Sensitive Data Assessment
Many organizations are no longer confident that they can detect and prevent the loss of sensitive data. And with the explosion of emails, documents, images and other unstructured data happening in every area of the business, understanding and protecting that data becomes more difficult every single day.
Driven by artificial intelligence, DryvIQ continually detects, analyzes, and classifies sensitive and other valuable data and labels the degree of criticality. It discovers a wide array of aspects of your unstructured data including sensitivity levels, age, type, last-accessed, location, permissions access and both internal and external sharing rights and more.
Take a look at some of the insights DryvIQ gathered after performing a sensitive data audit and risk assessment for a recent customer’s IT department – and some of the recommendations our experts were able to make on how to better govern their unstructured data.
Overall, there were over 7,000 potential risks identified in the target environment.
Findings:
- 2.5% of the 400 GB of content analyzed was identified as containing sensitive IT data.
- 7,527 identified sensitive data items located in the HR share.
Recommendations:
Immediate recommendations:
- 1,157 passwords require immediate review and remediation to reduce vulnerability.
- Sensitive items located in the HR share require immediate review and remediation.
Long-Term Recommendations:
- Automate policy enforcement with DryvIQ for continuous monitoring and management.
- For data governed by regulatory laws, implement the DryvIQ cost exposure and savings feature to ensure compliance & reduce risk.
- For manual remediation, assign data owners and assign applicable items in the Policy Items Report.
- Audit permissions to locations with sensitive data and quarantine highly-sensitive documents to a secure repository.
Contact us today to get started with your own sensitive data discovery and risk assessment.
Audit & remediate your existing file sensitivity labels
Validating the accuracy of labels while identifying unlabeled files has historically been a manually intensive process. There are many reasons that users may not have applied the correct sensitivity label to files resulting in unknown corporate risk. Even automated labeling solutions should be periodically “audited” to ensure labeling accuracy, check for dated data, or even back file data that may be missing labels.
DryvIQ enables organizations to validate the accuracy of sensitivity labels while identifying unlabeled files — and automatically applying accurate labels utilizing artificial intelligence driven classification and sensitivity discovery.
