It is essential to start with a business vision of the problem you are working on. What are the KPIs? What are the parameters that can influence these KPIs? What types of results would be useful?
The actual “data science” phase consists of gathering data, cleaning it if necessary, and injecting it into different models to find the best performance.
The last phase is crucial: it is the insertion of the model into the industrial process, taking into account the added value of human supervision, the performance and reliability of algorithms.