When should Azure Synapse Analytics be used?

Azure Synapse Analytics is particularly well-suited for performing complex queries and aggregations. It is designed to handle large volumes of data and support analytics workloads that require the processing of complex datasets. This capability allows users to execute intricate queries across massive amounts of data efficiently, leveraging its powerful distributed computing architecture.

By utilizing parallel processing and optimization techniques, Azure Synapse Analytics can perform aggregations and analyses that might be challenging or time-consuming to execute with other data services. It’s optimized for big data analytics, making it ideal for scenarios that involve data exploration, transformation, and advanced analytical tasks.

The other options do not align as closely with the primary strengths of Azure Synapse Analytics. For instance, while basic data storage requirements can be fulfilled by many services, Azure Synapse Analytics is more specialized toward analytics rather than merely storing data. Data visualization and reporting might be better achieved using tools specifically designed for those purposes, such as Power BI, which integrates well with Azure Synapse but is distinct in functionality. Finally, running OLTP (Online Transaction Processing) workloads typically requires a different type of database system that is optimized for high-speed transaction processing, which is not the primary focus of Azure Synapse Analytics.