Summary

In this chapter, we said that, currently, how data science is defined is a matter of opinion. A practical explanation is that data science is a progression or, even better, an evolution of thought, consisting of collecting, processing, exploring, and visualizing data, analyzing (data) and/or applying machine learning (to the data), and then deciding (or planning) based upon acquired insight(s).

Then, with the goal of thinking like a data scientist, we introduced and defined a number of common terms and concepts a data scientist should be comfortable with.

In the next chapter, we will present and explain how a data developer might understand and approach the topic of data cleaning using several common statistical methods.