This document summarizes a project analyzing geolocation crime data from Chicago using HiveQL to determine safe and unsafe areas. The project team downloaded a 1.3GB crime dataset, uploaded it to HDFS, and ran Hive queries to analyze crime types and locations. Visualizations of the query results showed crime counts by type and location. The team created tables in HCatalog and used Beeswax to run queries on the data. Final queries ranked addresses by crime counts to identify unsafe areas. The results could help with targeted advertising and predictive policing.