Data integrity can be compromised at all DWH/BI phases: when data is created, integrated, moved, or transformed. However, testing of data warehouses is usually deferred until late in the cycle. If testing is shortchanged (e.g., due to schedule overruns or limited resource availability), there’s a high risk that critical data integrity issues may slip through the verification efforts. Even if thorough testing is performed, it’s difficult and costly to address any data integrity issues exposed by this late-cycle testing.

Download this paper to explore strategies and best practices for catching data integrity issues as early as possible—to reduce the resources required to address them and ensure that data integrity issues don’t compromise the accuracy of the data that business leaders rely on. You’ll learn ways to identify quality issues in:

• Data warehouse design
• Data sources
• Each ETL phase
• Staging and loads to the data warehouse
• BI reports