Which would be a practical application of dynamic tiering?

Dynamic tiering is designed to optimize data storage within the SAP HANA environment by providing the capability to efficiently manage different types of data according to their usage patterns. Selecting to reduce costs by storing archival data efficiently aligns perfectly with the functionality of dynamic tiering. This approach allows less frequently accessed data to be stored in a more cost-effective manner while keeping the mission-critical, frequently accessed data readily available in the in-memory storage.

By utilizing dynamic tiering, organizations can move older or less critical data to extended storage while retaining the potential for quick retrieval when needed. This leads to significant savings on storage costs without sacrificing performance for essential real-time analytics on more relevant and recent data.

In contrast, creating real-time analytics for all data does not leverage the intended benefit of dynamic tiering, as it’s more about efficiency and cost reduction rather than handling all data in-memory. Increasing data redundancy is not a goal of dynamic tiering; instead, it focuses on optimizing space usage. Streamlining database query languages is unrelated to the dynamic tiering concept, as it deals more with how queries are processed rather than how data is stored and managed.