Which two methods are commonly used for data reduction?

The correct choice highlights two widely recognized techniques for data reduction: deduplication and compression.

Deduplication refers to the process of identifying and eliminating duplicate copies of data. This method increases storage efficiency by ensuring that only unique pieces of data are stored, which significantly reduces the overall data volume. This is particularly useful in environments where multiple copies of the same data might exist, such as backups or replicated datasets.

Compression, on the other hand, involves encoding data using fewer bits than the original representation. This can either be lossless, where no data is lost during the process, or lossy, where some data may be discarded for the sake of reducing size. Compression is effective for all types of data, from images to text files, making it a versatile method for reducing needed storage space and improving transfer times.

The other options, while they may involve data management or transformation, do not primarily focus on the act of reducing data volumes in the same way that deduplication and compression do. Therefore, choosing deduplication and compression showcases the most relevant methods for data reduction.