Summary

Congratulations on your excellent progress in this chapter. Together, we learned the fundamental data visualization paradigms, such as summarizing and comparing populations, examining the relationships between attributes, adding visual dimensions, and comparing trends. These visualization techniques are very useful in effective data analytics.

All of the data we used in this chapter had been cleaned and preprocessed so we could focus on learning the visualization goals of data analytics. Now that you are on your way toward learning about effective data preprocessing in the next chapters, this deeper understanding of data visualization will help you become more effective in data preprocessing, and in turn, become more effective in data visualization and analytics.

In the next two chapters, we will continue learning about other data analytics goals, namely, prediction, classification, and clustering, before we start introducing effective preprocessing techniques.

Before...