Trying to tackle too much at one time is the best way to fail in any enterprise initiative.ĭata Product Lifecycle: define what we mean by the data product lifecycle. Start in a domain/division: this is universally agreed to in most circles. We will try to boil it down to what we have seen as most critical to get started: There are converging disciplines that, if not considered, will have at best a half-baked strategy and results. There is not a single piece of software that solves the problem. In our travels at XponentL, we have learned that to enable a Data Product strategy it is not a singular “thing” that you must create, manage, do well, etc. So, is this group of data product thinkers and believers Arthur and his Knights? Are we pursuing the Holy Grail of data through this new concept? While I would like to say yes, I see more fiction than fact in most of these discussions…just as there is potentially more fiction than fact in Arthur and his Knights. Think of Arthur and his Knights - their pursuit of righteousness was noble as their quest for the Holy Grail and commitment to protect the weak is something I think we would all agree is inspiring. But even in historical references we see hyperbole. This is no surprise, as there will inherently be some level of hyperbole and ambiguity in any new concept or idea. In the age of unlimited access to information and knowledge we need to do better. Many of these discussions have been shrouded in hyperbole, lack of detail or worse, misinformation. I have had the pleasure of listening, reading, talking, and applying the concepts around data products for a few years now.

We are now the knights who say