Working with data details the earliest processes of data science problem solving. The 1st step is to identify the problem, which determines all else that needs to be done. The 2nd step is to gather data. The 3rd step is to wrangle (munge) data, which is critical. Wrangling is getting data into a form that is useful for machine learning and other data science problems. Of course, wrangled data will probably have to be cleaned. The 4th step is to visualize the data. Visualization helps you get to know the data and, hopefully, identify patterns.