In this chapter, we provided a universal definition for data mining, listed the most common techniques used by data scientists, and stated the overall objective of the efforts. Data mining was also compared to data querying and, using R, various working examples were given to illustrate certain key techniques. Finally, the concepts of dimensional reduction, frequent patterning, and sequence mining were explored.
The next chapter will be a hands-on introduction to statistical analysis of data through the eyes of a data developer, providing instructions for describing the nature of data, exploring relationships presented in data, creating a summarization model from data, proving the validly of a data model, and employing predictive analytics on a data developed model.