How is data reduction deployed in PowerScale?

Data reduction in PowerScale is implemented through a post-process method, which means that the data reduction occurs after the data has been ingested into the storage system. This allows for the application of various techniques such as compression and deduplication to optimize the storage efficiency after the initial write processes. By performing data reduction post-process, PowerScale can assess the data effectively and apply the most suitable reduction techniques based on the stored information.

This method contrasts with the other options, which suggest different timing for data reduction techniques. For instance, real-time methods would imply that the data is reduced as it is being written, which could affect performance. Pre-process might suggest that data is reduced before being written to the storage, which is not the approach used in PowerScale. In stages may imply a tiered approach to reduction, which is less fitting than the straightforward post-process method used by PowerScale.