The Business Problem
An incident register records what happened, but it does not automatically show which pattern matters most. Leaders need to separate routine volume from serious exposure, understand response performance and identify where recurring categories or SLA breaches require intervention.
Without a shared analytical view, operational reviews can focus on totals while missing the combination of severity, exposure, location and response delay that defines real risk.
The dashboard turns incident history into a triage view: what is driving risk, where is it concentrated and which records need attention first?
What I Built
I created an interactive security incident dashboard using a synthetic dataset covering 260 events, six fictional clients, five regions, seven categories and four severity levels. Date, client, region, category, severity and response-time controls update the full report together.
The experience combines conditional KPIs, a weekly incident trend, category distribution, category risk, client exposure, response SLA, a regional heat map, generated analyst notes and a priority-sorted incident register.
Solution Architecture
The product follows an incident-intelligence flow from structured event capture to risk scoring, visual monitoring and accountable follow-up.
Incident capture
Standardize events Record date, client, region, site, category, severity and owner.
Comparable records Consistent incident data ready for analysis.
Response context
Measure service Compare first-response time with severity-specific SLA targets.
SLA status Met or breached response expectation for every event.
Risk logic
Weight priority Combine severity, exposure and SLA breach pressure into a risk index.
Triage order Highest-risk incidents move to the top.
Visual control layer
Explain the pattern KPIs, trend, category split, client bars, SLA and regional heat update together.
Shared risk view Volume, severity and response are visible in one place.
Action output
Assign and review Use analyst notes, accountable owners and the filtered register for follow-up.
Operational response Escalate, investigate or coach using the selected evidence.
The Data Model
Each synthetic row represents one incident and includes the event date, client, region, site, category, severity, response minutes, SLA target and status, exposure value and accountable owner.
The model is intentionally traceable: every total and chart segment can be connected back to the detailed event register that produced it.
The Analytical Logic
Critical and high-severity events drive the critical-share KPI. Average response time and the percentage of events meeting their severity-specific target explain service performance.
The risk index weights severity against exposure and adds pressure when an incident breaches its SLA. This prevents a high-volume but low-impact category from automatically outranking a smaller group of serious, delayed incidents.
Dashboard Experience
The report opens with the five measures needed for an executive scan: selected incidents, critical share, average response, SLA met and total risk index. The visual rows then explain trend, category mix, client exposure and regional pressure.
Conditional formatting and tooltips keep the canvas clear, while generated analyst notes convert the selected filter context into concise operational cues.
Key Decisions Enabled
The dashboard helps teams decide which incident categories require root-cause review, which region or client carries the greatest exposure, where response performance needs correction and which high-risk incidents require escalation.
It also supports governance conversations by keeping the responsible owner and detailed evidence available alongside the management summary.
Power BI Techniques Demonstrated
The project demonstrates a star-schema-ready incident model, severity-aware measures, dynamic filter context, conditional KPI cards, category and regional comparisons, heat-map logic, ranked exception tables, dynamic commentary and CSV export.
Production Path
A production version could connect to an incident-management platform, control-room logs and client systems; add automated refresh, notifications, workflow states, evidence attachments, role-based access, audit trails and governed category definitions.
I use synthetic data here to demonstrate the analytical design rather than reproduce a live security incident system.
The Value In One Sentence
Incident Categories Dashboard demonstrates how I transform security event data into decision intelligence that helps leaders understand incident patterns, monitor response performance and prioritize the risks that need action.