dbt has become the center of gravity for modern data engineering by solving the chaos of managing SQL at scale. Rather than just writing SQL, dbt brought structure, testing, documentation, version control, and deployment practices to data transformations — the often-neglected heart of the data stack. This piece reflects on how dbt quietly reshaped the analytics engineering landscape and why its rise was no accident. Note: the full analysis is behind a Substack paywall.
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