Inside the Analyst’s Mind
Explore how data analysts approach problems by understanding key questions and examining a typical day in their workflow to see the implementation of these skills.
We'll cover the following...
In our last lesson, we learned what data is, why it’s so important, and the big picture of what data analysts do. Now, it’s time to dive deeper. Imagine we’re going behind-the-scenes, right into the mind of a data analyst. We’ll explore how they think by examining the kinds of questions they ask, then we’ll walk through a typical “day in the life” to see how they put their skills to practice.
How analysts think
Data, by itself, is just raw information. It’s like a giant pile of LEGO bricks. We can have all the bricks in the world, but if we don’t have a plan or a question, we won’t build anything meaningful. This is where the analyst’s mindset comes in: they know how to ask the right questions to transform that ineffective pile of bricks into something meaningful, like a towering castle or a speedy race car. Asking smart questions is the very first step to uncovering the insights hidden within data.
Data analysts ask different kinds of questions to reveal different layers of understanding. This helps them move beyond just the observation of what happened to understanding why it happened, what will happen, and what should be done.
Descriptive analysis
When we use descriptive analysis, we’re acting like historians. Our main goal is to summarize and describe what has already occurred. We’re asking, “What happened?”
For example, imagine we run an online shoe store. A descriptive question might be: “How many pairs of running shoes did we sell last month?” or, “What was the average price of sneakers sold in the last quarter?” The analyst’s role here is to gather all the sales data, and present these facts clearly, often using simple charts or summaries. We’re simply reporting on the past.
Informational note: Descriptive analysis forms the foundation for all other types of analysis. We can’t figure out why something happened or what will happen, if we don’t first understand what happened!
Diagnostic analysis
With diagnostic analysis, we become detectives. Once we know “what happened,” we want to understand “why it happened.” This type of analysis involves digging deeper into the data to find the root causes behind trends, changes, or unusual events.
Diagnostic analysis often involves looking for “outliers” (data points that are very different from others) or sudden shifts in trends, as these can be strong indicators of a root cause. Tools like “root cause analysis” are often applied here. ...