Work with data in the spreadsheet format—and functions—you already know.
Don’t choose between speed-to-insight and scalability. Sigma dashboards get you both.
Know how to use a spreadsheet? Now you can build a data application.
Generate sustainable revenue by using Embedded Applications with Sigma to sell data as a product to your existing customers.
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See for yourself. Sigma is a G2 crowd favorite, backed by countless reviews.
We currently use PowerBi for reports and dashboards, but were limited with what data we could provide, and if there was a lot of data, the report would take a while to produce results. With Sigma, we can publish large amounts of data quickly, plus it also has some great visualizations. In less than 6 months Sigma has changed the way the organization views data, and they just can’t seem to get enough of Sigma.”
Darlina J.
Business Intelligence Manager
Enterprise
Provides a familiar spreadsheet environment improving time to value for developers and adoption for consumers.
Does not offer a traditional spreadsheet interface; focuses on interactive visualizations and dashboards.
Use familiar spreadsheet skills for data analysis as well as direct SQL queries.
Users need to learn Power BI’s interface, M, DAX, and Power Query for data modeling and analysis.
Right-click on any element to drill down into further analysis without additional set-up.
It supports interactive drill-downs with cross-filtering capabilities for detailed data exploration. Users can encounter irrelevant reports because they cannot restrict the drill-through to select reports.
Enables dynamic data summarization and complex analysis. Easy multi-level groupings and customization.
Offers pivot table functionality through matrix visuals and dynamic aggregation options. Limited native functionality and relies on Power Pivot for advanced features.
Easy to combine user input context, UI actions, and data warehouse to build data applications. Easy to input cell level data or upload CSVs to the warehouse.
Does not natively support write-back functionality. Power Apps and Power Automate must be leveraged to support write-back—even those are limited by refresh restrictions and API throttling.
Connects seamlessly to real-time data sources.
Connects to various live data sources. May experience performance issues with sources outside the Microsoft ecosystem.
Leverages intelligent query engine for performant queries.
Optimized for high performance with STAR schema models for efficient data handling. Faces performance challenges when querying large datasets with its large dataset and DAX limitations when using Direct Query.
Utilizes warehouse caching mechanisms to securely enhance performance and reduce query times.
Utilizes caching mechanisms and optimized query handling to enhance performance and reduce query times. Managing cache refreshes and ensuring data consistency can be challenging.
Supports real-time collaboration while building data projects.
Offers collaborative features through shared workspaces and dashboards but lacks real-time editing capabilities.
Provides a robust SQL editor allowing analysts to do ad-hoc analysis and share results.
Supports SQL queries through Power Query with limited flexibility and DAX for custom calculations.
Integrates Python for scripting and advanced data analysis.
Can create custom visuals with python. Notebook-like experience not supported.
Shows a detailed view of data origin and transformations; each element is a data source.
Limited visibility into data lineage, making impact analysis a challenge. Relies on external tools like Power BI Helper and DAX Studio to support.
Offers assistance and resources via live chat for all users within the platform.
No in-product support.
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