ETL Refers to “Extraction of Data from different Applications” developed and supported by different Vendors, Managed and operated by different persons hosted on different Technologies “into Staging Tables –Transform data from Staging Tables by applying a series of rules or Functions which may include Joining and Duplication of Data, Filter and Sort the Data using specific Attributes, Transposing Data, Make Business Calculations etc. To derive the data for loading into the Destination System, Usually the Data ware House is used for Business Intelligence & Reporting Issues. ETL basically standsfor (EXTRACT TRANSFORM LOAD) which simply implies the process where you extract data from Source Tables and Transform them in to the desired Format based on certain Rules and finally load them onto Target Tables. So ETL Testing implies, Testing this entire Process using a Tool or at Table Level with the help of Test Cases and Rules Mapping Document. With the help of SQL Queries’ we need to validate Data from Source to Target.
ETL Testing / Data Warehouse Testing though is a niche area with in the Software Quality Industry it has gained much prominence in recent years.Currently 15,000 ETL Testing Job Positions are open for this exciting career PAN India.
It involves the extracting the Data from different heterogeneous data Sources.Data extraction from a Transcationl System varies as per the requirement and the ETL Tool in use.It is normally done by Running Scheduled Jobs in Off-Business hours like running jobs at night or over the weekend.
It involves Transforming the Data into a suitable Format that can be easily loaded into a DW System.Data Transformation involves applying Calculations,Joins and defining Primary and Foreign Keys on the Data. For example – if you want % of Total Revenue which is not in Database,you will apply % Formula in Transformation and Load the Data.Data Transformation also involves the Data correction and cleansing of Data, Removing incorrect Data,Incomplete Data Formation and Fixing Data errors.It also includes Data Integrity and Formatting Incompatible Data before Loading it into a DW System.
It involves loading the Data into a DW System for Analytical Reporting and Information.The Target System can be a simple Delimited Flat File or a Data warehouse.
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