Case Study: Blackstone leverages Sigma and Snowflake to perform data analytics at cloud scale
Key results
The challenge
Given its scale, Blackstone's finance teams had the financial knowledge but needed additional technical expertise to operate traditional BI tools such as Tableau and Power BI, or Python. Those tools were limiting for ad hoc analysis and took raw data away from end users, while Excel struggled with the scale and complexity at which Blackstone operates. The team sought a platform with the ease of Excel, the power and speed of a cloud data warehouse, real-time collaboration, and enterprise security and scale.
The solution
Blackstone chose Sigma, purpose-built for the cloud data warehouse, for its Excel-like interface suited to aggregate and portfolio analysis over datasets running into billion-row records. This let the firm unlock its existing pool of Excel experts and reduce reliance on dedicated Tableau developers, so finance teams could self-serve most ad hoc analysis. Sigma's Input Tables let teams add data directly to Snowflake without writing custom logic back into the database, and were embedded in internal applications.
“I think the biggest value driver for Sigma is that you're not using specialized Python developers to analyze billion row records anymore. You're just adding an Excel user.”
HZHan ZhangSenior Vice President, Blackstone
The results, in context
Blackstone reported more than 700 active Sigma users analyzing million- to billion-row datasets globally, achieving data democratization by empowering Excel users rather than specialized Python developers. Ad hoc analysis time savings moved from days to hours. The firm uses Sigma for portfolio analysis, root cause analysis, and scenario modeling on Snowflake.