About MetricFlow
Learn more about MetricFlow and its key concepts
Learn more about MetricFlow and its key concepts
Learn about MetricFlow and build your metrics with semantic models
Metrics can be defined in the same or separate YAML files from semantic models within the same dbt project repo.
Use Cumulative metrics to aggregate a measure over a given window.
Derived metrics is defined as an expression of other metrics..
Dimensions determine the level of aggregation for a metric, and are non-aggregatable expressions.
Entities are real-world concepts that correspond to key parts of your business, such as customers, transactions, and ad campaigns.
Learn how to create your first semantic model and metric.
Joins allow you to combine data from different tables and create new metrics
Measures are aggregations performed on columns in your model.
Query metrics and metadata in your dbt project with the metricflow cli
MetricFlow expects a default timespine table called metricflow_time_spine
When you define metrics in dbt projects, you encode crucial business logic in tested, version-controlled code. The dbt metrics layer helps you standardize metrics within your organization.
Use ratio metrics to create a ratio out of two measures.
Semantic models are yml abstractions on top of a dbt mode, connected via joining keys as edges
Use simple metrics to directly reference a single measure.
The Semantic Layer, powered by MetricFlow, has three types of built-in validations, including Parsing Validation, Semantic Validation, and Data Warehouse validation, which are performed in a sequential and blocking manner.