Automated data classification involves the application of a classification for a particular file or message by a pre-defined rule set. The rule set might be based on matching keywords or expressions found in the content with a given list or identifying some other characteristic of the file for example it came from the customer information data store so needs to be protected.
Automated classification can also extend classification coverage across a variety of originating data sources, including those which originate outside of user control. This approach is useful when organisations have data generated by automated processes or systems that should be classified at the point of creation without user intervention – for example reports that are produced by an ERP system.
Some organisations look to combine automation with a user-driven approach to provide an element of support to the user. For example, applying default labels based on user group or department. This approach reduces the number of clicks that the user has to perform but by involving the user greatly enhances the accuracy of the classification process.
Automatic classification cannot understand the context of a file or document and as a result faces challenges with accuracy. Incorrect matches or ‘false positives’ reduce user’s trust in the system and failure to identify sensitive data or ‘false negatives’ expose the organisation to unnecessary risk. The challenge is to tune these algorithms to provide an acceptable error rate that avoids frustrating users and ensures policies are adequately enforced. Where this is not possible often organisations de-tune their automation rules in order to reduce the error levels, clearly this dilutes the tools effectiveness.
Blending the use of automated techniques with user-driven data classification can deliver significant benefits. Capturing user insight in the process of data classification is critical to ensuring decisions are made within the correct context. In order to get this blend of techniques right for your business, your classification solution needs to offer an integrated range of approaches that you can tailor to meet your precise needs and that can be easily adapted as your needs evolve.
Boldon James Classifier360 is an Enterprise Classification System that blends together best practice in user-centric and automated classification techniques in the manner most appropriate to your business.
- Adapts to your business and infrastructure needs
- Reflects the differing requirements of your user communities
- Supports users in their classification decision-making
- Streamlines workflow for routine classification tasks
- Balances technology-based decision-making with user insight
- Respects the authority of user judgements
- Widens the reach of data classification
- Leverages investment in Discovery tools such as DLP