Originating Author: Michael McCreary
Retrofitting metadata to the huge and growing accumulation of unstructured data -- e-mails, IM sessions, notes, memos, etc. -- that companies are accumulating is one of the major challenges facing organizations as they attempt to create full, organized records from the data on their hard drives.
The underlying technologies supporting enterprise search and natural language processingmay form the foundation for building a consistent and defensible (not necessarily perfect) capability to automatically classify the growing corpus of unstructured data owned by organizations today.
In many ways this represents the Holy Gail for records management as it will remove the end user from the equation. However the benefits of such a capability are far larger than risk mitigation through improved records compliance. By being able to effectively segregate and treat like unstructured information in the aggregate organizations will be better able to:
- Find the specific information they require.
- Create new connections and draw inferences across large data sets.
- Free end users from the burden of organizing their information.
- Reduce storage costs.
- Defensibly delete the junk and keep information around for only as long as it is either relevant and useful or required by regulating authorities.
- Leverage emerging Enterprise Digital Rights Management to quickly and securely share information outside the boundaries of the organization.
- Focus security efforts on the high risk information and not worry about the rest.
Action Item: Ideally going forward tools will tag / classify information objects at the time of creation, e.g., an extension to the file / save as process, and store / organize them virtually according to content, use, value, retention period, etc. Under this model the traditional hierarchical files structure disappears, replaced by a content-based semantic structure that is automatically built and maintained by the system versus the user.
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