The Modern Data Teams Hub

For years now, I’ve found myself frustrated at how so many of the conversations around building effective data organizations have centered around tooling and technology. In the pre-COVID days, I’d attend conferences looking for nuggets of wisdom that would speak to me, only to find another talk on faster data ingestion or the best infrastructure for running Airflow. Having personally watched, led, and grown data organizations in both size and impact, I believe tooling is a hurdle, but people management and building cross-functional relationships that enable data teams to be strategic is a much more difficult set of problems to solve.

This list of links began as a collection in my bookmarks bar. Eventually, it became a GitLab Snippet. I’d link people to it, but eventually I’d stumble on someone else sharing it too. What started as a small collection of links on how to build data organizations is now something a lot bigger and better, and I’m excited to share it today: The Modern Data Teams Hub. Y’all, I’m over building the Modern Data Stack, I’m here to talk about building Modern Data Teams.

You can read more about what I think building great data teams is about in the hub. But for a quick sneak peek, I believe data teams today should be focusing on:

• Breaking out of the service trap
• Aligning on the metrics that best measure our actual business practices
• Creating clearer job titles, career ladders, and actually using them
• Accepting that you’re a bit aways from ML (and predictive analytics can get you 80% of the way there)

I didn’t write everything here personally – these links and resources have been collected over the years from speakers, podcasters, and writers. Resources generally fall into six categories:

1. Building data-driven organizations (e.g.Cultivating algos)
2. Creating Data team strategy (e.g.Share your data insights to engage your colleagues
3. The types of work your Data team does (e.g. An intake form for data requests)
4. Thinking about Data quality (e.g. Data meta-metrics)
5. Crafting Data careers (e.g. On training wheels and balance bikes)
6. Technical overviews (e.g. You Don’t Need Kafka)

It’s certainly not comprehensive, but my goal isn’t to catalog everything that’s been written. This is my curated list, the resources that I found myself leaning into over and over.

As I wrote recently,

The explosion of tooling in the data space is a result of a better understanding of exactly the problems we are solving for organizations. Today we have a whole toolkit of dedicated solutions helping us best address the ways that our data teams impact the business.

I get excited by all of the new tooling. New companies, new ideas, new problems- they are exciting! But, we cannot obsess over the tooling and lose sight of the work: driving impact through improved decision making.

The Modern Data Teams Hub will continue to grow and evolve over the next couple of years. I look forward to seeing how data tooling continues to evolve over the next couple of years but, more importantly to me, I look forward to how data problems will be solved by leadership, organization, process, and people.

The next time you find yourself thinking about the problems Data Teams are facing, before you reach for your tooling, I hope you’ll ask yourself if this is a people problem and, if so, I hope you’ll find yourself at moderndatateams.com.