Practical thinking on data leadership, building data teams from scratch, scoped data projects, and what actually works in B2B SaaS analytics. No fluff - just lessons from 10+ years of doing the work.
Someone had a great idea - replace our BI tool with code-based dashboards that AI could spin up in minutes. The idea was genuinely good. But it wasn't that simple.
Read →AI lets everyone build dashboards faster. But faster doesn't mean better. Here's why governance and human judgment matter more in the age of AI reporting.
Read →The reflex to reach for AI is becoming the default for everything. Even stuff you already know how to do. That habit is costing more than time.
Read →RevOps promised a unified revenue engine for a decade. AI agents are finally forcing the issue - not because they're smarter, but because they literally can't function any other way.
Read →Data models quietly constrain what analysts can build, what AI can answer, and what questions your business can even ask. A rigid modeling foundation is an invisible bottleneck.
Read →Everyone says dashboards are dead. They're half right. The problem was never the dashboard - it was where we put it and what we expected it to do.
Read →I wrote about build vs buy back in 2022. AI has completely rewritten the calculus. Easier to build doesn't mean you should - and the real challenge is now internal.
Read →The best data work I've seen runs on the most boring tools imaginable. The business doesn't care if you used SQL or Python - it cares if the numbers are right.
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