Introduction data analytics using Python for auditors. Originaly developed by Steve Rummel as a case study using Python to help auditors begin to build theiy Python skills, but the exercise may be completed using any adequate tool.
Current solutions exist in Alteryx, but are proprietary to the deveoper (not me). It should be easy to solve in any SQL database, MS PowerQuery, FoxPro (for those of you who have been around for a while) or Audit Command Language (if you really must) as well.
Run the file 'Introduction to Python - Extract, Transform, Load (ETL) v1.ipynb' and it will generate the relevant data files, etc. You can see comments in the file that detail what is being done.
If you run the second file, 'Introduction to Python - Extract, Transform, Load (ETL) Solution v1.ipynb' it will load the datafiles generated by the first and solve the business problem, plus generate a nice basic graph.
Ideally, the student will complete the exercises in the first file, then use the second notebook to understand what a solution would look like and how to implement it. There are some basic charts in there as well for reference.
Constructive criticism is always welcome. If there is interest, I will consider expanding the scope of the case study.
This case study is based on business cases and issues I have run into during my 15+ years spent helping clients fix data-related issues. It covers the essential skills of an audit analytics practitioner, both tool-wise (i.e., Python) and thought-process-wise. It has been a useful primer in training my current team of data specialists at CVS Health in audit analytics. I hope you find it useful.