Angol
Government entities and private organizations regularly use data and analytics to maximize efficiency. Law enforcement agencies are increasingly using data to predict where crime is likely to occur and how to address it. Data-Driven Policing provides an overview of the various areas of data-driven policing and applies them to police management, policies, and development of strategies and decisions. The book examines the role of data in both historical and contemporary policing and looks at the utilization of data-driven policing in community-based, collaborative problem-solving as well as in reducing police misconduct.
The book is presented in four sections. Section 1 examines the importance of using data in policing, the historical evolution of policing, and the role of data in guiding policing strategies. Section 2 addresses the primary approaches currently defining the application of data to police practices. Section 3 concerns the application of data to police management. Section 4 synthesizes the information and includes chapters devoted to understanding data-driven policing initiatives and to directions for data-driven policing in the future. The authors provide clear, up-to-date information about data-driven strategies and contextualize these approaches with theoretical and applied perspectives and pertinent examples. This book is appropriate for policing classes and classes supporting crime and intelligence analysis at the undergraduate and graduate levels, as well as for law enforcement administrators and training programs.
