Blog
Practical writing on simpler architectures, maintainable analytics systems, and choosing the right level of complexity for the problem in front of you.
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Most companies that hire their first data engineer are not starting from zero. Data already exists across the business, but it lives in spreadsheets, dashboards, and manual workflows that…
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Self serve analytics is often positioned as the solution to an overwhelmed data team. The idea is simple. Give business users access to data and tools so they can answer their own…
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If you ask most teams why they don’t trust their data, the answers usually point to symptoms. Dashboards don’t match. Numbers change depending on who you ask. Reports require manual…
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Being the only data person at a company is often framed as an opportunity. You get ownership, autonomy, and the chance to build something from the ground up. In practice, it tends to feel…
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Most teams exploring Apache Iceberg are not actually dealing with the problems Iceberg was designed to solve.
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As data teams move beyond dashboards and begin building internal tools, the problem shifts from visualizing data to operationalizing it. At that point, the question is no longer how to…
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Many small distributors do not begin with structured systems or formal processes. They build their operations around whatever allows them to move quickly and serve customers without…
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The modern data tooling market is crowded. Each year new platforms promise faster pipelines, real time analytics, or infinite scalability. Spark clusters, streaming frameworks, lakehouses,…
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For many small wholesale distributors, the search for better operational visibility eventually leads to order management software. These systems promise inventory tracking, automated order…