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Build your metrics

Use MetricFlow in dbt to centrally define your metrics. As a key component of the dbt Semantic Layer, MetricFlow is responsible for SQL query construction and defining specifications for dbt semantic models and metrics.

Use familiar constructs like semantic models and metrics to avoid duplicative coding, optimize your development workflow, ensure data governance for company metrics, and guarantee consistency for data consumers.

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MetricFlow is currently available on dbt v1.6 or higher and allows users to define metrics in their dbt project whether in dbt Cloud or dbt Core. dbt Core users can use the MetricFlow CLI to define metrics in their local dbt Core project. However, to experience the power of the universal dbt Semantic Layer and query those metrics in downstream tools, you'll need a dbt Cloud Team or Enterprise account.

Before you start, consider the following guidelines:

About MetricFlow

Understand MetricFlow's core concepts, key principles, and how to use this powerful tool.

Semantic model

Use semantic models as the basis for defining data. They act as nodes in the semantic graph, with entities connecting them.

Metrics

Define metrics through the powerful combination of measures, constraints, or functions, effortlessly organized in either YAML files or separate files.

About the dbt Semantic Layer

Introducing the dbt Semantic Layer, the universal process that allows data teams to centrally define and query metrics

Get started with the dbt Semantic Layer

Use this guide to build and define metrics, set up the dbt Semantic Layer, and query them using the Semantic Layer API

Available integrations

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.

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