Metabase Cheat Sheet

Updated 2026-05-26

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Metabase is an open-source business intelligence platform that lets teams explore data, create visualizations, and build interactive dashboards without necessarily writing SQL. It connects to 30+ databases and provides a graphical query builder for non-technical users and a native SQL editor for analysts. Metabase has evolved significantly — with Data Studio for semantic-layer curation, Metabot AI for natural-language querying and SQL generation, a Modular Embedding SDK, and Actions for writing data back to databases — making it a full self-service analytics platform, not just a BI viewer. A key insight: models and transforms are Metabase's layered approach to reusable data: models add metadata within Metabase; transforms persist results as real database tables.

What This Cheat Sheet Covers

This topic spans 24 focused tables and 258 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core ConceptsTable 2: Data Source SetupTable 3: Query Builder InterfaceTable 4: SQL Editor FeaturesTable 5: Question Types and VisualizationsTable 6: Dashboard Creation and DesignTable 7: Filters and ParametersTable 8: Collections and OrganizationTable 9: Permissions and Access ControlTable 10: Alerts and SubscriptionsTable 11: Embedding OptionsTable 12: Appearance CustomizationTable 13: Models and Data ModelingTable 14: Data Studio and TransformsTable 15: Actions and Write-BackTable 16: Performance TipsTable 17: Custom Expressions and FunctionsTable 18: Dashboard InteractivityTable 19: Search and NavigationTable 20: Advanced SQL FeaturesTable 21: AI Features and MetabotTable 22: Administration and ConfigurationTable 23: Installation and DeploymentTable 24: Time Series Comparisons

Table 1: Core Concepts

Understanding Metabase's building blocks — from questions to documents to the semantic library — prevents confusion about where content lives and how the different content types relate to each other.

Concept	Example	Description
Questions	Query builder or SQL query	A query, its results, and its visualization — the basic analytical unit in Metabase.
Dashboards	Collection of charts with filters	Group related questions into tabbed pages with shared filters and interactive elements.
Models	Turn question into a model	• Curated datasets built from questions • queryable like tables with annotated column metadata.
Metrics	"Revenue" aggregation formula	• Standardized aggregations defined once and reused • ensures consistent calculations across teams.
Collections	"Marketing Analytics" folder	• Organizing folders for questions, dashboards, models, and metrics • permissions set at collection level.
Documents	Charts + narrative Markdown text	Reports that combine charts and rich text — like a Notion doc or Jupyter notebook — available on all plans.

Table 1: Core Concepts

Concept	Example	Description
Questions	Query builder or SQL query	A query, its results, and its visualization — the basic analytical unit in Metabase.
Dashboards	Collection of charts with filters	Group related questions into tabbed pages with shared filters and interactive elements.
Models	Turn question into a model	• Curated datasets built from questions • queryable like tables with annotated column metadata.
Metrics	"Revenue" aggregation formula	• Standardized aggregations defined once and reused • ensures consistent calculations across teams.
Collections	"Marketing Analytics" folder	• Organizing folders for questions, dashboards, models, and metrics • permissions set at collection level.
Documents	Charts + narrative Markdown text	Reports that combine charts and rich text — like a Notion doc or Jupyter notebook — available on all plans.