Are You Using Snowflake & Power BI? 3 Reasons Sigma Is So Much Better

Large enterprises often pair Snowflake with Power BI in their data and analytics (D&A) stacks, but the combination can be more about necessity than efficiency, leading to issues such as data governance risks, lack of a single source of truth, and high costs due to data duplication. Power BI's Import mode, while optimal, requires duplicating data, which can result in double charges from both the Cloud Data Warehouse (CDW) and Microsoft's ecosystem, whereas Sigma paired with Snowflake offers a simpler, consolidated billing approach. Power BI's Direct Query mode also presents limitations, including restricted functionality, slow query speeds, and row limitations, all of which are addressed by Sigma's faster direct query times and unlimited row results. Additionally, Power BI's complexity, requiring users to learn M and DAX languages, presents a steep learning curve and administrative burden, while Sigma offers a more intuitive UI and easier syntax to learn. The blog argues that moving from Power BI to Sigma and Snowflake can result in significant benefits, including improved data governance, reduced costs, faster insights, and enhanced scalability, thereby maximizing the return on investment from cloud data warehouses and simplifying embedded use cases in a cloud-native environment.