A Power BI crime data analysis project for Washington, D.C., uncovering trends, hotspots, and severity to support data-driven decisions. Includes key KPIs like Crime Severity Index, Top 5 Crime Types, and Time of Day insights to guide targeted policing and community safety efforts.
🧩 Problem Statement
Washington, D.C. faces ongoing challenges related to crime and public safety. Addressing these effectively requires deep, data-driven insights into how crime unfolds across time and space.
Using Power BI, this project explores a comprehensive crime dataset to reveal patterns and correlations that can guide decision-making and strategic planning for crime reduction.
Dataset Source → Onyx Data March 2025 Challenge
🧹 Data Cleaning Steps
- Ensured columns are in the correct data type
- Filtered out null values
- Dropped unnecessary columns
📊 Key Performance Indicators (KPIs)
- Total Crimes Reported – Volume of crimes over the selected timeframe
- Crimes by Time of Day – Shift-based crime distribution (Midnight, Day, Evening)
- Top 5 Crime Types – Most frequent offense categories
- Crime Severity Index – Weighted metric using UCR crime rankings
- Crime by Neighborhood – Crime counts by neighborhood cluster
- Hotspot Analysis – Geographic crime concentration visualized
- Weapon-Related Crimes – Percentage involving firearms!
- Time to Resolution – Time from occurrence to report filing
- Trends Over Time – Monthly and yearly crime trend tracking
- Crime Rate by Police District – Crime-to-district comparison for efficiency
📌 Summary of Findings
- Most crimes are non-violent thefts, peaking in the evening hours
- Crimes are geographically clustered, especially in Cluster 2 and 14th Street NW
- Weapon-related and violent crimes are less frequent but contribute to severity
- The Crime Severity Index reflects a moderate risk level (6.33)
- Time-of-day and geographic trends offer clear direction for targeted interventions
✅ Conclusion
The analysis highlights the importance of:
- Focused policing in high-crime areas
- Boosting patrol presence during evening hours
- Community programs to prevent property crimes
- Smarter, data-informed resource deployment
🙌 Credits
This project was completed as part of a group capstone initiative. Special thanks to all team members for their collaboration and contributions:
- 👨💼 George – Group Leader
- 👩💻 Maureen
- 👩💻 Stella
- 👩💻 Naijeria