This presentation provides an analysis of crimes in Chicago based on statistics, frequency, occurrence, districts, and location description. The data shows that theft is the most common crime in Chicago and most of the crimes are of non-domestic in nature. The presentation also explores the occurrence of crimes, crimes in districts, and location description of crimes. Additionally, it raises the question of whether the CLEAR initiative undertaken by Chicago police has been able to reduce the incidence of crime.

Big Data and Analytics Group Assignment

The assignment requires students to work in teams to write a Data Analytical report using Watson Analytics to analyze and visualize a given dataset on reported incidents of crime.

Discover crime statistics, types, districts, and locations in Chicago. Evaluate CLEAR initiative's impact on crime reduction.

Analysis of Crimes in Chicago: Statistics, Frequency, Occurrence, Districts, and Location Description

This article provides an analysis of crimes in Chicago using Big Data and Analytics. It includes reporting/dashboards, advanced insights, research, and recommendations for the police chief.

Hartpury University and Hartpury College

Data Science and Big Data

Statistics and Probability

Big Data and Analytics - Analysis of Crimes in Chicago

This article explores the analysis of crimes in Chicago using big data and analytics. It covers different crimes, locations, and trends. The article provides recommendations for the police chief based on the analysis. The article is relevant for courses related to data analytics, criminology, and law enforcement.

Big Data and Analytics

Software Engineering Assignment (Solved)

This report provides insights into the crime trends in Chicago from 2012 to 2016. The report covers the number of crimes reported, types of crimes, locations, and districts. The report also provides recommendations to the police chief to control the crime rate.

Real Time Analytics - Analysis of Chicago Crime Data

This report provides insights on crime trends in Chicago based on data analysis and dashboard representation. The report recommends measures to control crimes and increase vigilance in vulnerable areas.

Big Data and Analytics: Insights on Crime Trends in Chicago

This project analyzes the crime records in Chicago City from 2012 to 2017 using IBM Watson data analytics tool. The report provides insights on trends, types of crimes, locations, and recommendations for police chief. The dataset contains 24 columns with data about a crime and its different attributes. The analysis suggests increasing police patrolling on streets and improving response time against theft, battery, and narcotics. The report also highlights the increase in the number of homicides in 2016 compared to previous years.

Analysis of Crimes in Chicago: Statistics, Frequency, Occurrence, Districts, and Location Description

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Big Data and Analytics - Analysis of Crimes in Chicago

Big Data and Analytics

Software Engineering Assignment (Solved)

Real Time Analytics - Analysis of Chicago Crime Data

Big Data and Analytics: Insights on Crime Trends in Chicago

Big Data Analytics for Crime Prevention in Chicago City

Analysis of Crimes in Chicago: Statistics, Frequency, Occurrence, Districts, and Location Description

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Big Data and Analytics - Analysis of Crimes in Chicago

Big Data and Analytics

Software Engineering Assignment (Solved)

Real Time Analytics - Analysis of Chicago Crime Data

Big Data and Analytics: Insights on Crime Trends in Chicago

Big Data Analytics for Crime Prevention in Chicago City