If you think about it, isn’t building technical capabilities in Data and AI Governance a science, while getting people to adopt them is more of an art? I remember a business leader once asked me what I thought we spent way too much time on. I said, “Honestly? Reading emails.” My second answer was all those “routine” meetings packed with way too many people. So, my question is – how many of us are running from one meeting, or call to the next, trying to keep up but barely accomplishing anything meaningful? It’s exhausting, isn’t it? We rarely pause to ask ourselves if everything on our plate is really important or urgent. Half the time, it feels like we’re simply attending meetings without thinking about what truly matters to us in our job responsibilities. Our real job is to spot the few solid things that actually matter. In other words, it’s all about trimming out or eliminating the non-essential.

Being an Essentialist isn’t about squeezing in more tasks or chasing productivity for its own sake. It’s about getting the right things done. It doesn’t mean just doing less for the sake of less either. To me, being an Essentialist means channeling our energy and time so we can operate at our highest level—by focusing on what’s truly essential and doing so with clarity and responsibility.

Essentialism

Practicing Essentialism is really about choosing what you want to do instead of what you have to do. And sure, things can feel a bit too much in the beginning, but asking the right questions will kickstart your journey towards Essentialism. From what I’ve seen, many Data Governance programs that didn’t deliver real value were the ones that slipped into “the undisciplined pursuit of more”—trying to do everything instead of focusing on what actually matters.

The world around us is constantly pushing for more, more, more. That’s why we need a disciplined approach to spot the “vital few” things and let go of the “trivial many.” It’s really about doing less—but doing it better. At the end of the day, our natural question is always, “How can we do less and still achieve more?” Essentialism isn’t about getting things done in less time, and it’s definitely not about running a minimum viable program.

“ Essentialism is about focusing on the right things, and only the right things. ”

We have to get comfortable saying “no” to the non-essentials—things like unproductive meetings or work that doesn’t really add value. And saying “no” isn’t some impulsive reaction. It comes from a clear, thoughtful choice to deliberately and strategically cut out what doesn’t matter. When we do that, we create space for what does matter. It’s all about continually reducing, refocusing, and simplifying so we don’t fall into the trap of the undisciplined pursuit of more.

CDEs

When it comes to Data Governance, “critical data elements” (CDEs) have been the buzzword for more than a decade. But the word “critical” has been thrown around so much—and often without solid business context, care, or stewardship —mostly because building a business glossary by hand is such a heavy lift. The truth is, unless those CDEs are actually linked to use cases like Data Quality, privacy, sensitivity, and lineage, they’re basically just a bag of important-sounding terms. And even though it might sound similar, Essentialism is not the same as tagging data assets as “critical.” Essentialism is about avoiding the pull on our time and energy that leads to scattered efforts and unnecessary distractions. It helps us stay focused on the essential metadata required in the Data Catalog.

We’re already living in a new age of technology, where the number of choices and distractions just keeps growing. Take something as basic as harvesting a data dictionary in the Data Catalog. A single data source can contain thousands of data structures that need to be cataloged, understood, and governed. So how are we supposed to handle hundreds, maybe even thousands, of these data sources? It reminds me of my academic days in astrophysics, where the catalog contained a massive library of stellar spectra. With today’s speed of processing and the massive volumes of data we deal with, it’s easy to feel like we’re getting buried under a data avalanche. And when you throw in constantly evolving regulations and the pressure to innovate, it’s no surprise we feel overwhelmed. To keep up, we’re going to have to play both offense and defense—just like any great championship basketball team.

DQ – Undisciplined Pursuit of More

One of the striking examples of the “undisciplined pursuit of more” is actually found in Data Governance —in Data Quality programs. Ask any executive what value these Data Quality programs bring, and you’ll probably hear the same thing – an overload of Data Quality rules that add little to no real value. Most of them don’t check anything beyond basic metadata characteristics. In an age of advanced Machine Learning (ML) engineering, do we really still need rules that simply confirm dates look like dates or numbers look like numbers? Shouldn’t that be part of regular data engineering? And even when we focus on Data Quality dimensions such as consistency and completeness, what about the business accuracy of data? What about the quality of unstructured data?

“ Gartner estimates that 80–90% of business data is unstructured, and it’s growing three times faster than
structured data. ”

By 2026, that growth is expected to triple the total volume of unstructured information. If we keep spending time on low-value checks, where will we find the bandwidth to deal with significant, meaningful challenges—like unstructured data issues?

Essentialism pairs really well with something as simple as the Eisenhower Matrix, where you sort tasks by urgency and importance. And it’s true—if we don’t think like Essentialists and set our own priorities, someone else will happily set them for us. And honestly, who wants that? Being an Essentialist takes courage. It means feeling free and confident enough to say what matters—clearly, openly, and without fear.