Sigma Computing is a cloud-native business intelligence and analytics platform designed to democratize data analysis through a familiar spreadsheet-like interface that operates directly on cloud data warehouses (Snowflake, BigQuery, Databricks). Unlike traditional BI tools that extract and cache data, Sigma executes all computations in the warehouse itself, ensuring live data access, infinite scalability, and consistent governance. The platform uniquely bridges the gap between self-service analytics for business users and governed, code-free data modeling, while supporting embedded analytics, writeback scenarios, Python integration, and AI-powered workflows—making it both a visualization layer and an application development framework.
What This Cheat Sheet Covers
This topic spans 25 focused tables and 159 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Core Document Types
Everything you build in Sigma lives inside one of four document types, and knowing which to reach for sets the foundation for the rest of the platform. Workbooks are where most analysis happens, data models hold the governed business logic everyone shares, reports give you pixel-perfect exports, and templates let you stamp out consistent layouts across teams.
| Type | Example | Description |
|---|---|---|
create New > Workbook | • Primary analysis and dashboard document • supports tables, pivots, charts, controls, and actions • versioned with draft/publish workflow | |
create New > Data Model | • Semantic layer defining metrics, relationships, and reusable business logic • replaced the legacy Dataset concept after June 2026 • central source of truth |