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Businesses, operating in an increasingly complex world, are pressured by globalization, customer demand, government regulations, market conditions, and competition. Executives must have the right data to make strategic, tactical, and operational decisions. Data warehouses, when implemented correctly, promise to meet this need by integrating and organizing key operational data in a form that is consistent, reliable, timely, and readily available, wherever and whenever needed. Unfortunately, 40% to 50% of data warehouse initiatives end in costly failure. The search for root causes converged on not understanding the user’s business problems. Rockart’s classic Critical Success Factor (CSF) method offers a proven way to move from high-level need to the lower-level data that support management decisions. While this paper summarizes the research on data warehousing implementation CSFs, its primary focus is to recommend Rockart’s CSF method as a means to address the fundamental challenge of building an effective data warehouse; namely understanding the user’s business problems and providing concise, dependable, data, information, and knowledge, about current trends and changes. The outcomes may be useful to business leaders and information technologists as they plan and implement data warehousing (DW) solutions.

CRITICAL SUCCESS FACTORS FOR DATA WAREHOUSING: A CLASSIC ANSWER TO A MODERN QUESTION