1. Getting started with data visualization in Excel
Welcome to this course! I am Agata, and it's my pleasure to introduce you to the world of data visualization in Excel!
2. Excel - the world's most versatile data analysis tool
Excel is the world's favorite data analysis tool. Thanks to its cells arranged in rows and columns, it offers great flexibility for data manipulations and performing arithmetic operations. But did you know that it can also visualize your data and insights?
From basic to advanced charts and dashboards, Excel is a good starting point on your journey toward other data visualization tools such as Tableau or Power BI.
3. What is Data Visualization?
But what is data visualization? It is a graphical representation of information, facilitating communication of often complex data to wide audiences who aren't necessarily experts on the subject.
It involves the application of knowledge and selection of suitable charts for specific objectives, along with the incorporation of visual design elements.
4. The power of visualizing your data
Why is visualizing data important? Did you know that 90% of the information absorbed by the brain is visual? Remember the last time you were admiring the stillness of nature?
Suddenly, the corner of your eye detected an almost imperceptible movement as a squirrel rushed up the tree. This broke the pattern, as just seconds ago, everything in nature was still. You surely spotted the squirrel faster than you would have if someone handed you a structured printout list of all the flora and fauna visible to your eyes at that moment in time.
This is because our brains are wired for pattern recognition. We can spot trends and irregularities much faster when the data is visualized rather than presented in a flat or tabular format. We will leverage this skill throughout this course.
5. What will we cover in this course?
The first chapter will focus on building basic charts and adapting them to our purposes.
In the second chapter, we will advance to more complex charts and learn how to build, among others, scatter plots and waterfall charts.
Chapter 3 will focus on data visualization best practices. We will discover the dos and don'ts and learn how to leverage various chart elements and features.
Finally, in Chapter 4, we will work with disaggregated data and explore pivot tables and charts, progressing toward mini dashboards.
6. Bar and column charts
Let's look at the first set of charts we will encounter in this chapter.
Bar and column charts offer a simple yet effective way to compare values across different categories. They come in clustered or stacked variants and, if formatted properly, can offer immediate insight into the data at hand.
In many cases, these charts can be used interchangeably. However, be aware that if the category labels are lengthy, a bar chart provides more space for the labels.
Be mindful that the human eye processes information from top to bottom and left to right. Therefore, how you sort the values in your bar chart is very important.
7. Line and area
Line and area charts are brilliant choices when visualizing trends and patterns of measures over time, for example, the evolution of sales. Even with multiple lines, the chart is legible and allows for immediate comparison of measures.
Area charts are similar to line charts; however, the area below the line is filled. They work best in the stacked variant and are an excellent choice when illustrating the magnitude of change in a dataset over time or across categories.
8. Pies and doughnuts
Next up are the pie and doughnut charts. These popular charts are used to visualize the proportions of a whole. However, they are often used incorrectly.
It is difficult for the human eye to accurately assess the angle of many slices in a pie or doughnut chart.
9. Pies and doughnuts
Therefore, it is highly recommended to use these charts only when dealing with a limited number of categories.
10. Our dataset for this course: "We Have It All"
Throughout this course, our focus will be on analyzing a commercial dataset obtained from a fictitious enterprise named "We Have It All." We will examine the data from various dimensional perspectives such as region or product. We will also work with various calculations on measures such as sales and profit.
Additionally, we will explore both raw, disaggregated data tables, as well as summarized, aggregated data tables.
11. Let's get started!
Let's get started!