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Data Engineering for Small Teams
Build Maintainable Pipelines, Quality Checks, and Useful Analytics
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54 b
Nové
You are the developer, analyst or founder who ended up in charge of the numbers, with no data team and no time for a year-long platform project. This guide shows how to build a small, boring and dependable setup: loads that are safe to run twice, a clear raw, staging and mart structure, schedules that recover from failure, and a short list of quality checks that catch problems before your colleagues do. It then turns clean tables into agreed metrics and reports people actually open, and finishes with the runbook, access rules, privacy habits and cost limits that keep everything running when someone is away. Worked examples follow a fictional online shop, and a Quick Reference gives you checklists to apply straight away.
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