In today’s highly sensitive business environment, every organization is holding some level of risk in their data. Personal information in unsecured environments, highly sensitive corporate information leaving the building on laptops; these are not just potentially expensive breaches of the General Data Protection Regulation, but it could be a very embarrassing headline in the national newspaper that costs a loss in customer confidence and market capitalization.
We have created this Privacy Assessment score-card to give you a summary of the data that resides in shared repositories.
The initial driver for most FileFacets users is to determine what kind of documents they have, what they should be concerned about, and subsequently what they should do with the various results found.
Through our years of experience, it has become evident that the Document Type of a record will drive many of these concerns and the actions taken to secure sensitive information. Each Document type will have a level of risk associated with it based on the usual contents of that document type.
By using Machine Learning to identify the document type, the usual level of risk, whether that document type tends to contain PII, and analyzing the file location, we can create a Document Profile and score. Using these profiles and machine learning within the FileFacets tool, each repository can be scanned and have a score determined. Using these outputs, the business you can make a meaningful correlation to the document type profile of Security, Sensitivity, Personal Data, and ROT.
The remainder of the report includes a Content Analysis Report with graphs for:
After the scan is complete, you will receive your results by repository with a breakdown per repository.
You will also receive recommendations that may include things like:
Each recommendation will include steps to follow in order to complete the task.