Without data you’re just another person with an opinion.
—W. Edwards Deming, Data Scientist [1]
Learning about data analytics tools and methods typically begins with discussions of how to prepare a given dataset for analysis. The reason for this is that many datasets have problems – defects in design, missing or incorrect data items, and non-standard file formats. This often leads to lengthy and complex tasks required to produce datasets ready for efficient analysis. Unfortunately, the critical first step – understanding the nature of data representation – is frequently missing or not ...
