A single source of truth for how metrics are defined and their business logic in an organization. ## Metrics Layer Advantages - You can define a metric once and use it everywhere ## Metrics Layer Disadvantages #placeholder/description ## Popular Metrics Layer Tools [[Cube.js]] [[Metriql]] [[data build tool|dbt]] (with [dbt metrics + dbt server coming soon](https://www.getdbt.com/blog/licensing-dbt/)) [[Metricflow]] %% wiki footer: Please don't edit anything below this line %% ## This note in GitHub <span class="git-footer">[Edit In GitHub](https://github.dev/data-engineering-community/data-engineering-wiki/blob/main/Concepts/Data%20Management/Metrics%20Layer.md "git-hub-edit-note") | [Copy this note](https://raw.githubusercontent.com/data-engineering-community/data-engineering-wiki/main/Concepts/Data%20Management/Metrics%20Layer.md "git-hub-copy-note")</span> <span class="git-footer">Was this page helpful? [👍](https://tally.so/r/mOaxjk?rating=Yes&url=https://dataengineering.wiki/Concepts/Data%20Management/Metrics%20Layer) or [👎](https://tally.so/r/mOaxjk?rating=No&url=https://dataengineering.wiki/Concepts/Data%20Management/Metrics%20Layer)</span>