by Angela Guess
Rick Sherman recently shared his thoughts on how companies often fail to connect the dots between different data management processes. He writes, “When I teach my master’s degree classes I use slides to present the theoretical, and then use workshops to illustrate how the theory applies to design and development of business intelligence solutions. In addition, I use examples or case studies to tie the theory to real world situations. This is how I connect the dots in the classroom.”
Sherman continues, “In the real world the situations I discuss or encounter in enterprise BI, data warehousing and MDM implementations lead me to the conclusion that many enterprises simply do not connect the dots. These implementations potentially involve various disciplines such as data modeling, business and data requirements gathering, data profiling, data integration, data architecture, technical architecture, BI design, data governance, master data management (MDM) and predictive analytics. Although many BI project teams have experience in each of these disciplines they’re not applying the knowledge from one discipline to another.”
He adds, “The result is knowledge silos where the the best practices and experience from one discipline is not applied in the other disciplines. The impact is a loss in productivity for all, higher long-term costs and poorly constructed solutions. This often results in solutions that are difficult to change as the business changes, don’t scale as the data volumes or numbers of uses increase, or is costly to maintain and operate.”
photo credit: jimblodget
