Select an industrial analytics use case from fields such as manufacturing analytics, marketing analytics, hr analytics or sales analytics..etc.

Apply the CRISP (Cross industry standard process for data mining) steps to your use case:

1. Define the problem and possible business outcomes/objectives that you can achieve by applying analytics solutions.
2. What kind of data do you need to build the solution? From which processes can you gather that data?
3. Which analytical approach(es) you should use to solve the business problem? (Supervised/unsupervised) Why?

What kind of a machine learning model you should use ? (Regression models, classification models, segmentation models..etc)

How would you test the success of the model?

4. What will be your target (if any) and what will be your possible features that will be given as an input to your model?