Capturing Data-Driven Insights to Shape Tomorrow’s Law Enforcement

With today’s steadily proliferating supply of data and advanced technologies to tap into it, law enforcement agencies are poised to transform criminal justice processes. Law enforcement professionals can harness the power of data analytics to make sense of this wealth of data and reveal deeper insights into their field’s most pressing issues, such as:

The relationship between criminal propensity and opportunity.
Recidivism among the recently incarcerated.
The effectiveness of community-based policing in achieving the required goals.
Bias in legacy data.
Officer health and wellness.

The sheer volume of data available through local, state, and federal agencies, social media, and other dynamic sources presents both opportunities and challenges.

Data Science Analytical Capabilities

Data Society is well versed in creating the tools and analytical capabilities that power faster, more accurate data analysis. This expertise is instrumental in supporting the emerging priorities of law enforcement agencies and the communities they serve, such as effective policing that meets the expectations of citizens, public leaders, the legal system, and society as a whole. We equip organizations with the tools and techniques that they need to leverage abundant data efficiently and effectively, including:

Data mining for crime forecasting and predictive policing.
Data integration and natural language processing to track drug trafficking trends.
Social media monitoring using data science to analyze social media for criminal activity, such as gang activity, cyberbullying, or threats of violence.
Data-driven resource management to help law enforcement agencies optimize the deployment of resources, such as patrol officers and vehicles, to improve efficiency and reduce crime.

Specialized data science skills and organization-wide data literacy can empower law enforcement agencies to utilize their growing data resources effectively, ethically, and responsibly. Teams with relevant data science skills empower themselves with the best practices for performing critical functions such as:

Collecting and processing structured and unstructured data from diverse sources.
Automating manual processes.
Training models with attention to potential bias in the historical data.
Developing algorithms that offer transparency, explainability, and accountability.
Reporting data-driven insights accurately and compellingly.

Training that prepares teams to harness data for more effective, efficient, and responsible law enforcement efforts spans subjects ranging from foundational to advanced, including:

Fundamentals of Data Literacy.
Data Visualization Design and Storytelling.
Foundations of Big Data.
Data Wrangling in R.
Advanced Clustering in R.
Applications of AI for Anomaly Detection.
Advanced Deep Learning for Object Detection.
Sentiment Analysis in NLP.
Convoluted Neural Networks for Image Recognition.
Fundamentals of Deep Learning for Multiple GPUs.
MLOps CI/CL Theory.

Data-Driven Law Enforcement