Our data processes and systems are becoming increasingly complex, and dynamic. Many companies are struggling with maintaining data quality and increasing trust in the data landscape.
Testing offers insight into risks and quality of the data, the systems, and the dataflows. It investigates for instance the performance, the data integrity and the business logic. Much more than finding issues and bugs, testing is about providing confidence and building trust for end-users in the solution that is being built. Testing should therefore be a critical component in any business intelligence and data environment.
In this talk, I address testing knowledge targeted to data environments using TMAP and the VOICE model. I will address DAMA quality characteristics you can adopt and encourage you to communicate the level of confidence you have in the quality of your systems and data. Gain insight and tips on how to test BI & Data solutions.
Key points:
- The importance of testing
- The TMAP and VOICE model of testing
- Building confidence by providing insight into the level of quality
- Testing in a BI & Data environment by looking at:
- Data flows; looking at how the data moves through the system
- Data quality; what KPI’s can be used?
- Data profiling; how to find bugs even before the solution has been built.