Practical perspectives on data engineering, platform delivery, and building effective data teams — from people who do the work.
Most data platform failures aren't technology failures. They're scoping failures. Unclear ownership, undefined done, and an architecture that was never validated against real workloads. Here's how to avoid the most common traps.
Read article →The platform debate is still live — and the answer is still "it depends." We break down the trade-offs across workload types, team skills, governance requirements, and total cost of ownership.
Read article →Most governance implementations stall at the tool purchase. The hard part isn't the catalogue — it's the operating model. We cover the policy, ownership, and workflow patterns that make governance stick.
Read article →More articles coming soon.
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