June issue of DM Review magazine has an interesting article on Data Warehouse Testing. This topic has always been up for debate. Traditional testing teams want to test a Data Warehouse like any other transactional systems. Whereas Data Warehouse gurus would always suggest testing the input and output. This article lists seven goals for a successful data warehouse testing, namely;
- Data completeness. Ensures that all expected data is loaded.
- Data transformation. Ensures that all data is transformed correctly according to business rules and/or design specifications.
- Data quality. Ensures that the ETL application correctly rejects, substitutes default values, corrects or ignores and reports invalid data.
- Performance and scalability. Ensures that data loads and queries perform within expected time frames and that the technical architecture is scalable.
- Integration testing. Ensures that the ETL process functions well with other upstream and downstream processes.
- User-acceptance testing. Ensures the solution meets users' current expectations and anticipates their future expectations.
- Regression testing. Ensures existing functionality remains intact each time a new release of code is completed.