D) Data Lake is designed for data analytics as it allows for the storage and analysis of large volumes of various forms of data and is optimized for big data analytics tasks.
The option designed for data analytics is D) Data Lake. Data lakes are specifically engineered to store a large amount of raw data in its native format, which includes structured, semi-structured, and unstructured data. They are designed to handle high volumes of data and are optimized for performing big data analytics, where large and complex datasets are analyzed to uncover hidden patterns, market trends, customer preferences, and other useful business information. Unlike traditional databases or data warehouses, which can be limited by data schema or size, data lakes are ideal for exploring vast amounts of varied data using advanced analytics techniques.
In contrast, CosmosDB is a globally distributed, multi-model database service, BLOB Storage is used for storing large amounts of unstructured data, and a SQL database is a structured query language database that supports tabular data storage and is typically used for online transaction processing. While all of these can be used in analytics to some degree, a Data Lake is the most synonymous with big data and analytics workloads.
So, for tasks related to data analytics, a Data Lake is the best-suited option among the ones listed, as it offers the flexibility and scalability required for such operations.