Looker
Looker is the most powerful BI tool in the GCP ecosystem — LookML governance plus Gemini-powered AI. We implement it for companies that need a centralized semantic layer and are ready to invest accordingly.
What It Is
Looker is Google's enterprise BI platform, built around LookML — a modeling language that defines a governed semantic layer sitting between your data warehouse and your end users. Every metric, dimension, and relationship is defined once in LookML and reused consistently across all reports and dashboards.
Looker's AI story is now central. Conversational Analytics lets business users ask natural-language questions against the governed LookML model; Dashboard Agents generate AI summaries and deep-dives inside dashboards; LookML-aware assistants help developers write expressions and build visualizations. The Conversational Analytics APIs also expose the same capability to embedded apps.
Why We Chose It
For organizations where data governance and metric consistency matter — where finance and product can't have different definitions of "revenue" — Looker is the right tool. The LookML semantic layer also makes Looker uniquely powerful for embedded analytics and multi-tenant reporting. The GCP native integration (Looker is now part of Google Cloud) also means tighter BigQuery integration, including BI Engine acceleration and Gemini on top.
How We Use It
Design and implement LookML models: views, explores, derived tables, and measures
Build executive and operational dashboards with governed metrics
Configure Conversational Analytics and Dashboard Agents so business users can ask questions in natural language against governed LookML
Set up Conversational Analytics APIs for embedded AI analytics in client-facing apps
Implement user access controls and group-level permissions
Configure Looker's BigQuery connection with persistent derived tables (PDTs) and BI Engine for performance
When Looker is the right BI tool — and when it isn't
Choose Looker when:
- You need enterprise governance and consistent metrics across teams
- You have 20+ BI users across multiple departments
- You want embedded analytics or multi-tenant reporting at scale
- You need Gemini-powered conversational analytics on top of a governed semantic layer
- Budget is 5k+/month (Looker pricing is sales-quoted)
Choose Lightdash instead when:
- You want version-controlled metrics (dbt YAML or Lightdash's native semantic layer)
- You prefer flat-rate pricing that does not scale with headcount
- You don't need the full LookML semantic layer
Choose Metabase instead when:
- Budget is below Looker tier but you still need broad BI (dashboards, embedding, SQL access)
- You want the option to self-host the BI layer
- You want a real AI assistant without Looker-tier commitment
Choose Steep instead when:
- Primary users are non-technical
- The goal is broad self-service access for business users
- Budget is under €500/month