How would you store structured data for analytics in Azure?

Storing structured data for analytics in Azure is best accomplished with Azure Synapse Analytics. This service is designed specifically for big data and analytics workloads, combining big data and data warehousing capabilities. Azure Synapse Analytics allows for the querying of structured data through a scalable architecture and provides services to ingest, prepare, manage, and serve data for business intelligence and data analysis purposes. It integrates seamlessly with other data services and supports various analytical tools, enhancing its utility for analytics tasks.

While Azure SQL Database is a robust option for transactional data and smaller analytical workloads, it may not provide the same level of performance or scale for large-scale analytics as Azure Synapse Analytics. Similarly, Azure Storage Accounts are intended for storing unstructured data and do not offer the analytical capabilities that structured data requires for in-depth analysis. Azure Data Lake Storage is primarily designed for storing large amounts of unstructured or semi-structured data rather than structured data specifically for analytics. Though it can work in conjunction with analytical services, it does not inherently provide the analytics capabilities that Azure Synapse Analytics offers.