Data Product Confusion

There is a lot of confusion in the marketplace about the definition of a data product. Everyone has a different opinion. Ask a vendor and you’ll get a self-serving perspective: a data product is what their product does. Ask a data developer, and they’ll say a data product is a building block that helps them build analytic solutions faster. And so on. 

The problem with all these definitions is that they describe things that data & analytics teams have delivered for decades. (See figure 1.) So what’s really new? 

When you read articles about data products, you often get a list of characteristics that constitute a data product. They are all nice characteristics, things that you would want from any data asset. (See figure 2.) But that’s the problem! 

What’s the difference between a run-of-the-mill data asset and a data product? If that’s the case, should everything we build be considered a data product? And if so, why the name change?

“There is little agreement on the definition of a data product. Most definitions describe things that have existed for decades. So what’s new?”

Clearing Up Confusion

Figure 1. What is a Data Product?


Figure 2. Generic Traits

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