Artificial Intelligence for Marketing. Sterne Jim

■ Data set E has no field for a middle initial.

       ■ Data set F stores transaction numbers but not customer IDs.

       ■ Data set G does not include in‐page actions, only clicks.

       ■ Data set H stores a smartphone's IMEI or MEID number rather than its phone number.

       ■ Data set I is missing a significant number of values.

       ■ Data set J uses a different scale of measurements.

       ■ Data set K, and so on.

      It's easy to see how much work goes into data cleansing and normalization. This seems to be a natural challenge for a machine learning application.