The net result is that BI programs spend more time on necessary non-value added activities and less time delivering value to the organization.
Organizations require a better approach to BI, which provides a greater focus on defining and delivering value, as well as principles and practices that help them deliver more, in shorter iterations, with their existing resources. However, delivering more, faster doesn’t necessarily mean better. The solution needs to incorporate the business into the design and development process, align across functional areas, and eliminate unnecessary, non-value added activity. Every BI project and program is an investment that must deliver more value than what it costs to deliver.
One approach is lean BI. My next article, entitled "How to Implement Lean BI," provides a definition and explanation of how lean BI generates customer value.
Steve Dine is the managing partner and founder of Datasource Consulting, LLC. He has extensive experience delivering and managing successful, highly scalable and maintainable data integration and business intelligence solutions. Steve combines hands-on technical experience across the entire BI project lifecycle with strong business acumen. He is the former Director of Global Data Warehousing for a major durable medical equipment manufacturing company and currently works as a consultant for Fortune 500 companies. Steve is a faculty member at The Data Warehouse Institute and a judge for the Annual TDWI Best Practices Awards. He teaches courses and presents on the topics of Lean BI, BI in the Cloud and Enabling BI for the 21st Century. Steve earned his bachelor's degree from the University of Vermont and a MBA from the University of Colorado at Boulder. Contact Steve via email at sdine@datasourceconsulting.com or on Twitter: @steve_dine
Encountering undocumented or poorly documented mapping rules is as difficult to understand as your first encounter with a foreign schema.
Or are you saying a "good" semantic layer of necessity has documentation that enables understanding on the first encounter? If so, how common would you estimate "good" semantic layers to be?