Chicago Crime Dataset Analysis

Overview:

This repository contains the SQL code for the Chicago Crime Dataset, which reflects reported incidents of crime in the City of Chicago from 2001 to the present. The dataset is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system and is stored in Google BigQuery for analysis.

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Google's BigQuery is a managed data warehouse service that operates without the need for servers, enabling scalable analysis of large data sets. This Platform as a Service (PaaS) supports querying using SQL and includes native machine learning features.

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Objective:

The primary objective of this project is to conduct a comprehensive analysis of the Chicago Crime Dataset using SQL queries in Google BigQuery. By leveraging SQL, we aim to uncover insights, patterns, and trends within the dataset that can inform decision-making for law enforcement agencies, policymakers, and community stakeholders.

Technologies Used:

• Google BigQuery.
• SQL.
• Google Data Studio/Looker and Sheets (for visualization).
• Git (for version control).

Contents:

• SQL_Code/: Contains SQL script used for analysis and visualization in Google BigQuery.
• Documentation/: Documentation site link for project reports, analysis summaries, and any supplementary materials.
• README.md: This file, provides an overview of the project, its objectives, and contents.

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Prerequisite:

GCP account is necessary to access and run SQL queries in BigQuery. If you don't have a GCP account, you can sign up for free here.

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Getting Started:

To get started with the analysis, follow these steps:

1. Clone the repository to your local machine using Git.
2. Navigate to the Project's_Code/ directory to access the SQL script for analysis.
3. Open the script in Google BigQuery or any SQL editor of your choice to execute the queries and perform the analysis.

Usage:

• Execute the SQL script in Google BigQuery to analyze the Chicago Crime Dataset.
• Visualize the results using Google Looker Studio or any other visualization tool.
• Modify and customize the analysis as needed for specific insights and requirements.

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Contributors:

• Kevin Ndungu: Project lead and primary contributor.