What Separates Good From Great Data Teams

A guide to shifting from outputs to outcomes in your data career

Hi, fellow future and current Data Leaders; Ben here 👋

I’ve had the chance to work with dozens of data teams, each at different stages and with very different infrastructure setups. Sometimes I only learned about a tool because one team happened to use it, and then I never saw it again. While tools can certainly make life easier, what really made certain teams stand out wasn’t the stack, it was the traits they consistently showed in how they worked and what they delivered. Those traits are what I want to share with you today.

Before we dive in, a quick note: I still find that many data teams spend much of their time trying to get data from data sources into their data warehouse. That’s where Estuary comes in. It makes moving data in real-time or batch simple, freeing teams to focus more on high-value workflows. I’ve used it with clients myself, which is why I now also work with them as an advisor. If you’re interested you should check out this recent case study.

Now let’s jump into the article!

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Intro

I don’t remember when I first paused and looked at the work I delivered, and was bummed out, because it really didn’t go anywhere.

I’ve spoken with many data ICs and executives who’ve had this experience. They spend hours, days, months building tables, dashboards and ML models and no one used them.

Or they failed to get implemented. For many, this is when things click.

I’ve got to do more than just deliver a query. If I really want to drive impact, I’ve got to, at the very least ask why.

Why are we building this? Who is this for? What problem does it solve?

And beyond that, how do I ensure it goes beyond me.

Because in the end, if your dashboard or ML model never get’s implemented, it might as well have not been done.