These release notes provide information about the Metalogix Sensitive Content Manager 2.2 release. Metalogix Sensitive Content Manager uses a micro-service architecture and can be integrated with Microsoft SharePoint, Metalogix ControlPoint and Metalogix Essentials.
Metalogix Sensitive Content Manager (SCM) provides a reliable, accurate and flexible solution for detecting sensitive information within enterprise content management systems. SCM ships with pre-built analysis profiles such as General Data Protection Regulation (GDPR), Personally Identifiable Information (PII), Protected Health Information (PHI), Payment Card Information (PCI) in addition to the detection capabilities with customizable analysis profiles.
This version of Metalogix Sensitive Content Manager introduces the following features and improvements:
New Search Terms
·USA Bank Account Number
·USA Passport Number
·USA Individual Taxpayer ID Number
·UK Passport Number
·Germany Tax Identification Number
·Upgrades the installed Erlang installation to version 24
·Upgrades the installed Rabbit MQ installation to version 3.8.17
·Backs up log files before rolling back
·License key is masked by default.
·New Dashboard provides a snapshot of the scan results over a pre-selected period and helps you to inspect the scans in greater detail.
·The landing page has been changed from the License Information page to the Dashboard
·New Services Health page to monitor the workloads by service and queues.
·New Notification panel that displays messages about the progress of scan reports.
·Active Reports page enhanced with:
oNew Profile column for the Active Reports list
oAutomatic page refresh to view the progress of scans
·Users can download logs directly from Logs page
·Added scan support for PowerShell files (.ps1 and .psm1)
·Improved the processing performance of the Document Processing service
The following is a list of issues addressed in this release.
A 200 MB Excel file cannot be processed by the Analysis service
NOTE: Excel files up to 500 MB can be processed successfully on a server with 32 GB RAM and 8 cores.
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