Databricks Metric Views

Databricks Unity Catalog Metric Views, kept as YAML files in your repository. dex reads them with no workspace connection, authors them as reviewable diffs, and holds them to the warehouse when columns move. Nothing is deployed for you.

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Semantic layer
Note:
Repository-first · no deploys

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Why connect Databricks Metric Views?

Databricks Unity Catalog Metric Views define your measures and dimensions over Unity Catalog tables. Dex works on the YAML files you deploy them from: it reads them with no workspace connection, authors them as reviewable diffs, and tells you when they fall out of sync with the warehouse.

What you get

1Keep Metric View definitions in your repository, reviewed like code
2Derive a Metric View from a declared dbt mart, or convert one from an Apache Ossie document and back
3Measure the one-match keys your joins declare against the data they claim
4Nothing deployed for you: Dex validates against the Metric View rules and never touches your workspace

In your repositoryDex

Agent-native analytics engineering on your Databricks Metric Views.

.dex/config.yml
metric_views/orders.yaml

How it works

Explore, transform, maintain: the Dex loop on Databricks Metric Views.

1
Point Dex at your Metric View files
Install Dex in Claude Code by running /plugin marketplace add exmergo/exmergo-agent-plugins and /plugin install dex@exmergo, then add the extra with pip install 'exmergo-dex-core[metric-views]'. Set semantic.vendor: databricks in .dex/config.yml and list your Metric View YAML files under semantic.databricks.files.
databricks-metric-views
- /plugin marketplace add exmergo/exmergo-agent-plugins
- /plugin install dex@exmergo
- pip install 'exmergo-dex-core[metric-views]'
2
Read the catalog before you touch anything
/dex:explore reads the fields, measures, and joins your Metric Views declare, with no workspace connection. Each join and each declared one-match key becomes evidence Dex uses when it profiles tables and verifies joins.
databricks-metric-views
- /dex:explore
3
Author views as reviewable diffs
/dex:transform writes and updates your files through semantic databricks define, and transform apply commits them byte-for-byte. A declared dbt mart derives its Metric View, and an Apache Ossie document converts to one and back.
databricks-metric-views
- /dex:transform
- semantic databricks define
- transform apply
4
Nothing is deployed for you
Every file is validated against Dex's port of the Metric View YAML rules, stricter on write than on read, so keys Databricks would refuse are caught before a file is written. Nothing is deployed to your workspace.
5
Catch drift automatically
/dex:maintain holds your Metric Views to the warehouse: a field or measure reading a column its table lost, a source that is gone, a date format on a column that is not a date.
databricks-metric-views
- /dex:maintain