18 docs tagged with "Metrics"

Learn more about MetricFlow and its key concepts

Learn about MetricFlow and build your metrics with semantic models

Use Conversion metrics to measure conversion events.

Define metrics in your dbt project to create quantitative indicators.

Use Cumulative metrics to aggregate a metric 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.

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 commands.

MetricFlow expects a default time spine table called metricflow_time_spine

Learn how to migrate from the legacy metrics spec to the latest metrics spec.

Use ratio metrics to create a ratio out of two metrics.

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.

Semantic models are YAML abstractions on top of a dbt model, connected via joining keys as edges

Use simple metrics to aggregate data directly from columns in your semantic models.

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.