With the increasing demand to analyse large amounts of data within small time frames, organisations prefer working with the data directly over samples. This presents a herculean task for a data scientist with limitation of time.
Extracted from Chicago Police Department’s CLEAR (Citizen Law Enforcement Analysis and Reporting) system, this data set contains information on reported incidents of crime in the city of Chicago from 2001 to present, with the absence of data from the most recent seven days. Not included in the data set, is data on murder, where data is recorded for each victim.
It contains 6.51 million rows and 22 columns, and is a multi-classification problem. In order to achieve mastery over working with abundant data, this data set can serve as the ideal stepping stone in the pursuit of tackling mountainous data.