analytics-and-warehouse-design

What problem does it solve?

Designs governance-backed analytics architectures to ensure consistent data grain, lineage, metric ownership, and reproducible reports across warehouses, lakehouses, and semantic layers.

Core Features & Use Cases

• Layered analytics architecture guiding Raw, Staging, Curated Core, Mart, Semantic, and BI layers to ensure data quality and governance.
• Explicit metric definitions, slowly changing dimensions handling, and certified datasets to enable cross-domain reporting.
• Use Case: Build a star-schema data mart for a marketing analytics dashboard with clearly owned metrics and reconciliation checks.

Quick Start

Define the grain, dimensions, and metrics for a new analytics warehouse and specify the data contracts between layers.