Data Loss Prevention (DLP) is different from most traditional data-centric security solutions in that its primary focus is on internal, as opposed to external, threats. Unauthorised disclosure of internal data through any media, network mechanism or the accidental disclosure by well-meaning users can have disastrous results for an organisation’s brand, reputation or standing with regulatory bodies. There are solutions however that can, and should, work alongside DLP tools in the ongoing challenge to ensure that data is made available to authorised recipients only, while remaining adequately secured at all times – data classification is therefore key.
When a data classification solution is integrated with your existing DLP solution, an additional precision can be achieved, enabling the organisation to extract value while simultaneously managing the inherent liability of regulated data. Using metadata, driven by data classification, your DLP solution will dramatically reduce the number of false positives and negatives that would otherwise be seen, leaving you safer in the knowledge that your data is being appropriately protected.
Watch this 30-minute discussion to understand:
• What is data classification
• The challenges faced using a DLP solution without data classification
• How does Boldon James solve those challenges?
Better together: how data classification and DLP solutions complement each other to protect your sensitive data