The article discusses the evolving landscape of semantic layers in data architecture, highlighting three primary patterns rather than a single definition. It contrasts BI-native semantic layers, where logic is embedded within tools like Looker or Power BI, with platform-native layers that reside within data platforms such as Snowflake or Databricks. A third pattern, the dbt Semantic Layer, is also presented as a distinct approach. AI
IMPACT Provides guidance on data architecture choices relevant to AI/ML data pipelines.
RANK_REASON The article provides an analysis and decision framework for choosing between different types of semantic layers, which is an opinion or commentary on architectural choices.
- Databricks
- Databricks Metric Views
- dbt Semantic Layer
- Looker
- LookML
- MetricFlow
- Power BI
- Snowflake
- Snowflake Semantic Views
- Tableau Semantics
- Unity Catalog
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