Sigma vs.
Power BI
Maxed out Power BI to its limit?
Sigma delivers self-service analytics at scale, live in your cloud data platform.
DATA-DRIVEN BUSINESSES USE SIGMA FOR FAST, EASY, AND POWERFUL ANALYTICS
Sigma vs.
Power BI
- Direct Query Limitations
- Syntax Headaches with M, Dax, and MDX
- End Users Performing Excel Exports
Leverage the power of the cloud and analyze data at speed and scale.
Sigma
- Empowers cloud self-service analytics in a governed and familiar UI: the spreadsheet.
- No complex syntax
- Data and BI teams free from creating, managing, and maintaining Dataflows.
- Enables business users to freely drill anywhere to row-level data at massive scale.
- CSAT: 4.8. Real-time dedicated in-app support for your entire organization in minutes.
- Thirty-minute dedicated office hours over Zoom to all accounts.
Power BI
- Direct query capability only able to address basic use cases.
- Desktop & Cloud-combined deployment model.
- Transformation occurs in Dataflows and Cubes.
- Collaboration is disconnected, desktop driven, and difficult to merge.
- Business users are actively encouraged to work in Excel for analytics.
Real time support in minutes, not days
The support team is nailing it, it's really good support. Please keep it and even if you make it "VIP Treatment," then we want to be VIP. We love your live support.
Nan Xiao
CTO, Greenland Capital Management
There hasn't been a single data question I haven't been able to answer in Sigma once I engage the support team for help.
Mathew Jennings
Director, Orennia
What really helped make my life easier in making the case for Sigma was the thought, effort, and responsiveness that your team put in whereas the competition simply lacked that level of depth!
Orr Sergev
Director of Analytics, OpenWeb
Why Companies Choose Sigma Over Power BI
A Cloud-Native Start With Sigma
Sigma's generational differentiator from traditional BI tools is being born in the cloud, keeping the modern cloud data platform in mind. Sigma will never hold or persist any of your data. Sigma’s spreadsheet-like interactions produce machine-generated SQL code that is executed live against your warehouse. Sigma's cloud-native architecture allows us to provide lower cost per user at scale and rapidly deploy innovative features such as:
- Billions of rows, enterprise scale
- Drill Anywhere
- Live Edit Collaboration
- "Bring Your Own Data" with Input Tables
A Language and Interface Teams Already Know and Love
Whether data experts know spreadsheets or SQL, Power BI requires knowing M, DAX, MDX, Dataflows, and even more of the Microsoft stack.
In contrast, Sigma gives analysts the option to leverage their existing expertise, saving time and resources while working with one platform. Sigma gives everyone—including non-technical users—the ability to query the data warehouse directly using an intuitive spreadsheet-like UI with familiar formulas and functions.
Flexible Data Curation With Zero Pre-Modeling Required
With Power BI, data must be appropriately transformed before business users can access it—even when similar transformation has already been performed with tools like dbt. Sigma’s spreadsheet experience allows even non-technical users to freely explore, calculate, filter, and sort through billions of rows of data directly from the cloud data warehouse with no modeling required. Users can also endorse and curate datasets for collaborative analytics on trusted data.
Explore our Customer Stories
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Taylor Perkins
Co-founder & CTO, Slope Software
“If you had told me a year ago that we were going to switch embedded analytics' providers, I would’ve told you, you were crazy. Looker was integrated throughout our application. However, after running into enough roadblocks, limitations, and support issues, we started searching for alternatives and finally implemented Sigma.”
Additional Resources
We are Sigma.
Sigma is a cloud-native analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. It requires no code or special training to explore billions of rows, augment with new data, or perform “what if” analysis on all data in real-time.