Data Demystified: Capabilities

I've written quite a bit about the need for the data function to have a product-oriented mindset, but in order to achieve it there must be a solid foundation in production capabilities.

The DAMA-DMBOK2 framework captures eleven distinct capabilities needed to be considered a "mature" data organization, and Big Tech has taken advantage of this framework to create solutions for each.  Many of these tools are wonderful, if you can afford them.

For organizations still trying to figure out their data function, I'd collapse the DAMA framework into 3 P's - Pull/Push, Prepare, Present.  Many purists will howl in dismay over this oversimplification of their deep data management mystique, but business doesn't happen in ivory towers.  It happens in the frenzied scrum of constantly changing economics and evolving technology.

The bottom line is that you need to do these 3 things to deliver even the most rudimentary data products.  They are non-negotiable.  How a given organization accomplishes them can follow nearly infinite paths.  So start simple.

Pull/Push - this is the first order capability.  You need to be able to move data.  If this wasn't necessary, you could get everything you need from your core business systems.

Prepare - integrate, clean, master, organize, and secure the data you're moving to optimize consumption.

Present - distributions, dashboards, reports accessible with a single mouse click or scheduled job.

Unfortunately, what I see time and again are organizations trying to develop data strategy that's out of balance with the other key 3 P's:  People, Processes, Platforms.

Platforms have evolved to the point where they can level the playing field for small-to-mid-sized organizations seeking to leverage data.  Essential data capability platforms are increasingly point-and-click and cloud based tenancy further simplifies their implementation.  This is where most data strategy stops - find the right platforms and everything else will magically fall into place.

People - the distinction between business and data roles will blur as the workforce continues to develop data-centric skills (statistical analytics, SQL, AI) and understanding foundational information technology.  Deploying these resources outside of the technology functions will soon separate the wheat from the chaff when it comes to competitive advantage from data.  An IT-centric mindset towards data team organization is the quickest route to failure.

Processes - this is the area where the most corners are cut - and always have been.  Process modeling has never been more important.  Agentic AI can't run on tribal knowledge, and being the single human who "knows everything" isn't sustainable.  Standardizing how data capabilities are implemented and executed has never been more important.

There are many layers of complexity that can be exposed beneath these key concepts, but establishing them as foundational pillars will help organizations of all sizes avoid spiraling into chaos.