BigID, the leader in data discovery and intelligence for privacy, protection and perspective, today introduced Hyperscan technology for scanning large volumes of unstructured file data in the data center or cloud at petabyte scale. BigID’s Hyperscan leverages BigID developed ML to dramatically expedite the classification, cataloging and correlation of sensitive data in high volume file stores like O365, Sharepoint, Box, GDrive, S3, NetApp, EMC, HDFS for the purposes of data compliance, privacy, remediation, access governance, cloud migration, minimization or retention.
Organizations produce and store petabytes of documents like PDFs, spreadsheets, presentations, and forms – yearly. Understanding what and whose data is inside these diverse “unstructured” files has always proved challenging, requiring large compute resources to achieve performance that can take months or years for scanning typical enterprise volumes. This creates significant issues for data compliance, security and governance since files often contain sensitive data about people, IP, accounts and more. For over a decade the only innovation in scanning unstructured files was around optimizing data parsers and parallelizing scanners. BigID completely rethinks how unstructured data is scanned and processed achieving the first order of magnitude speed enhancements in a generation.