Effective Quality Assurance and Testing in Data Centric Projects

Testing, usually known today as quality assurance (QA), has always been recognized as an important part of the Systems Development Life Cycle (SDLC). Over time specialists have emerged whose primary orientation is to QA. Tools, infrastructures, and methodologies have also been developed to support QA. And yet, many enterprises find that QA remains a serious and often growing problem in production environments. How can it be that with decades of investment to mature the capabilities of QA, quality problems are increasing rather than decreasing?

If the QA techniques developed over the past five decades do not match the needs of modern application development activities, then we have a serious problem. There is evidence that such a problem exists. There are persistent reports in the literature that Data Warehouse (DW) initiatives have a high failure rate.