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Ten Mistakes to Avoid in Test-Driven Data Warehouse Development
TDWI Member Exclusive

May 10, 2019

By Wayne Yaddow

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations as they seek to empower more and better data-driven decisions and actions throughout their enterprise. Such firms want to expand their user base for BI, data management and analytics (DM/A), and data discovery so fewer users are making uninformed decisions. Similarly, users are demanding high-quality BI reports.

This Ten Mistakes to Avoid focuses on helping organizations sidestep QA problems that many other DW projects have experienced. Tips offered will help ensure satisfaction as DW (and DM/A) teams plan and implement new functions and capabilities. These time-tested recommendations may save significant money, time, and staff resources and improve results from the DW application being developed.

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