How to Get Started with Sigma Computing

Sigma Computing runs analytics directly inside a cloud data warehouse, presenting results in a familiar spreadsheet interface. There is no data export, no file size limit, and no manual refresh. This guide covers everything from signing up for a free trial to building your first filtered dashboard without writing a single line of SQL.

What Is Sigma Computing

Sigma Computing is a browser-based analytics platform designed to feel like a spreadsheet but operate at the scale of a cloud data warehouse. Instead of exporting data to Excel or Google Sheets, analysts connect Sigma directly to Snowflake, BigQuery, Databricks, or PostgreSQL and query live data from the browser.

The platform uses familiar concepts such as rows, columns, and formulas, but applies them at the column level rather than the cell level. A formula written in a column automatically applies to every row in that column, eliminating copy-paste errors common in large spreadsheets. According to Sigma's own research, the 2010 Harvard debt-growth study error, which affected macroeconomic policy in multiple countries, resulted from a cell-reference mistake in Excel that column-level tools like Sigma would prevent.

For teams already working in cloud warehouses, Sigma is particularly well-suited to analysts and operations managers who need to explore large datasets but do not have SQL experience.

What You Need Before Starting

Sigma is not a standalone tool. It acts as a query and visualization layer on top of a cloud data warehouse. Before you can analyze data, you need:

• A supported data warehouse: Snowflake, Google BigQuery, Databricks, or PostgreSQL
• An account with read access to at least one schema or table in that warehouse
• A modern browser (Chrome or Edge recommended)

If your data currently lives in CSV files or spreadsheets, you will need to load those files into one of the supported platforms first. Both Snowflake and BigQuery offer free tiers that accommodate small datasets, making them practical entry points for small teams evaluating Sigma without a large existing infrastructure.

If you want to analyze CSV files or flat data without setting up a cloud warehouse, VSLZ lets you upload a file and get statistical analysis and charts from a single plain-English prompt, with no configuration needed.

Starting Your Free Trial

Sigma offers a 14-day free trial with access to core analytics features. To start:

1. Go to sigmacomputing.com and click Start Free Trial
2. Enter your name, work email, and organization name
3. Select your data warehouse type
4. Sigma creates your organization and opens the home screen

The Essentials plan, which covers unlimited users, core analytics, and the full spreadsheet interface, starts at $300 per month after the trial. The Professional and Enterprise tiers are custom-priced and add embedded analytics, AI capabilities, and advanced governance.

The 14-day trial is long enough to connect a warehouse, build several workbooks, and share them with colleagues to assess fit before committing to a plan.

Connecting Your Data Warehouse

After signing in, the first task is adding a data connection. This is an admin-level operation done once; team members reuse the connection without needing credentials.

To add a connection:

1. Click the Administration menu in the top-right corner
2. Select Connections from the left sidebar
3. Click Create Connection and choose your warehouse type
4. Enter your connection credentials:
   • For Snowflake: account URL, warehouse name, database, schema, username, and password or OAuth token
   • For BigQuery: upload a service account JSON key file and select your project and dataset
   • For PostgreSQL: host, port, database name, and credentials
5. Click Save and Sigma validates the connection with a test query

Once connected, Sigma displays the databases, schemas, and tables available under that connection. Teams see only the data their permissions allow.

A security note: create a dedicated read-only role for Sigma in your warehouse rather than using admin credentials. In Snowflake, this means running GRANT SELECT on the relevant schemas to a new role. In BigQuery, assign the roles/bigquery.dataViewer IAM role to the service account.

Creating Your First Workbook

Workbooks are Sigma's primary analysis container. Each workbook holds one or more pages, similar to tabs in a spreadsheet. Each page holds data elements such as tables, charts, and pivot tables.

To create a workbook:

1. Click New in the top-left menu and select Workbook
2. On the blank page, click Add New Element and select Table
3. In the data panel, browse the connection tree to find the table you want to analyze
4. Click the table name to load it as a live query

At this point you are querying live data. Sigma shows the columns from your warehouse. You can scroll, sort, and resize columns just as in a spreadsheet. No SQL is involved.

To rename the page, double-click the tab at the bottom of the screen.

Building Calculations and Pivot Tables

Once a base table is loaded, you can add calculated columns using familiar formula syntax.

To add a calculated column:

1. Click the + button at the right edge of the column header row
2. Select Add Column
3. Type a formula in the formula bar, for example [Revenue] / [Units Sold] to calculate revenue per unit
4. Press Enter and Sigma applies the formula to every row in the column

Sigma formulas use square brackets to reference column names, which reads more clearly than Excel-style cell references like B2/C2.

To build a pivot table:

1. Add a new element to the page and select Pivot Table
2. Drag columns into the Rows, Columns, and Values sections in the left panel
3. Sigma executes the aggregation live against your warehouse

Grouping is one of Sigma's more practical features. You can group a table by any column and nest multiple groups to compare segments side by side, without formulas. In a sales dataset, for example, you can group by Region and then by Quarter in a single click.

Adding Charts

To convert a table to a chart:

1. Click Add Child Element on any existing data table
2. Select a chart type such as Bar Chart, Line Chart, or Scatter Plot
3. Sigma maps columns automatically; adjust axis assignments in the left panel
4. Use the Marks panel to color by a dimension, adjust label formatting, or modify the chart style

Charts in Sigma are linked to their parent table through a parent-child relationship. Filtering the parent table updates all child charts immediately. This eliminates the manual refresh step that slows down Excel-based dashboards.

Adding Filters and Sharing

Filter controls let viewers interact with a workbook without editing the underlying data. To add a filter:

1. Click Add New Element and select Filter Control
2. Choose the column to filter on, such as Region or Date Range
3. Position the filter control near the top of the page so viewers find it quickly

To share the workbook:

1. Click Share in the top-right corner
2. Enter email addresses or team names
3. Select whether recipients can view, explore, or edit the workbook

Sigma also supports scheduled PDF and email exports for stakeholders who prefer a push report to logging into the platform.

Summary

Sigma Computing gives analysts and operations teams a spreadsheet-like experience on top of a live cloud data warehouse. The critical prerequisite most introductory guides skip is the warehouse itself: Sigma does not store data or accept file uploads. Once a Snowflake, BigQuery, Databricks, or PostgreSQL connection is in place, the setup process takes under 30 minutes. Workbooks, calculations, pivot tables, and charts all follow patterns familiar to Excel users, but the queries run against the full warehouse dataset at cloud scale. The 14-day free trial is the most practical way to evaluate whether the tool fits your team's existing data infrastructure.