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In the parlance of today's IT community, cold data is data that is not frequently accessed or actively used. It is data that may get collected and sit for a long time in some virtual container without being retrieved, analyzed or transferred to another part of the system.
Working with cold data, as opposed to warm or hot data, involves some specific philosophies. In general, cold data is easier to deal with, because there are not as many requirements regarding synchronized results, or immediate input-output processes that have to be accommodated. Cold storage often involves setting up a durable archive – a place where data can stay safely for the long term, but where it is available when it is needed.
Some experts create specific thresholds for cold data, for instance, data that is dormant for between 91 and 180 days, or data that sits longer than six months or a year. In many cases where data does not move, the related outcomes are less labor-intensive and a company or professional may choose not to perform some task because it is not necessary. Sometimes administrators may use metrics like “last use” to assess the frequency of data activity. Companies may use these metrics as part of research to consider clearing out old data to make room in finite storage systems.