How data transformation improves data quality and analysis
Summary
Centralizing data transformation within modern ELT architectures improves analytical accuracy and data quality through systematic cleaning, normalization, and validation. Codifying this logic in authoritative, version-controlled models eliminates conflicting metrics across teams while providing reliable, reusable foundations for downstream machine learning and reporting.
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