Without effective data quality management measures in place to support their data warehouses, businesses remain highly vulnerable to operational, financial and regulatory risks. Unfortunately, few companies have adequate safeguards in place for their data warehouses.
They may have conventional tools in place for validating certain types of data (such as customer names and addresses) once they’re in the data warehouse, but they often lack the controls necessary for:
• Preventing bad data from getting there in the first place
• Properly validating financial data
• Discovering and remediating the root causes of chronic data quality problems
• Documenting data quality management measures to third parties (such as auditors and regulators)
Read this paper to learn:
- The 5 primary data warehouse testing challenges, approaches and guidelines to help you address them.
- Best practices and test methodologies based on practical experiences verifying DWH/BI applications.