Denver Crime Dashboard

Role: Data Analyst | Tools: Tableau, Excel | Data Source: Kaggle (Denver Crime Statistics)

Quick Links: Tableau Dashboard | Data Set

Executive Summary:

Developed an interactive Tableau dashboard to analyze Denver crime trends from 2021–2022 and support data-driven resource allocation for law enforcement and city planning. The dashboard highlights neighborhood hotspots, peak crime times, and category-level changes, enabling strategic recommendations such as targeted policing, adjusted patrol schedules, and community prevention initiatives.

Business Problem:

With limited staffing and budgets, law enforcement must deploy resources strategically. This project sought to answer 3 questions:

  • Which neighborhoods experienced the largest year-over-year increases in crime?

  • When are crimes most likely to occur, and how does this vary by weekday?

  • Which crime categories require targeted intervention?

Approach:

  • KPIs: Created 5 KPIs for total, violent, and non-violent crime.

  • Heat Maps: Built geographic heat maps to identify high-crime neighborhoods.

  • Time Periods: Analyzed temporal patterns by hour and weekday to pinpoint peak crime periods.

  • Filters: Incorporated filters for district, crime type, and year-over-year percentage changes.

  • User Experience: Designed from the perspective of police and city planners, focusing on actionable insights.

Findings & Recommendations:

  • Findings:

    • DIA and University Hills had the steepest increases in auto-related crimes.

    • Weekday midday hours (11 am – 3 pm) showed the highest spike in incidents.

    • Non-violent crimes, especially auto theft, grew more sharply than violent offenses.

  • Recommendations:

    • Neighborhood Targeting: Increase patrol presence and implement theft-prevention programs in DIA and University Hills.

    • Patrol Scheduling: Reallocate resources to cover weekday midday hours.

    • Public Education: Launch community campaigns to reduce auto theft in high-risk neighborhoods.

Impact:

  • Built 4 visualization types, 9 filter types, and 5 KPIs to enable granular, data-driven analysis.

  • Created a decision-support tool for strategic policing and city safety planning.

  • Shared the dashboard with professional colleagues, leading to further Tableau project collaborations.