Metadata
- Author: @aurimas
- Full Title:: The Jungle of Metrics Layers and Its Invisible Elephant
- Category:: 🗞️Articles
- URL:: https://aurimas.eu/blog/2022/08/metrics-layers-and-power-bi/
- Finished date:: 2024-02-15
Highlights
Until they supported it
the current DBT’s approach is to be the layer where metrics are only defined but not queried. The implementation of converting metric definitions to queries/computation of metrics is delegated to upstream tools. You can see how that plays out in an announcement from Cube, which just released DBT metrics support. (View Highlight)
Here’s the thing: in none of the discussions about what a metrics layer should be / coverage of key players, have I ever seen a reference to a player that has functionality that fulfils most of the requirements typically listed for a metrics layer (View Highlight)
Cube, Metriql, Metlo, MetricFlow, AtScale and Malloy do not store data (View Highlight)
However, even these players admit that in some cases querying raw data in data warehouses is suboptimal. Thus, some support the pre-aggregation – frequently used metrics and dimensions are precomputed and stored in their own database (View Highlight)
so far, we are still in the land of relatively basic metrics (View Highlight)