For some reason the topic of “best practice BI” has been popping up very frequently of late. In the past 3 weeks I have been asked to speak on this topic at least 5 times. IN the hopes that I can head some of this repetitive discussion off (or at least leverage this blog with others in the future!) I thought I would take the time to at least set the framework of the discussion.

I have to be upfront on the whole “best practice” term. If there was some sort of practices that really lead to leading class BI then they would be some common as to not be “best”. The people that are doing the “best” are going beyond the normal practices and really breaking down the barriers to innovation and analytics. I hope that by sharing what these leading examples are they will become a common practice. The underlying theme is that you want to move from reporting on the business to understanding the business well enough to actually take actions that direct and cause business to occur.

Editor's note: Rob Armstrong is an employee of Teradata, a sponsor of The Smart Data Collective.

So with that off my chest I will get off my soapbox. The next comment I typically make is to create discussion around what you mean by BI? There are many flavors to this term and it gets thrown around very casually. Like many other terms in the data warehousing arena, it helps to first get everyone to agree on what each other means.

So, what do I mean by BI? I like to read an acronym backwards. BI is not about business intelligence, it is about having enough intelligence regarding your business that you can make, and take, relevant, timely, and profitable actions. Many see BI as simply reporting tools or “interactive analytic” tools. Others use the term to mean dashboards and data mining. I see the term encompassing all these areas. However, each of these purposes has some particular service level expectation and responsibility from the user community. I see it as follows: