Introduction

In the previous chapter, we developed the skills necessary to effectively analyze data within a SQL database, and in this chapter, we will turn our attention to the efficiency of this analysis, investigating how we can increase the performance of our SQL queries. Efficiency and performance are key components of data analytics since without considering these factors, physical constraints such as time and processing power can significantly affect the outcome of an analysis. To elaborate on these limitations, we can consider two separate scenarios.

Say that we are performing post hoc analysis (analysis after the fact or event). In this first scenario, we have completed a study and have collected a large dataset of individual observations of a variety of different factors or features. One such example is described within our dealership sales database, which analyzes the sales data for each customer.

With the data collection process, we want to analyze the data for patterns...