What is Sigma Computing?

Sigma Computing is a cloud-native analytics and business intelligence platform that gives business users a familiar spreadsheet-like interface to explore, analyze, and visualize live data directly from cloud data warehouses like Snowflake, Databricks, BigQuery, and Amazon Redshift, without extracting or moving data. Unlike traditional BI tools that require SQL expertise or data modeling, Sigma lets Excel-fluent analysts query warehouse-scale datasets using formulas, pivot tables, and filters they already know. Advanced users can drop into SQL or Python within the same workbook. The platform also supports AI-powered chat-with-data, writeback to the warehouse, embedded analytics, and low-code AI app building. Named in the 2025 Gartner Magic Quadrant for Analytics and BI and Snowflake's BI Partner of the Year for three consecutive years, Sigma is trusted by companies like JPMorganChase, Ramp, and Figma.

Key Features

Spreadsheet-Like InterfaceLive Warehouse QueriesAI Chat with DataSQL and Python EditorsWriteback to WarehouseEmbedded Analytics SDKLow-Code AI App BuilderSnowflake Native IntegrationBigQuery ConnectorDatabricks SupportReal-Time CollaborationRow-Level SecurityScheduled ReportsVersion HistoryCustom Visualization Builder

How to Use Sigma Computing

1Connect Sigma to your cloud data warehouse (Snowflake, BigQuery, Databricks, or Redshift)

2Open a workbook and browse your warehouse tables using the familiar spreadsheet interface

3Explore data using filters, formulas, grouping, and pivot-style controls with no SQL required

4Build dashboards, charts, and reports and share them with your team or stakeholders

5Embed analytics in your product or use AI chat to ask questions against live data

✅ Best For

Analytics teams and business users at data-mature companies running Snowflake, BigQuery, or Databricks who are comfortable with spreadsheets but not SQL, and want to self-serve warehouse-scale analysis without depending on a data engineer.
Finance, revenue operations, and product teams that need to write back data, model scenarios, and build governed AI applications on live warehouse data in a single, collaborative workspace.

❌ Not For

Organizations that do not have a cloud data warehouse, as Sigma requires Snowflake, BigQuery, Databricks, or Redshift as its data foundation and cannot connect to flat files or local databases as a standalone source.
Small businesses or early-stage startups with limited budgets, as Sigma's Essentials plan starts at $300 per month, making it significantly more expensive than Metabase (free) or Power BI ($14 per user per month) for small teams.

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Pricing

Essentials$300/mo

✓Unlimited users
✓spreadsheet interface
✓live queries
✓dashboards

ProfessionalCustom

✓AI features
✓embedded analytics
✓writeback
✓Python/SQL

EnterpriseCustom

✓AI apps
✓advanced governance
✓SSO
✓dedicated support

Prompts to Try

Show me monthly revenue cohorts broken down by pricing plan and acquisition channel

Which product features are most correlated with 90-day user retention in our Snowflake data?

Build a scenario model showing how a 10% price increase affects projected gross margin

Summarize our top 20 accounts by ARR and flag any that declined month-over-month

Create a real-time supply chain dashboard pulling live inventory data from our warehouse

Use Cases

A revenue operations manager at a SaaS company opens Sigma, connects to their Snowflake warehouse, and builds a live ARR waterfall analysis using spreadsheet formulas on billions of rows of transaction data, completing in 2 hours a report that previously required a 3-day data engineering request.

A finance team at a fast-growing startup uses Sigma's writeback feature to update deal forecasts directly in the warehouse from a familiar spreadsheet-style interface, replacing a fragile Google Sheets process that broke whenever someone edited the wrong cell.

A product analyst without SQL experience uses Sigma's grouping and formula controls to segment users by activation milestone and calculate 30-day retention rates across 50 million event rows, getting results in seconds that previously required filing a data request.

A data team at a retail company embeds Sigma dashboards into their merchandising portal so category buyers can explore live inventory and sales data for their specific product categories without needing access to Snowflake directly.

A growth team uses Sigma's AI chat feature to ask which marketing campaigns drove the highest qualified pipeline last quarter, getting an instant chart from live BigQuery data without building a new report or writing a single query.

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