One significant ongoing information governance challenge is how to deal with the “Zombie” devices and file shares that remain after employees depart for one reason or another, or that are uncovered during merger & acquisition activities. Zombie devices and data can include laptops or other personal computing devices, and previously assigned file share space.

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The devices and file shares aren’t live in the sense that people are actively using them, but they’re not sufficiently dead as to permit decent burial or disposition. Like in the horror shows, zombie devices and data can cause considerable disruption if they just keep piling up with no plan for disposition.

The good news about dealing with them is that visual classification provides a reliable and defensible way to assess the content to determine whether it needs to be retained, and if it does need to be retained, to associate a document-type label with the appropriate documents so that the correct retention period can be assigned. At that point the devices or file shares can be redeployed.

The initial step is to collect the files from the Zombie devices and file shares. BeyondRecognition can provide a “Collector” which is a USB devices that dedupes data and skips known system files. This makes it relatively straight forward to collect the data and begin the visual classification process.

The visual classification process can also involve extracting designated attributes from each cluster of visually-similar documents, as well as potentially redacting PII. For more information, see this link to visual classification. As noted in other blog postings, the intelligence that was accumulated in processing other content within the organization can be applied to the content gathered from the Zombie devices and file shares. Alternatively, if the Zombie devices and shares are the first content to be classified, the intelligence gained doing that can be applied to subsequent collections.

Related Post: Rolling Intelligence: The Enterprise-Equivalent of Paying It Forward.

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