The Metric Layer & how it fits into the Modern Data Stack

Published by Transform

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A metric layer is a centralized repository for key business metric. This “layer” sits between an organization’s data storage and compute layer and downstream tools where metric logic lives—like downstream business intelligence tools. 

A metric layer is a semantic layer where data teams can centrally define and store business metrics (or key performance indicators) in code. It then becomes a source of truth for metric—which means people who analyze data in downstream tools like Hex, Mode, or Tableau will all be working with the same metric logic in their analyses. 

The metric layer is a relatively new concept in the modern data stack, mainly because until recently, it was only available to companies with large or sophisticated data teams. Now it is more readily available to all organizations with metric platforms like Transform.
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In this article, you’ll learn what a metric layer is, how to use your data warehouse as a data source for the metric layer, and how to get value from this central metric repository by consuming metrics in downstream tools.

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