Welcome to the land of King Arthur of Data and the Knights of the Round Table.

I have had the pleasure of listening, reading, talking, and applying the concepts around data products for a few years now. Many of these discussions have been shrouded in hyperbole, lack of detail or worse, misinformation. In the age of unlimited access to information and knowledge we need to do better.

This is no surprise, as there will inherently be some level of hyperbole and ambiguity in any new concept or idea. But even in historical references we see hyperbole. 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. 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.

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. There is not a single piece of software that solves the problem. There are converging disciplines that, if not considered, will have at best a half-baked strategy and results. We will try to boil it down to what we have seen as most critical to get started:

• Start in a domain/division: this is universally agreed to in most circles. Trying to tackle too much at one time is the best way to fail in any enterprise initiative.

• Data Product Lifecycle: define what we mean by the data product lifecycle. A key ingredient to this entire strategy is having some uniformity around how we build, manage, and consume data products.

• Data Product Anatomy & Certification: to have a product we must understand its ingredients, the processes to ensure it meets a certain level of standards and the ability to repeat the same results. Most organizations manufacture products with the proper processes, controls, and information to ensure they meet an external standard. We need to bring these same concepts to our data product lifecycle. Products have features and we need to define these key features of our data products, many of which are metadata (classification, quality, definition, etc.).

• Marketplace: if we make products but cannot market or sell them, they decrease in value! Enabling a data product marketplace which serves as the way consumers and producers interact with products is key. This entire strategy revolves around increasing the overall experience for consumers and how easily they can find answers to their questions.

• User Experience: with the Marketplace as the center of user engagement, ensure you are providing users with an intuitive, pleasurable experience with high quality results. Build the user experience muscle in your data organization and you will be surprised how much more engagement and usage you drive.

• Operating Model: your operating model must converge across data governance, data product governance and the marketplace. We strive to have a one-size fits all approach to how we operate but it is impractical in a large enterprise. Divisions and business units have different capabilities, we must have a model that meets our customers based on their level of maturity and uplevels their ability to create products on their own. Should a unit that is self-sufficient not have to work within a common framework? Should a unit with less capability be shunned from this strategy? You get the point.

• Platform: we must have a platform that supports the concepts of lifecycle, anatomy, and certification. These platforms should seamlessly interact with our marketplace, so data producers understand the key steps to create products, lowering the barrier to creation and simplifying engineering.

So, while I admire this band of Knights who so nobly speak on behalf of us, I ask them all — Have you applied these concepts? Have you thought about how you will enable this change? Have you been in the trenches thinking, applying, learning, and bringing this back to the masses? While we are not Arthur, I am confident our experience has identified what is most meaningful in making this concept a reality. Onward!!!!