Example of a Custom Report for Target Segments

Below is an example of a "Monthly Data Risk & Remediation Report" designed for a specific business unit (e.g., the Finance Department). This report assumes you have segmented your targets using the tag Dept: Finance.

Report Title: Monthly Sensitive Data Governance Summary

Target Segment: Finance_Department_Assets (All targets tagged Dept: Finance)
Reporting Period: October 1, 2023 – October 31, 2023
Audience: VP of Finance / Data Privacy Officer

1. Coverage Summary (The "Are we looking?" section)

This section proves that the Finance department's assets are being monitored as promised.

• Total Assets in Segment: 45 (12 Databases, 28 File Shares, 5 SharePoint Sites)
• Scan Success Rate: 98% (44 of 45 targets successfully scanned this month)
• Last Scan Date: All targets scanned within the last 7 days.
• Gaps Identified: 1 File Share (\\Fin-Server\Legacy_Archive) returned an "Access Denied" error; ticket #12345 opened for permissions fix.

2. Risk Findings (The "What did we find?" section)

A breakdown of the sensitive data discovered within this specific segment.

• Total Sensitive Matches: 1,240
• Top Data Types Found:
• • Credit Card Numbers (PCI): 850 matches (Primary location: \\Fin-Server\Invoices)
  • Social Security Numbers (PII): 340 matches (Primary location: \\Fin-Server\Payroll_Exports)
  • Bank Account Numbers: 50 matches
• Risk Trend: -15% reduction in total matches compared to last month.

3. Remediation Activity (The "What did we do about it?" section)

This is the most important section for proving the value of the program. It shows the outcome of your Playbooks.

• Automated Actions Taken:
• • Shredded: 400 files (Temporary exports older than 90 days).
  • Quarantined: 150 files (Sensitive files found in "Public" folders moved to \\Secure\Finance_Vault).
  • Notified: 25 Data Owners alerted via email regarding unencrypted spreadsheets.
• Manual Actions Pending: 12 high-risk files in the Payroll_Exports folder require manual review by the Finance Manager.

4. Top 5 "At-Risk" Locations

A targeted list to help the Finance team prioritize their manual cleanup efforts.

1. \\Fin-Server\Invoices\2022_Archive (600 PCI matches)
2. SharePoint: Finance_Team_Site / General / Drafts (120 PII matches)
3. SQL_Server: Finance_Prod / Table: Customer_Profiles (50 Bank Account matches)
4. ... (and so on)

How to Generate This Report in Spirion Sensitive Data Platform

To create this report, you would use the Report Builder with the following filters:

1. Filter by Target Tag: Set Target Tag EQUALS Dept: Finance.
2. Filter by Date: Set Scan Date to Last 30 Days.
3. Group By: Group results by Target Name and Data Type.
4. Columns to Include:
5. • Target Name
   • Match Count
   • Data Type
   • Remediation Status (to show Shredded/Quarantined/Pending)
   • Last Scan Date

Tip: The "Zero-Risk" Goal

For highly regulated segments (like Finance), your goal is to eventually produce a report where the "Risk Findings" section is near zero.

If you see a spike in a custom report for a specific segment, it usually indicates a Process Failure (e.g., a new automated report is exporting unencrypted data to a public share). By having a custom report for that segment, you catch the spike immediately rather than losing it in the "noise" of a company-wide report.

Summary

This custom report transforms raw technical data into a Business Narrative. It tells the VP of Finance: "We are scanning your data, we found these specific risks, we have already automated the cleanup of 80% of them, and here is the small list of items your team needs to review."