On-Demand Webinar

How the Chicago Police Department Improved Public Safety with Data Analytics

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Law enforcement departments have always relied on data to keep the public safe and informed. For the Chicago Police Department (CPD), they're leveraging data analytics to deploy resources across the city, conduct crime analysis for strategic planning, join disparate data across the organization for new insights, and further organizational improvements across the agency. Watch the on-demand webinar below to hear how CPD is developing a data-driven culture to better enable every officer with the tools and insight needed to better serve and protect citizens. Discover how to:

  • Enable a policy of data-driven decision making and organizational analytics
  • Equip all areas of department with access to data and build analytical capacity across the department
  • Create interactive dashboards to improve transparency with the public and within the department

About the speaker

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Sabih Khan

Deputy Chief of the Bureau of Technical Services, Chicago Police Department

Sabih Khan is the Deputy Chief of the Bureau of Technical Services at the Chicago Police Department where he serves as one of the members within the Department’s executive staff. Currently as the commanding officer of the Bureau, Deputy Chief Khan leads the development and management of Chicago Police Department’s technology and data analytics strategy, along with managing the Bureau’s six divisions including the Information Services, Data Analytics, Evidence and Recovered Property, Records, Facilities Management, and General Support Division.

His experience and academic background positions the Chicago Police Department with the ability to develop strategies that increase the Department’s analytics capacity and maintain its position as a model agency across the country for innovative policing technology that embraces the Department’s philosophy of reducing crime through data-driven policing.

Deputy Chief Khan holds a master’s degree in Predictive Analytics and Data Mining from DePaul University.

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