The data warehouse testing is also called ETL testing.
The data warehouse testing or ETL testing includes the following techniques:
- Data transformation testing: Here the data from various sources are collected and verified to transform as per the business rules .
2. Data transfer count testing: counting the target of records loaded in the data warehouse sources should match with the expected count.
3. Data transfer testing: Verifying all the data which is collected is loaded properly in the data warehouse without any loss or truncating.
4. Data Quality testing: here the quality of the data is tested it makes sure that improper and invalid data is reported and replaced with proper default values.
5. Performance Testing: Here it verifies that the data is loaded in data warehouse within the prescribed time slots to improve its performance and scalability.
6. Production data testing: Validating or checking the data in production process against the data which is in sources.
7. Data Integration Testing: Verifying that all data from the sources are loaded properly and checked in each point and then transformed properly.
8. Software Migration Testing: In this testing it is made sure that the data from the data warehouse is working efficiently in the new environment or platform.
9. Data and Constraint case check: In this type of testing data type, length, constraints are checked.
10. Data integrity testing: here it is checked for any duplicate data in the target systems.
Database testing can be often confused with data warehouse testing. Database testing is done on smaller volumes of normalised data to validate the changes that affect the data from the software application. Data warehouse testing is performed on huge volumes of data that is not normalised.
Check your understanding:
1. Identify the possible challenges in data warehouse testing.