Nick notes that while the article is directed at BI specialists, there are some important takeaways for SOA specialists as well. For example:
"The success of enterprise data integration hinges upon leveraging a mature information architecture and integration practices prevalent in BI, while evolving to account for recent architectural concepts, such as service-oriented architecture (SOA), to ensure the hunger for timely and meaningful information is satisfied.
Izydor and McCollum wrote that "BI and SOA architecture disciplines support similar needs: IM, metadata, data integration and data quality."
Nick also adds that the mature processes and practices already tackled by BI specialists to provide a common view of data from across enterprise stovepipes provide some great templates for SOA proponents to follow. Plus, "the natural synergy between BI and SOA can make them a strong ally in the fight for a better, faster, cheaper, and more intelligent enterprise."
I agree completely, as SOA and enterprise data management share the same challenges, and can be built around the same ROI model. They serve the same purposes, require the same type of governance structure, deliver the same kind of ROI. Most importantly, they need each other.
Consider the similarities: Both enterprise data warehouses and SOA battle the silos. Both are about getting the right information at the right time. Both emphasize "reuse" as a primary value -- SOA reuses application components that get written and validated once and deployed many times; EDW reuses data that has been written and validated once and gets deployed many times. Both require a strong, enterprise-focused governance structure that involves the business and builds support. Both need metadata repositories to succeed on an enterprise scale. Both may have negligible ROI the first time around; but economies of scale grow exponentially as assets are shared or reused.