We have both an education product and several financial products. With our education product, we store pre-generated JSON files in Azure Data Lake Storage, representing different student tests in a hierarchical structure. This allows us to serve pre-made tests to thousands of students without hitting performance bottlenecks. Similarly, for our financial products, we store the final calculated output in Azure Data Lake Storage for use with Power BI Embedded. Users get their Power BI data directly from the data lake. We’ve offloaded a lot of load from our core Azure SQL Server by using Azure Data Lake Storage. Overall, we primarily use Azure Data Lake Storage to serve data to end-users, not for complex calculations or analytics.
