ETL testing stands for Extracting, Transforming and Loading from the heterogeneous data sources and into data warehouse. ETL is the three step integration process which works Extracting means locating the data and removing from the source, Transforming is the process of transporting to the required target file and Loading means load the file in the target system in the required format. This article focus on why ETL testing required, task to be performed by ETL testing, Classification of ETL testing and Process of ETL testing with detailed example.
ETL testing is process of loading data from source system to the target system.
It validates the data in the source and the target system based on the business requirement.
It is used to store data in uniform structure in data warehouse
Need to write script for automation testing process.
ETL is fast and systematic
It is also called as ETL data warehouse testing
Why ETL Testing required:-
1] Integrate all historical, day to day and other business data into centralized target system
2] To make process very efficient and speedy
3] Extraction of multiple data sources into cohesive database
4] Well planned and executed by ETL experts
List of task to be performed by ETL Testing:-
1] Review data model
2] Understand data to be used for reporting
3] Map source to target
4] Verification and validation source and target data
5] Check integrity and quality of data
6] Do performance testing on data
Classification of ETL testing:-
1] New data warehouse project
2] Adding new data source file to existing data warehouse
3] Migration of data warehouse
4] Change of business logic
5] Report testing
6] Platform migration
Process of ETL Testing:-
1] Understand business requirement
2] Test planning and estimation
3] Test data preparation and test case designing
4] Test execution
5] Summary report and result analysis
6] Test closure
In any bank, retail store has different department like sales, marketing, logistic and accounting. Each department handles customer / vender information independently and store the data in respective format (can say heterogeneous /different data source file).
Now if bank and store want to design product and marketing strategies based on historical transaction.
So ETL helps to extract all heterogeneous data source file. Transform them and load in uniform data structure in a data warehouse. It is done with the help of ETL in speedy and efficient manner.