In this chapter, we presented an overview of the data analysis ecosystem and explained the basic concepts of the data analysis process and tools, as well as some insight into the practical applications of data analysis. We have also provided an overview of the different kinds of data, both numerical and categorical. We got into the nature of data: structured (databases, logs, and reports) and unstructured (image collections, social networks, and text mining). Then, we introduced the importance of data visualization and how a fine visualization can help us with exploratory data analysis. Finally, we explored some of the concepts of big data, quantified self-, and social network-analytics.

In the next chapter we will look at the cleaning, processing, and transforming of data using Python and OpenRefine.