- Published on
Stop hand-building a galaxy of star schemas. If the business layer is modeled, the consumption layer - Unified Star Schema, mart, OBT, star - is downstream of it and should generate itself.
Data-modeling
All Posts
data-modeling (12)
- data-engineering (11)
- methodology (6)
- declarative-architecture (6)
- ai (5)
- data-architecture (4)
- architecture (3)
- automation (3)
- analytics (2)
- data-warehouse (2)
- data-contracts (2)
- semantic-clarity (2)
- team (2)
- daana (2)
- unified-star-schema (1)
- analytics-engineering (1)
- semantic-layer (1)
- daana-cli (1)
- release (1)
- data-warehousing (1)
- integration (1)
- ensemble-modeling (1)
- ux-design (1)
- identity-resolution (1)
- focal-framework (1)
- platform (1)
- case-study (1)
- Published on
Analytical systems are built for questions that do not exist yet. A layered DAS/DAB/DAR architecture with ensemble modeling makes continuous change survivable.- Published on
Skills, semantic layers, and ontologies make analytics agents work, until they hit the messy data underneath. The durable fix is structural, not more context.- Published on
Information Integration is the discipline of determining which Concept each data record belongs to - and that depends entirely on Definitions. Part 1 of a three-part series on Definitions as the foundation of every Data Warehouse.- Published on
Subtraction at the operational layer, deepening at the modeling layer. The local Postgres sidecar is gone, deploy and execute are ~2× faster, --full-refresh now works at workflow, entity, or attribute scope, and many-to-many relationships are correct and tested across PostgreSQL and BigQuery.