This repository stores an OLAP analytical project I did with the Chicago historical crime dataset.

The dataset is routinely updated and has all crime reports from 2001 to present. Due to the huge number of records in the dataset (7 million+ by the time I downloaded it), I used PySpark to perform the queries and addressed the OLAP questions.

This project is composed of four main parts:

1. Perform OLAP queries to extract key information from the dataset and address specific questions;
2. Create a geographical heatmap to visualize the distribution of crimes across the city;
3. Perform clustering using the spatial data, and give advice on how to select ideal locations for police stations and helicopter patrol centers;
4. Perform time series analysis and forecast the number of crimes in the future using historical crime data and temperature data;

The results of the analyses can be found in this notebook published on Databricks. A report summary is given at the end of the notebook. A local version of the notebook is provided in this repository as well.

Note: If the geographical map is not showing in the published notebook, you can find a saved html file of the map in this repository.