
  • JD Edwards
  • people soft

File Sources

  • XML Files
  • Flat files

Relational Sources

  • Oracle
  • SQL Server
  • DB2
  • Sys bases

Legacy Sources

  • Main frames
  • AS 400
  • Cabal files etc

Data transformation

The process of transformation data and cleansing the data into the required business format. The following are data transformation activities takes place in the stage (temporary memory).

  • Data merging
  • Data cleansing
  • Data scrubbing
  • Data aggregation

Data merging

The process of integrating the data from multiple sources system is known as Data Merging. There are two types of data merging method which takes places in the staging

  • Horizontal merging – Horizontal Merging is the process of merging the records horizontally.
  • vertical merging – When two sources have same “meta data” then the process of merging the records is known as Vertical Merging.

Data cleansing

It is a process of changing inconsistencies and inaccuracy data. And also we can say that it is the process of removal of unwanted data from staging.

Data cleansing

Data scrubbing

It is a process of deriving new attributes & Attributes in a table column.

Data aggregation

The process of calculating the summary from detailed data. 

Data loading

The procedure of adding the data into a target system is called Data Loading. There are two types of data loading-

  • Initial load (or) delta load- We are extracting data from source system to load the data into target system first time the records are entered directly to the target system.
  • Incremental load (or) delta load- We are extracting data from the source system to load the data into destination system first time newly entered the records as well as update the records into the target system.


OLAP is a set of specification or technology which recovers the data from data warehouse and it is interface or get way between the user and database.


Types of OLAPS

  • DOLAP (Desktop OLAP) – DOLAP is used to query data from database that build by utilizing desktop databases.
  • ROLAP (Relation OLAP) – ROLAP is used to Query data from relational sources.
  • MOLAP (MULTIOLAP) – It is used to Query the data from multi dimensional sources.
  • HOLAP (hybrid HOLAP) – It is a combination ROLAP and MOLAP.

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