Monthly reports

Data Sources

File	Key Fields
applications	status, accountsUsed, accountsDetected, category, classificationId, sources, lastActivity
users	status, vendorsUsed, vendorsDetected, emails

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1. Application Status Distribution

Each application is bucketed by its status field:

Status	Filter
Approved	status == 'approved'
Discovered	status == 'discovered'
Security Concern	status == 'security-concern'
In Review	status == 'in-review'
Evaluation	status == 'evaluation-period'
Closed	status == 'closed'

Each is displayed as a count and percentage of total_apps.

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2. Security Threat Metrics

Metric	Formula
Total Security	Count of apps where status == 'security-concern'
Contained	Subset where accountsUsed == 0 (no active users)
Active	Subset where accountsUsed > 0 (still in use)
Active Security Users	Sum of accountsUsed across all active security threats
Threat Containment Rate	contained / total_security × 100

A security threat is considered contained when it has been driven to zero active users.

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3. Shadow IT Metrics

Shadow IT includes apps with status in: discovered, security-concern, in-review.

Metric	Formula
Total Shadow	Count of apps with shadow IT status
Eliminated	Subset where accountsUsed == 0
Active Shadow	Subset where accountsUsed > 0
Shadow Reduction Rate	eliminated / total_shadow × 100

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4. Governance Coverage

Governed statuses: approved, in-review, evaluation-period, closed.

Metric	Formula
Governed Apps	Count of apps with a governed status
Governance Rate	governed_apps / total_apps × 100

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5. User Metrics

User Segmentation

Segment	Filter
Active Users	status == 'live' AND vendorsUsed > 0
Offboarding with Usage	status in ['offboarding', 'deactivated'] AND vendorsUsed > 0
Inactive Users	vendorsUsed == 0 (any status)

User Compliance Rate

A user is compliant if they use fewer than 30 vendors (compliance_threshold).

Metric	Formula
Compliant Users	Active users where vendorsUsed < 30
Compliance Rate	compliant_users / active_users × 100

Usage Efficiency

Metric	Formula
Avg Detected	Average vendorsDetected across active users
Avg Used	Average vendorsUsed across active users
Usage Efficiency	avg_used / avg_detected × 100

User Distribution

Active users are bucketed by vendorsDetected into ranges: 0–20, 21–50, 51–100, 101–150, 150+.

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6. AI Metrics

AI App Detection

An app is classified as AI if:

• Its category is "Artificial Intelligence and Automation"

AI Indicators

Metric	Filter
AI Total	All AI-classified apps
AI Security	AI apps with status == 'security-concern'
AI Active Threats	AI security apps with accountsUsed > 0
AI Active Users	Sum of accountsUsed on active AI threats
AI Discovered	AI apps with status == 'discovered' and accountsUsed > 0
AI Approved	AI apps with status == 'approved'
AI Pending	AI apps with status in ['in-review', 'discovered']

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7. Report Tables

Active Security Threats

Top 15 security-concern apps with accountsUsed > 0, sorted by active users descending. Shows a conversion percentage: accountsUsed / accountsDetected × 100.

High-Risk Discoveries

discovered apps with accountsUsed >= 10 (high_risk_user_threshold), sorted by active users descending, top 15.

Remediation Priority

Active security threats are assigned a priority based on accountsUsed:

Priority	Condition
P1 — Critical	accountsUsed >= 15
P2 — High	accountsUsed >= 5
P3 — Medium	accountsUsed < 5

Pending Governance

discovered apps with accountsUsed >= 20, sorted by active users descending, top 10.

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Key Concepts

• An app is contained/eliminated when accountsUsed == 0 — no one is actively using it.

• An app is an active risk when accountsUsed > 0.

• User compliance is based on keeping vendor usage below 30 apps per user.

• Usage efficiency measures what fraction of detected apps are actually used.

• Governance coverage tracks how many apps have moved beyond the "discovered" stage into a managed status.