I wrote a post about thinking past medallion architectures. That one went a little deeper about the architectural characteristics that make thinking in “medallions” unnecessary. But the truth is, you don’t need to internalize all that. I’m guessing you sense that data just doesn’t work, even with
Let’s talk about something nobody wants to admit. Your marketing team has their own copy of customer data. Sales has a different version. Product is maintaining yet another extract. Finance built their own dashboard using data they pulled last month. Each team has created their own shadow copy of
Picture this: You’re in an executive meeting. The company just acquired another business, and the CEO wants to change how you calculate monthly active users to include the new customer base. Simple request, right? “That’ll be six months,” comes the response from the data team. Six months?! To
Why AI is exposing decades of accepted dysfunction You can’t move at AI velocity when your data team still says “that’ll take six months.” Here’s how an entire industry normalized broken patterns, and why AI is forcing us to finally confront them. I was talking to a
A ritual playing out in boardrooms everywhere: the new data strategy presentation. This time it’s different. This time we’ll capture the value. The slides are beautiful. The architecture diagrams are comprehensive. Everyone nods. Nobody believes it. We’ve been here before. At least three times, in fact. The
December 4 at 11 a.m. PT / 2 p.m. ET Six-month data migration timelines. Projects on hold. Costs climbing. What if you could test your migration in parallel with production? Roll back mistakes without losing work? Compress months into weeks? Join us December 4 to see how Matterbeam makes
Matterbeam goes against the data industry's complexity addiction. We built it to let small companies access sophisticated data integration without enterprise budgets. You're not locked into decisions. Time is on your side. Transform and emit data fearlessly as new use cases arise.
Around 2015, I was leading an extraordinary architecture team in an effort to decompose Pluralsight’s monolithic application into distributed services. The system exhibited classic tight coupling symptoms: changes cascaded unpredictably into other components, deployment required coordinated release windows across multiple teams, and specific engineers became single points of failure
"Can I just get the data? Can I just get a dump? Can I please just connect to the database?" If you've worked in data in any organization for more than five minutes, you've heard this plea. Usually it comes from someone who just
