The leading foodservice distributor in the U.S. is a Fortune 500 company that partners with 300,000 restaurants and foodservice operators to help their businesses succeed. Like just about every company today, large and small, this foodservice distributor has a lot of data, including a multi-billion row dataset of service level data.
More than 2000 employees access the company’s Service Level Impact dashboard in Tableau multiple times a day to identify issues that must be addressed to ensure fulfillments are achieved and SLAs are met. However, the data powering the dashboard is summarized and aggregated due to scale limitations. Employees have to request an extract of all of the data related to the specific issue from the BI team to determine exactly what the issue is, why it had happened, and which action should be taken to resolve it immediately. In short:
Sigma was purpose-built for Snowflake and cloud data warehouses. Employees now have direct access to live data in Snowflake, ensuring that everyone is always working with the same current data – no more stale extracts, data sprawl, or conflicting insights – and the data stays safe in Snowflake.
Sigma is a cloud-native solution delivering unlimited scale at cloud speed – no summaries or aggregates necessary. Employees can now easily analyze and filter billions of rows of transactional data, enabling them to drill down into data without rendering or latency delays.
Sigma’s spreadsheet interface makes iterative ad hoc analytics available to anyone, especially those that are accustomed to analyzing data in spreadsheets. Today, employees analyze data and create pivot tables in Sigma, just as they had in Excel, so they can quickly address potential issues before they become serious problems.
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