Data classification is embedded in the very DNA of successful data protection and privacy programs, at the heart of a true data asset inventory, and is critical for compliance – but it can be difficult, unreliable, and inconsistent (at best). How can enterprises know their data in a fragmented data landscape of diverse data formats, schemas, content, and metadata types? Why haven’t we solved the classification conundrum – and how can security and privacy teams lead the charge for next-generation classification?
It’s crucial that data classification takes a leap forward – enabling organizations to maintain an accurate data inventory, achieve continuous compliance, get insight on their critical data faster, and establish a holistic view of sensitive data across the data sprawl.
Únase a esta sesión para obtener más información sobre:
● Why organizations need a new approach to data classification – and why traditional classification isn’t enough
● How to apply ML to get deeper insight into data
● New techniques for classifying sensitive data