8 Introduction to Descriptive Analytics

8.1 The Core Measures of Descriptive Analytics

You now have a solid understanding of what Descriptive Analytics is, how it works, and where it’s applied. We’ve established its role as the foundation of business intelligence, focused on answering the crucial question: “What has happened?”

But how do we move from a mountain of raw data—like thousands of sales records or website clicks—to a clear, concise answer? The answer lies in using a specific toolkit of statistical measures. These measures are the workhorses of descriptive analytics, allowing us to summarize the essential characteristics of a dataset with just a handful of numbers. They transform complexity into clarity.

Think of these measures as different lenses through which you can view your data:

One lens helps you find the center or most typical value.
Another shows you how spread out or varied the data points are.
A third describes the overall shape of the data’s distribution.

In the sections that follow, we will delve into these fundamental building blocks. We will start with Measures of Central Tendency to locate the heart of our data, followed by Measures of Dispersion to understand its variability. We will then explore Measures of Skewness and Kurtosis to describe the shape of its distribution.

Mastering these core measures is the first practical step in any data analysis. They provide the quantitative summary needed to create meaningful reports, build insightful dashboards, and lay the groundwork for the diagnostic and predictive analyses to come.