Summary

You will find the techniques covered in this chapter valuable not only initially when working with a new set of data, but throughout the analytic journey as patterns are investigated and further exploration of the results is undertaken.

Understanding the structure of the data in detail is critical before moving on to more sophisticated analytical methods as they often characterize the relationship found into a handful of summary statistics. The diagnostics accompanying these statistics provide a means of assessing how well they capture the patterns, but appreciating in advance where issues are likely to be present helps focus the examination of the results. 

The next chapter will expand on the topic of outliers touched on here and address the issue of missing values. Both of these situations occur regularly when dealing with real data and there are several approaches that can be utilized to detect their presence so that the impact on analytics can be minimized.