In my earlier articles I explained how a metadata-driven data platform, dual SCD2 historization, source access views, and business-friendly mappings work together to deliver reliable, demand-driven data to consumers.
But before we can generate SQL code automatically, before we can build exposure views or perform mappings step by step, we need something more fundamental: high-quality data models.
Without them, we’re coding blind. With them, we can automate, govern, and evolve our data platform with confidence.
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Why Data Models Are the Cornerstone
Data models are not “just documentation.” They are the blueprints for every transformation in a metadata-driven platform.
They allow us to:
Describe what data means (logical models).
Describe how data is stored (physical models).
Translate messy source structures into consistent, business-oriented structures.
