ETL tool extracts the data from all these heterogeneous data sources, transforms the data (like applying calculations, joining fields, keys, removing incorrect data fields, etc.), and loads it into a Data Warehouse. This is an introductory tutorial that explains all the fundamentals of ETL testing.
Audience : This tutorial has been designed for all those readers who want to learn the basics of ETL testing. It is especially going to be useful for all those software testing professionals who are required to perform data analysis to extract relevant information from a database.
Prerequisites : We assume the readers of this tutorial have hands-on experience of handling a database using SQL queries. In addition, it is going to help if the readers have an elementary knowledge of data warehousing concepts.
ETL testing involves the following operations −
- Validation of data movement from the source to the target system.
- Verification of data count in the source and the target system.
- Verifying data extraction, transformation as per requirement and expectation.
- Verifying if table relations – joins and keys – are preserved during the transformation.
Common ETL testing tools include QuerySurge, Informatica, etc.
Database testing stresses more on data accuracy, correctness of data and valid values. It involves the following operations −
- Verifying if primary and foreign keys are maintained.
- Verifying if the columns in a table have valid data values.
- Verifying data accuracy in columns. Example − Number of months column shouldn’t have a value greater than 12.
- Verifying missing data in columns. Check if there are null columns which actually should have a valid value.
Common database testing tools include Selenium, QTP, etc.