In this chapter, we briefly discussed data science and what role machine learning plays in it. Then we talked about doing a data science project, and what methodologies are useful for it. We discussed one of them, CRISP-DM, the steps it defines, how these steps are related and the outcome of each step.
Finally, we spoke about why doing a data science project in Java is a good idea, it is statically compiled, it's fast, and often the existing production systems already run in Java. We also mentioned libraries and frameworks one can use to successfully accomplish a data science project using the Java language.
With this foundation, we will now go to the most important (and most time-consuming) step in a data science project--Data Preparation.