What causes dbt Metric Definition Error?

A metric references a `measure` name that does not exist in the semantic model. The metric's `type` is not a valid MetricFlow aggregation (e.g., a typo in `SIMPLE`, `RATIO`, `CUMULATIVE`, or `DERIVED`). A `filter` expression on the metric contains an invalid dimension reference or Jinja syntax error. A DERIVED metric formula references another metric that was renamed or deleted. The metric YAML indentation is incorrect, causing the definition to be parsed as a different property

How do I fix dbt Metric Definition Error?

Run `dbt parse` and check for metric validation errors in the output — they include the metric name and the specific invalid property.. Verify all measure names in the metric definition match the `name` field of a measure in the semantic model YAML.. For DERIVED metrics, check that each metric referenced in the `expression` exists and is spelled correctly.. Validate the `filter` expression by simplifying it to a known-good dimension before adding complex logic.. Use `mf validate-configs` (MetricFlow CLI) for detailed validation output if available in your environment.

Medium severitydbt

Power BI Refresh Error:
dbt Metric Definition Error

What does this error mean?

A dbt metric definition in a YAML file failed validation. The metric references a non-existent measure, uses an unsupported aggregation type, or has an invalid filter expression.

Common causes

1A metric references a `measure` name that does not exist in the semantic model
2The metric's `type` is not a valid MetricFlow aggregation (e.g., a typo in `SIMPLE`, `RATIO`, `CUMULATIVE`, or `DERIVED`)
3A `filter` expression on the metric contains an invalid dimension reference or Jinja syntax error
4A DERIVED metric formula references another metric that was renamed or deleted
5The metric YAML indentation is incorrect, causing the definition to be parsed as a different property

How to fix it

1Run `dbt parse` and check for metric validation errors in the output — they include the metric name and the specific invalid property.
2Verify all measure names in the metric definition match the `name` field of a measure in the semantic model YAML.
3For DERIVED metrics, check that each metric referenced in the `expression` exists and is spelled correctly.
4Validate the `filter` expression by simplifying it to a known-good dimension before adding complex logic.
5Use `mf validate-configs` (MetricFlow CLI) for detailed validation output if available in your environment.

Frequently asked questions

Can I define metrics without using the dbt Semantic Layer?

Yes — before dbt 1.6, metrics were a standalone concept without a Semantic Layer API. From dbt 1.6+, the MetricFlow-powered Semantic Layer is the recommended approach. Legacy metric definitions (dbt < 1.6) used a different YAML schema.