In this chapter, we discussed how to derive insights from the raw data—compute descriptive statistics and aggregates and draw basic plots of relationships—and use special tools for big data visualization. As a result, we've learned how to start working with the dataset, investigate its overall properties, and drill down to specific details. We also learned how to visualize data, a vital skill for both personal data exploration and sharing the insights with a broad audience. These skills are fundamental for data analysis—knowing what to ask and how to answer your question with the data and noticing patterns and anomalies in the data and being able to interpret them and speculate on their origins.

In our next chapter, we'll go a step further in that direction, leveraging statistical and machine learning models to guide our interpretation.