UNT Police Dashboard

Data-driven public safety capstone.

Problem Statement

The University Police Department required a centralized view of incident data to identify crime hotspots, monitor response times, and allocate patrol resources more effectively across campus.

My Role

  • Collaborated with stakeholders to define reporting requirements.
  • Modeled complex incident data using a Star Schema approach.
  • Developed comprehensive Power BI reports using advanced DAX measures.

Tools & Tech

Power BI DAX SQL Public Safety

Dataset / Inputs

Anonymized police incident reports, call-for-service logs, campus geospatial data, and shift schedules.

Approach

1. Requirement Analysis

Conducted interviews with department officials to understand their primary decision-making needs and pain points.

2. Data Modeling

Transformed flat files into a relational model (Star Schema) to enable fast filtering and drilling down by time, location, and incident type.

3. Dashboard Construction

Designed intuitive visuals including heatmaps for location analysis and trend lines for temporal tracking.

Key Insights

  • Identified specific parking structures with higher rates of property crime during evening hours.
  • Revealed seasonal trends in service calls related to the academic calendar.
  • Highlighted variance in response times across different campus zones.

Business Impact

  • Resource Optimization: Enabled targeted patrolling in identified hotspots.
  • Transparency: Provided leadership with a clear, data-backed view of campus safety metrics.
  • Strategic Planning: Supported long-term staffing decisions based on peak incident times.