Data analysis is an important aspect in the criminal justice

Data analysis is an important aspect in the criminal justice; in this case the data can be used to predicting the human behavioral changes. The researcher especially social scientist can correlate the cause and the effect of different variables. Specifically, this can assist the police in correlating the causes of crime in various places. For instance they can be able to correlate school truancy and the increased level of burglary. Data analysis helps in projecting the crimes and therefore helping the police to focus the areas which projection of criminal activities is high.

Rigorous data analysis has helped the police department in formulating the modern predictive policing which is an offshoot of Compstat. Compstat is applied in identifying causes of crimes and their geographic ‘hotspots’ strategy in or the specific areas where the prevalence of crime is high. This approach relies on the data collection and organization within the police department as it relies on having regular, real-time access to data about complaints, arrests, calls for service and crime and disorder data. Recently the police department has adopted use of GIS mapping which is used in tracking the crimes trend and therefore drawing the right conclusion about the causes of crimes. This will help the criminal justice professionals in using a right combatant tactics. In this sense the police may decide deploy more security officers on foot patrol.

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Data analysis can improve the analysis of the criminal justice system professional by aiding them to applying a right a thesis and strategy in mitigating criminal activities in the neighborhood. For instance they may adopt use of broken window thesis which adopts that when there is a break in one apartment, and the windows are left without being repaired, then there are high chances of crimes happening in the neighborhood. This theory supports an immediate repaired of the broken parts so as the method of preventing further crime activities in the neighborhood.