Meeting Today's Data Management Challenges

by Peter H. Aiken

The analysis behind this report represents my 25-plus years of experience as a data manager, consultant, author, and researcher. My company, Data Blueprint, has recently completed assessments of the maturity of data management (DM) practices (for a more complete description of the assessment results, see [4]). The reality is that management, including IT management, does not understand DM; as a result, organizational management underappreciates DM's value. The lack of DM-specific knowledge is widespread, fundamental, and profoundly important. Some managers may recall taking a college course on databases. Fewer still may recall that something known as "normalization" was an important practice or can articulate how the concept of architecture provides business value. Accordingly, throughout the business slowdown that began in 2000, organizations reduced DM staff. The problem is that the vast majority of management does not understand how immature DM practices affect their business. In the face of this reality, it should not be surprising that DM is not viewed as a core best business practice. Given the renewed focus on business intelligence (BI), it is time to evolve our DM practices to support this area. When describing BI, most refer to the following processes: