You plan to deploy a data platform solution for 4 TB of data. The solution will be used to generate analytic reports during business hours only. All reports will be generated by using Microsoft Excel.

While Azure SQL Data Warehouse (now Azure Synapse Analytics dedicated SQL pool) offers high performance for analytical workloads, its always-on compute costs can be higher than a data lake solution, especially if resources are only needed during business hours.

Azure Cosmos DB is a NoSQL database optimized for high-performance transactional applications and real-time data access, making it less suitable and more expensive for batch analytical reporting requirements.

Azure SQL Database is a relational database primarily designed for OLTP workloads; while it can store 4 TB, it may not offer the most cost-effective solution or the highest possible read performance for large-scale analytical reporting compared to specialized data warehousing or data lake services.

Azure Data Lake Storage Gen2 provides a highly scalable and cost-effective storage solution for 4 TB of data, optimized for big data analytics with high throughput. It minimizes costs by offering tiered storage and allowing compute resources to be provisioned only during business hours when reports are generated, while still providing high read performance for analytical workloads.