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Case studyData engineering & the warehouse/lakehousedbt
dbt Labs Blog · Read source ↗

Fanatics has implemented dbt State to optimize their data warehouse operations. By only rebuilding the parts of the warehouse that have changed, they have managed to reduce compute costs and accelerate the speed of data processing runs.

MyDataWork POV — Dbt State's method of selectively rebuilding warehouse components highlights a key insight about enterprise AI: it's about assembling the right pieces rather than pursuing flashy solutions. By focusing on what's changed, Fanatics is saving on compute costs while streamlining their data operations. This method respects the reality of data work, where efficiency and precision are often more valuable than raw power. It's a reminder that sometimes the best innovations are those that make the complex more manageable.
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