Learn more about MetricFlow and its key concepts| docs.getdbt.com
In , both jobs and environments are configured to use a specific version of . The version can be upgraded at any time.| docs.getdbt.com
Integrate and query metrics and dimensions in downstream tools using the Semantic Layer APIs| docs.getdbt.com
Discover the diverse range of partners that seamlessly integrate with the powerful dbt Semantic Layer, allowing you to query and unlock valuable insights from your data ecosystem.| docs.getdbt.com
Joins allow you to combine data from different tables and create new metrics| docs.getdbt.com
Use this guide to build and define metrics, set up the dbt Cloud Semantic Layer, and query them using Google Sheets.| docs.getdbt.com
Reference public models across dbt projects| docs.getdbt.com
Explore dbt Cloud pricing plans. Find the best solution for your data transformation needs with transparent pricing.| dbt Labs
Use exports to write tables to the data platform on a schedule.| docs.getdbt.com
Learn how to create and set up CI checks to test code changes before deploying to production.| docs.getdbt.com
Measures are aggregations performed on columns in your model.| docs.getdbt.com
Entities are real-world concepts that correspond to key parts of your business, such as customers, transactions, and ad campaigns.| docs.getdbt.com
Saved queries are a way to save commonly used queries in MetricFlow. They can be used to save time and avoid writing the same query over and over again.| docs.getdbt.com
Dimensions determine the level of aggregation for a metric, and are non-aggregatable expressions.| docs.getdbt.com
Seamlessly set up the dbt Semantic Layer in dbt Cloud using intuitive navigation.| docs.getdbt.com
Learn how to migrate from the legacy dbt Semantic Layer to the latest one.| docs.getdbt.com
Learn how the dbt Semantic Layer enables data teams to centrally define and query metrics.| docs.getdbt.com
Read this guide to understand the ref Jinja function in dbt.| docs.getdbt.com