There are a few more Intelligent Enterprise topics I would like to discuss before we dive into the world of DW/BI terminology and how those terms and entitiesmap to an end-to-end elegant Microsoft BI solution.
While technology is very useful and powerful it only solves the enablement piece of the Intelligent Enterprise "puzzle". Organizations must commit to change, to grow their business through strategic, value-add corporate IT initiatives. Becoming an Intelligent Enterprise does not end when a data mart and some reports are completed. Becoming an Intelligent Enterprise means committing to a cultural change whereby you empower workers with intelligence. Furthermore, you commit the organization to continuous intelligence improvement by gaining more insight into your business which will result in enriched analytics (and thus business value).
I cannot emphasize the commitment of the business side for BI projects enough. While I all too well understand that BI is implemented in technology, it is 100 percent business driven! The BI projects I've witnessed having the most success started with someone outside of IT (CXO usually) who became aware of the power and value of adopting BI and drove the "BI stake" into the corporate ground hard. Incidentally, those enterprises who lead BI by the business side are now benefiting heavily from their resulting solutions still to this day as a result. They have a significant competitive advantage as a result.
Rapid BI & Project 'Gemini'
A friend notified me today that in my recent blog post I completely left out 'Gemini' in regard to Rapid BI. So let's dive into this topic a bit... 'Gemini' will bring about a new era of Rapid BI by taking some (not all, not near all) of the development workload out of IT's hands. So yes, 'Gemini' definitely qualifies as a Rapid BI platform. There are two very different yet strongly correlated worlds of BI: Traditional and Self-Service.
Traditional BI is what I and others like me do for a living. When a company wants "BI" we step in, gather requirements from key stakeholders, and start the design sessions (which translate into many technical artifacts thereafter). We are building the "Corporate Truth" for key business processes the business wants transparency into.
Self-Service BI does not compete but rather complements Traditional BI by allowing Information Workers to build their own analytical models (most likely sourcing some of its data from a data warehouse). How does Self-Service BI complement Traditional BI? Let's say Sue in marketing creates a new self-service analytical model. Sue publishes the new model to a collaboration server. Sue's colleagues really like the analytics she has created. As a result, the business now takes this model to "us" (the BI experts) and asks us to recreate this model in a Traditional BI capacity. Voilà! I could be wrong but from what the experts at Redmond are saying, this synergy of Self-Service & Traditional BI is where more value will come...