---
title: "Looker | Skills We Assign For | Azendo"
description: "Looker and the modelling layer — one definition per metric, and the Azendo roles assigned for analytics work."
url: "https://azendo.co/skills/looker/"
---

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

# Looker.

Looker is a business intelligence platform built around a modelling layer, LookML, where metrics are defined once in version-controlled code and every report derives from those definitions rather than from its own SQL.

## Where Looker fits on a long engagement.

The modelling layer is the whole point. In most BI tools every dashboard carries its own logic, so two reports disagree and nobody can say which is right. In Looker the definition lives in one reviewed place, and a change propagates rather than fragments.

That discipline is also the cost. LookML has to be maintained by someone comfortable with code review, and an organisation that wants analysts dragging fields around without governance will find it heavier than the alternatives. It suits organisations that have already been burned by conflicting numbers.

## What an assigned team does with Looker.

A modelling layer is only worth its overhead if it is maintained with review discipline. LookML edited by whoever is nearest, without review, becomes the same sprawl it was adopted to prevent — just in a more expensive tool.

The model and the warehouse beneath it are one problem, so they are normally one assignment, scoped under [data engineering outsourcing](https://azendo.co/services/data-engineering/) rather than split between a BI contractor and a data team.

## What we use Looker for.

* Ending the metric argument One reviewed definition of each measure, so meetings stop being about whose number is correct.
* Self-service with guardrails Business users exploring within a model that prevents nonsensical joins.
* Maintaining an inherited LookML project A model that has grown unowned brought back to a state someone can safely change.

## How Looker capacity is assigned.

Analytics engineering is assigned under managed data services, since the model and the warehouse beneath it are one problem. Every assigned specialist comes through the [Talent Success and Academy](https://azendo.co/talent-success-academy/) programme first.

## Roles we assign Looker for

* [Analytics Engineer Data engineering](https://azendo.co/services/data-engineering/analytics-engineer/)
* [BI Developer Data science](https://azendo.co/services/data-science/bi-developer/)
* [Data Analyst Data science](https://azendo.co/services/data-science/data-analyst/)

## Service lines it sits in

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

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

## Related in analytics and bi

* [Power BI — skill we assign for](https://azendo.co/skills/power-bi/)
* [Tableau — skill we assign for](https://azendo.co/skills/tableau/)
* [semantic layers — skill we assign for](https://azendo.co/skills/semantic-layers/)
* [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/)

## Tell us what your roadmap needs Looker 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/)