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Introduction to Informatica

Informatica Introduction

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 have taken over the market in a very short span of time. Let’s move forward to understand ‘what is Informatica?’

Introduction of Informatica
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)

To understand what is Informatica in detail lets go through the important concepts of Informatica.

Informatica Concepts

Following are some of the important concepts of Informatica you’ll learn in the introduction to 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 relevant business information. Transforming data into a required business format and loading it into the target system. 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 the type of sources which are used to define extraction you’ll be learning in Informatica introduction tutorial.

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

  • Mainframes
  • AS 400
  • Cabal files etc

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Data Transformation

The process of transforming data and cleansing the data into the required business format. The following are data transformation activities take 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 the same “metadata” then the process of merging the records is known as Vertical Merging.

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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 you’ll be learning in Informatica introduction tutorial –

  • Initial load (or) delta load- We are extracting data from the source system to load the data into the 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

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

Types of OLAPS

  • DOLAP (Desktop OLAP) – DOLAP is used to query data from the 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 of ROLAP and MOLAP.

With this, we come to the end of this section of the Informatica tutorial on introduction to Informatica. Hope it helped you to understand what is Informatica.

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About the Author

Data Analyst & Machine Learning Associate

As a Data Analyst and machine learning associate, Nishtha combines her analytical skills and machine learning knowledge to interpret complicated datasets. She is also a passionate storyteller who transforms crucial findings into gripping tales that further influence data-driven decision-making in the business frontier.