327 technical articles on Teradata, Snowflake, Databricks, SQL tuning and data warehouse architecture — written from production experience, not vendor decks.
A passing test means the tested assertion held for those cases, not that the whole program is correct. This limitation applies to deterministic software as well as systems containing LLMs. Traditional software tests establish behavior for tested cases, not general correctness. Deterministic programs can silently calculate wrong values. Property-based, randomized and concurrency tests can check …
“All models are wrong, but some are useful.”George Box This practical primer is part of the series on moving from data engineering into AI systems. It focuses on LLM concepts relevant to interviews and implementation; the original relative newsletter schedule is omitted. Read the related career and job-posting articles for the broader series. Publication timing …
“The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”Alvin Toffler Open any job board, scroll any LinkedIn feed, sit through any earnings call, and you will run into the same wave of new titles: AI engineer, AI developer, AI strategist, machine …
How to think about the choice when the standard path no longer reliably works. Foreword The path that worked through most of the previous decade — pick any reasonable engineering specialty, get hired into a junior role, learn the rest on the job — does not reliably work in 2026. The market has shifted. The …
Banks are cutting junior data engineers today. The bill comes due in 2035. Reports of technology layoffs motivate this concern, but this article does not supply a named dataset establishing the number or disproportionate junior share. The apprenticeship risk is an argument to evaluate, not an inference proven by those unsourced figures. That narrative is …
Three responses senior technical practitioners may consider as markets shift, with illustrative economics and trade-offs rather than guaranteed outcomes.
AI-assisted senior teams and outsourced implementation have different costs and risks. This opinion uses illustrative staffing assumptions to examine the value of expertise; it does not establish a universal cost ranking.
Every enterprise AI strategy deck I have seen in the past years contains the same promise: “We will build a RAG-based knowledge assistant that lets employees query our internal documents in natural language.” The board nods. The budget gets approved. Six months later, the assistant gives wrong answers, misses critical information, and nobody trusts it. …
Z-ordering and liquid clustering both support data skipping. Their effectiveness on skewed data depends on predicates, layout and maintenance; compare representative workloads rather than assuming either curve guarantees a win.
Spreadsheet risk depends on access, validation, change control and ownership. Practical governance matters for Excel and for the pipelines that replace it.
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