Prerequisites for successful data warehousing: Consider this statement. “Implementing a formal Total Quality Management (TQM) program is required for data warehousing success.”

Introduction / Context:
Data warehousing success depends on many factors: governance, sponsorship, correct architecture, incremental delivery, and robust data quality practices. This item asks whether a formal TQM program is a mandatory prerequisite for success.

Given Data / Assumptions:

• TQM is one of several quality management frameworks (others include Six Sigma, Lean, modern data quality platforms).
• Organizations may adopt tailored quality processes without labeling them as TQM.
• Success is measured by adoption, trustworthy analytics, and business outcomes.

Concept / Approach:
A warehouse can succeed with disciplined data quality controls (profiling, rules, monitoring, stewardship) embedded in governance, regardless of whether the overarching framework is called TQM. Conversely, merely declaring TQM without effective data practices will not ensure success. Therefore, TQM may help but is not required.

Step-by-Step Solution:

Verification / Alternative check:
Case studies show success under varied frameworks; the common elements are sponsorship, governance, iterative delivery, and targeted quality controls rather than any one brand of quality program.

Why Other Options Are Wrong:

• Labeling TQM as required is too restrictive.
• “Only regulated” and “with Six Sigma” add constraints that are not universally necessary.
• Vendor tooling alone cannot guarantee quality outcomes.

Common Pitfalls:
Overemphasis on methodology branding over practical data practices; assuming a framework replaces stewardship and root-cause correction.

Final Answer:
Incorrect