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, 198 flashcards. 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

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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.
Query builder	Click "New" → "Question" → Select table	Graphical interface for non-SQL users to build queries using dropdowns and buttons.
Native query editor	Click "New" → "SQL Query"	Text editor for writing queries in the database's native language (usually SQL).
Data Studio	Admin workbench for analysts	Analyst workbench for shaping data: transforms, semantic library, dependencies graph, and metadata management.
Library	Published tables and metrics	Curated semantic layer — tables and metrics published here are surfaced first in query builder as trusted starting points.
Segments	"Active users" filter	• Named filters applied to tables • creates official, reusable definitions of data subsets.
Metabot	"What was revenue last month?"	AI assistant for natural-language querying, SQL generation, chart explanations, and agentic workflows.

Table 2: Data Source Setup

Metabase connects to 30+ databases — including warehouses, cloud databases, spreadsheets, and uploaded CSVs. Field type and metadata configuration done here improves query builder usability for everyone who relies on that data.

Type	Example	Description
Connect database	Admin → Databases → Add database	Connect to PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, ClickHouse, and 30+ databases.

The rest of this section is part of the full cheat sheet

Table 3: Query Builder Interface

The query builder lets non-SQL users compose multi-step analytical queries entirely through a graphical UI. Each step — joining, filtering, summarizing, custom columns — translates to a SQL subquery under the hood.

Step	Example	Description
Pick data	Select "Orders" table or model	Choose a table, model, or metric as the starting data source.

The rest of this section is part of the full cheat sheet

Table 4: SQL Editor Features

The SQL editor gives analysts full control over query logic while keeping the results compatible with Metabase's filter system. Snippets, field filters, and AI generation bridge the gap between raw SQL and interactive dashboards.

Feature	Example	Description
Write native SQL	`SELECT * FROM orders WHERE total > 100`	Full database-native SQL with syntax highlighting, auto-complete, and formatting.

The rest of this section is part of the full cheat sheet

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.
Query builder	Click "New" → "Question" → Select table	Graphical interface for non-SQL users to build queries using dropdowns and buttons.
Native query editor	Click "New" → "SQL Query"	Text editor for writing queries in the database's native language (usually SQL).
Data Studio	Admin workbench for analysts	Analyst workbench for shaping data: transforms, semantic library, dependencies graph, and metadata management.
Library	Published tables and metrics	Curated semantic layer — tables and metrics published here are surfaced first in query builder as trusted starting points.
Segments	"Active users" filter	• Named filters applied to tables • creates official, reusable definitions of data subsets.
Metabot	"What was revenue last month?"	AI assistant for natural-language querying, SQL generation, chart explanations, and agentic workflows.

Table 2: Data Source Setup

Type	Example	Description
Connect database	Admin → Databases → Add database	Connect to PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, ClickHouse, and 30+ databases.

Table 3: Query Builder Interface

Step	Example	Description
Pick data	Select "Orders" table or model	Choose a table, model, or metric as the starting data source.

Table 4: SQL Editor Features

Feature	Example	Description
Write native SQL	`SELECT * FROM orders WHERE total > 100`	Full database-native SQL with syntax highlighting, auto-complete, and formatting.