The threat of data breaches has soared as organizations continue to digitally transform their operations. Data Loss Prevention, or DLP platforms, can help harden an organization’s security posture by offering real-time analysis of user activity and blocking unauthorized users from gaining access to sensitive data. But DLP programs can miss the mark by focusing myopically on data-in-motion. Real-time analysis of data in motion not only drags on network performance but it also results in high rates of false positives and leaves gaps in coverage, potentially exposing sensitive data.
Transform your data loss prevention with data classification.
To prevent breaches involving sensitive data, you must first determine exactly where that data resides—and more often than not, it is at-rest. Data classification of your data’s sensitivity, risk and other context serves as a starting point for effective data loss prevention strategies and is foundational for a successful DLP program. With sensitive data already identified, your DLP solution can be governed by a simpler set of rules, easing deployments and reducing false hits.
Join our panel of industry experts who will discuss the good, bad and ugly of DLP deployments and how you can drive more value from your DLP investment. Bring your questions and scenarios to this interactive panel to get the answers you need!
Key takeaways:
• Why your DLP strategy must include data-at-rest
• How to create an effective DLP program
• How data classification helps security teams focus monitoring and security efforts on the sensitive data that needs to be protected the most
• Benefits of automated data-at-rest discovery and classification as the foundation to your DLP program
Attendees are eligible to receive 1 CPE credit.