Which NetApp efficiency creates a group of data blocks before optimizing space?

The correct answer is compression. In the context of NetApp's data efficiency technologies, compression is the process that optimizes space by reducing the size of the data blocks stored. Before applying compression, the system first aggregates or groups these data blocks to identify patterns and redundancies within them. By examining the entire set of blocks together, the compression algorithm can apply more effective techniques that allow for significant space savings.

This optimization process is particularly beneficial for data that contains repeating patterns or is otherwise redundant, as it compresses the data more effectively when it can analyze it as a group rather than individually. As a result, this grouping is a critical step in improving storage efficiency and ensuring that optimal space is utilized within the storage system.

Other methods such as thin provisioning, deduplication, and snapshots serve different functions and do not create a group of data blocks in the same way as compression does. Thin provisioning allocates storage space dynamically, deduplication eliminates redundant data blocks across a dataset, and snapshots provide point-in-time copies of data without inherently optimizing its size. Hence, the function of creating a group of data blocks prior to optimization is specifically aligned with the characteristics of compression.