BANA-680 Data Management for Business Analytics Project C
Due Date: Please see syllabus
The Canadian border sees significant traffic flow from the US. The Government of Canada collects detailed information about wait times at its various crossings and publishes the data in https://open.canada.ca/data/en/dataset/000fe5aa-1d77-42d1-bfe7-458c51dacfef . You are asked to use the information for 2015-2017 in a csv files in this link. These files provide periodic information for all crossings. A traveler can peruse these files and determine typical wait times and use it for travel planning. However, the files are exceedingly large – one would need software such as Python to efficiently utilize the data.
You will produce a pdf (from printing an iPython notebook) that will address three issues:
- Using visualization, highlight key learnings from the data about border crossing into Canada.
- Using regression analysis, with 2015-2016 as training set, predict wait times in 2017 and provide a summary.
- Design an app (= user friendly function) of potential use to a traveler to Canada.
The page limit is 20. Please do not compress the output – I will award zero points to projects that are difficult to read.
This is an open-ended project – a wide variety of approaches are feasible. You are encouraged to focus on the main questions asked and provide meaningful results and conclusions. Technology/coding is a tool that helps you answer questions – so make the tools work for you. Often the most important answers are found in simple averages, data counts, and histograms!
You have come a long way this term, from not knowing much about Python Pandas, to doing meaningful work. This is your chance to take your game to the next level. In this project you will be utilizing skills in processing time, text data, data cleaning, summarizing, computing, plotting, and predictive modeling. But these skills are wasted without coherent reporting. You will display your skill in reporting in this project – this means many things including selection of material, formatting, clear writing, and summarizing.