Looker & Looker Studio
How the BI layer sits on top of dbt — Looker / Looker Studio dashboards, performance, and the metrics-layer conversation.
Looker (the enterprise BI tool) and Looker Studio (the free dashboard tool, formerly Data Studio) are how the dbt marts your team ships actually reach the business. The analytics engineer's job is to make sure the BI layer sits on top of well-modeled marts — not on raw warehouse joins that go sideways at scale.
This hub covers what an analytics engineer actually needs to know about the BI layer: how to design a dashboard that loads fast, where the metric layer should live (dbt vs LookML), and the realistic comparison to Tableau and Power BI. The capstone uses Looker Studio as the BI layer on top of the dbt marts on BigQuery.
By the end of this path you can…
- Build a stakeholder-ready dashboard on top of dbt marts
- Reason about where the metric layer should live (dbt vs LookML vs ad-hoc)
- Design dashboards that perform well under load
- Pick the right BI tool given a team's stack and budget
From beginner to job-ready.
- 01 · Foundations
What Looker and Looker Studio are, and how they differ.
- 02 · The BI surface
Dashboards, charts, filters, drill-downs — the building blocks of useful reporting.
- 03 · Performance
Aggregation in dbt vs aggregation in BI; cache vs live; the cost of bad joins.
- 04 · The metrics layer
Where 'revenue' is defined — in dbt, in LookML, or in both. Trade-offs.
- 05 · The capstone
Build the marketing-attribution dashboard in Looker Studio on top of dbt marts.
Read the playbook.
- BI
Optimizing Looker Performance: Best Practices for Faster Dashboards
Learn best practices to enhance Looker dashboard performance, from query optimization to backend improvements, ensuring faster and efficient insights.
- BI
Top 5 BI Tools Every Analytics Engineer Should Know in 2025
Explore the top BI tools for analytics engineers in 2025, including Looker, Power BI, and Tableau. Understand their strengths in visualization and integration.
Show, don't just claim.
Visualization and Reporting
8 lessons in this module
Common questions about this topic.
Looker or Looker Studio?
Looker (the enterprise tool, paid) for serious org-wide BI with LookML as the modeling layer. Looker Studio (free) for ad-hoc dashboards, lightweight team reporting, and portfolio projects. The capstone uses Looker Studio because it's free and reaches a wider audience.
Where should the metric layer live?
Push as much as you can into dbt marts: one definition of revenue, one definition of customer. Use LookML or the BI tool's semantic layer only for cuts that genuinely vary by audience. The single-source-of-truth rule pays dividends every quarter when a metric is questioned.
Is Looker on the way out post-Google acquisition?
No — Looker is still actively developed and remains the BI standard at many large data orgs. Looker Studio (the free tool) is also growing. Both are worth knowing as an analytics engineer.
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