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Looker

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Key Info:

Cloud / Online / Web based
Looker interface screenshot

Looker is Google Cloud's business intelligence and governed analytics platform. It uses the LookML modelling language to define reusable business logic, then exposes that model through Explores, Looks, dashboards, scheduled deliveries, APIs and embedded analytics experiences. Version-controlled modelling helps data teams review how shared measures and dimensions change over time.

Details

A modelling-first approach

Looker is designed around a semantic layer rather than a collection of independent report queries. Data teams describe dimensions, measures, joins and access logic in LookML projects. Business users then analyse governed fields in an Explore without needing to reconstruct joins or metric definitions. This can improve consistency, but the model requires engineering discipline, review and ownership.

Exploration, dashboards and delivery

Users can start from an Explore, select fields, apply filters and choose visualisations. Results can be saved as Looks or added to dashboards. Dashboards support filters, drill paths, scheduling and rendered delivery formats. The platform also supports embedding and themes for organisations that want analytics to appear inside an application or customer portal.

Development and operations

LookML projects use a development workflow that can be connected to version control. Administrators manage users, roles, permissions, connections, content and instance settings. A REST API supports programmatic access to content and administrative functions. Evaluation should cover model testing, deployment review, query performance, cache behaviour and the separation between content creators and model developers.

Who should evaluate it

Looker is most relevant to organisations that want a centrally governed analytics model while still allowing users to explore data. It can support internal BI, customer-facing analytics and operational workflows. Teams that only need a small number of fixed reports may not benefit from the additional modelling layer and development process.

Evaluation notes

Model one high-value subject area with definitions that normally cause disagreement, then ask different users to answer related questions without editing SQL. Test a model change, a permission boundary, a slow query and a scheduled delivery. Review version-control practices, development and production modes, data residency, identity integration, embedding requirements and edition-specific capabilities. Keep Looker Studio outside the comparison because it is a separate product with a different operating model. Verify how certified content is labelled and how owners find unused or broken dashboards before migration.


Features

LookML semantic modelling; reusable metrics and joins; Explores; Looks; interactive dashboards; dashboard filters; scheduled delivery; rendered outputs; version-control workflow; roles and permissions; REST API; embedded analytics and themes

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