Databricks Dashboards (formerly Lakeview) is an AI-assisted business intelligence platform deeply integrated into the Databricks Lakehouse, enabling interactive data visualization and reporting with enterprise-grade governance through Unity Catalog. Unlike traditional BI tools that operate as separate systems, Databricks Dashboards leverages native compute resources, inherits data permissions directly from Unity Catalog, and supports both AI-powered authoring with Genie Code agents and programmatic deployment through Declarative Automation Bundles (DABs). The key mental model: dashboards are governed analytical objects that sit alongside tables and views in Unity Catalog, connecting data modeling (datasets, local metric views, custom calculations, metric views) with visual storytelling—making them ideal for self-service analytics, embedded reporting, and CI/CD-managed dashboard workflows. Legacy DBSQL dashboards reached end of life on March 5, 2026 and are no longer available.
What This Cheat Sheet Covers
This topic spans 20 focused tables and 176 indexed concepts, 127 flashcards. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
A jump-to index of every table row in this cheat sheet.
An interactive map of every table and concept in this topic.
Table 1: Core Dashboard Components
Every AI/BI dashboard is built around two workspaces: the Data tab where semantic objects and SQL datasets are defined, and the Canvas tab where visualizations are laid out. Understanding these building blocks is the foundation for everything else.
| Component | Example | Description | |
|---|---|---|---|
Define datasets from Unity Catalog tables/views | • Central workspace for defining datasets, custom calculations, and parameters • all data modeling happens here before visualization. | ||
Drag-and-drop visualizations onto 12-column grid | • Layout editor where charts, filters, text widgets, and counters are arranged • supports multi-page organization. | ||
SELECT * FROM catalog.schema.sales_data | A Unity Catalog table, view, or custom SQL query serving as a reusable data source for multiple visualizations. | ||
Visual interface defines dimensions, measures, joins | • A dashboard-scoped semantic object created without publishing to Unity Catalog • ideal for prototyping before promoting to global metric views. | ||
[Revenue] * 0.3 for calculated measure | • Enables new measures or dimensions defined in the dashboard layer without modifying underlying SQL • supports aggregations, LOD expressions, and window functions. | ||
Create from catalog.schema.metric_views.sales_kpis | • A Unity Catalog semantic layer object defining business metrics once • reusable across dashboards, notebooks, and Genie. | ||
Query-based dropdown: SELECT DISTINCT region | • A dynamic input that passes values into dataset queries, custom calculations, or text widgets • enables user-controlled filtering. | ||
Filter by product_category IN ('Electronics') | • A filter widget that operates on dataset columns after query execution • ideal for rapid exploratory filtering. | ||
Markdown with headers, links, images, {{param_name}} | • A rich text element using Markdown to add context, titles, and notes • authors can embed parameter values inline |