---
title: "semantic layers | Skills We Assign For | Azendo"
description: "Semantic layers for consistent metrics — one definition, many tools, plus the Azendo roles assigned for it."
url: "https://azendo.co/skills/semantic-layers/"
---

[Skills](https://azendo.co/skills/) Analytics and BI 

# semantic layers.

A semantic layer defines business metrics once — revenue, active users, churn — in terms of the underlying tables, so every tool and every user calculates them the same way rather than each reimplementing the definition.

## Where semantic layers fits on a long engagement.

The problem a semantic layer solves is the meeting where two departments present different revenue figures and spend an hour reconciling them. Both queries were competent; they simply made different choices about refunds, currency or timing. A shared definition removes that class of disagreement permanently.

The definitions themselves are the hard part, not the tooling. Agreeing what counts as an active user across product, marketing and finance surfaces genuine differences in what each department means, and the layer cannot be built until those are settled. The technology is straightforward; the alignment is not.

## What an assigned team does with semantic layers.

A semantic layer only holds if it is the easiest path. If writing raw SQL is faster than going through the defined metrics, analysts will write raw SQL under deadline and the definitions will drift back apart.

Making the governed path the convenient one is a design decision, and holding it is continuous rather than a launch milestone. What that ongoing commitment covers is set out in [how the monthly fee is built](https://azendo.co/pricing/).

## What we use semantic layers for.

* One number across every tool Metrics defined once, so dashboards and notebooks cannot disagree.
* Definitions that are reviewable Metric logic in version control, changed through review rather than in a dashboard.
* Governance without blocking analysts A defined path that is faster than writing raw SQL, so it actually gets used.

## How semantic layers capacity is assigned.

Semantic layer work is assigned under [managed data services](https://azendo.co/services/data-engineering/), with metric definitions agreed across departments before implementation.

## Roles we assign semantic layers for

* [Analytics Engineer Data engineering](https://azendo.co/services/data-engineering/analytics-engineer/)

## Service lines it sits in

* [Data engineering](https://azendo.co/services/data-engineering/)

Capacity is agreed as a committed monthly capacity across a discipline, not per skill.

## Related in analytics and bi

* [Tableau — skill we assign for](https://azendo.co/skills/tableau/)
* [A/B testing — skill we assign for](https://azendo.co/skills/a-b-testing/)
* [experimentation design — skill we assign for](https://azendo.co/skills/experimentation-design/)
* [causal inference — skill we assign for](https://azendo.co/skills/causal-inference/)
* [cohort analysis — skill we assign for](https://azendo.co/skills/cohort-analysis/)
* [segmentation — skill we assign for](https://azendo.co/skills/segmentation/)
* [metric definition — skill we assign for](https://azendo.co/skills/metric-definition/)
* [forecasting — skill we assign for](https://azendo.co/skills/forecasting/)

## Tell us what your roadmap needs semantic layers for.

A service delivery manager replies with the disciplines we would assign, the monthly capacity and what the first month looks like.

[All skills we assign for](https://azendo.co/skills/)