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Data-driven Decision Making with Chicago Crimes Dataset

Marvin Herchenbach and four other team members

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Abstract

The task is to find out which crimes are committed in Chicago and where or when they are committed. A US non-governmental organization (NGO) has been commissioned to investigate crime in this major city. Once known as a major automobile metropolis, the city has been struggling with rising crime rates for many years, and residents are becoming increasingly concerned. In order to give the citizens more confidence in the police, data-based decisions are to be made on where new officers should be deployed and where more controls are needed.

Please note: All project files are in German, as this was the language of the course.

Structure

+-- images                    
+-- data_driven_decisions_teamwork.ipynb
+-- data_driven_decisions_teamwork.html
+-- onepager-final.pdf
+-- README.md

Links to Ressources

• Data_Analytics as iPython
• Data_Analytics as HTML
• Final Presentation as PDF

Ressources

• Code: https://www.kaggle.com/currie32/crimes-in-chicago

Author

• Marvin Herchenbach and four other team members - If you have questions you can contact me under marv.her@t-online.de

License

This project was done during my Managing Technology Change (MTC) Seminar in Group "Data Driving Decision Making" from Chair WI3 for IT-Management at the Friedrich Alexander University in Erlangen-Nürnberg.

Acknowledgments

• Thanks a lot to Markus Schmitz from Chair WI3 for IT-Management for the great exercises and supervision!