Understanding the message delivered in raw data requires you to have a third eye and be keen on details. Initially, most people encountered challenges in analyzing raw data. Thanks to the coolest data visualizations available, the entire process is easier and faster. Data visualization has greatly revolutionized how data is processed and delivered to readers.
What is Data Visualization
Data visualization is the process of presenting raw data using a graphical format. It involves using graphs, charts, and other types of visuals to communicate critical Information in a way your audience can understand. Also, it helps to uncover any existing relationship in your data, giving you a clear picture of what you are dealing with.
In addition, data visualization is a key aspect you need to have when dealing with massive amounts of data. Making sound decisions from huge data sets is difficult since you are likely to leave out some critical points. Visualizations enable you to summarize the process by creating a reliable data foundation you can use in decision-making.
When Visualizing your data, you need to choose a reliable tool to help you navigate the process. Excel is one of the best tools that have been in existence for more than a decade, serving various visualization needs. Do you know that you can create multiple creative data visualizations using Excel? Now you know!
However, it’s good to learn about some of the coolest data visualizations you can create using Microsoft Excel. This article outlines various creative data visualizations that you can create using Excel. Let’s check them out!
1. Spider Chart
A spider chart, also known as a radar chart, is one of the coolest data visualizations you can generate using Excel. What is a spider chart? This graphical methodology uses a two-dimensional chart or more quantitative variables to display multivariate data. The chart represents multiple data variables originating from the same data point.
When evaluating the data outlined in the spider chart, the axes’ relative position and angle are typically uninformative. Besides, a radar chart is only used to visualize quantitative data. It’s mainly applied when visualizing a huge number of parameters of a given product. There are people who prefer using column charts over spider charts.
However, the problem is that when you outline large parameters on a column chart, it will become cluttered, making it difficult to read and understand. A spider chart is the most preferred option when analyzing large data parameters. With Excel, you can easily generate creative data visualizations that fully serve your needs.
2. Column Chart
A column chart is used to analyze categorical data. The chart uses rectangular bars and heights directly proportional to the values presented. When generating the bars, you can make the chart vertical or horizontal, depending on your needs. A column chart is mostly used to visualize quantitative data.
The column chart works better if you want to highlight various values for comparison purposes. In addition, a column chart is used in places that need less emphasis on matters with time and focus. It’s a good chart to use for comparison purposes. Most organizations use column charts to evaluate the volume of shares traded within a single day.
Most people prefer using column charts because they give reliable data output used in decision-making. On most occasions, a column chart is also known as a bar chart since it has bars.
3. Bubble Chart
A bubble chart is one of the coolest data visualizations you can use to analyze variation in your data. In a scatter plot, the data points are represented using bubbles. But how do you define a bubble chart? A bubble chart is a multivariate chart, and a variant of a scatter plot. The chart is mostly applied in quantitative data sets.
Apart from the values mainly represented by the X and Y axis, the size of every bubble within the chart mainly represents the third value. Like a scatter chart, a bubble chart does not use a category axis in data presentation. The chart’s horizontal and vertical axes are referred to as the value axes.
When analyzing the data in a bubble chart, all the focus should be channeled on the distribution of bubbles across the chart. The bubbles represent the data points on the chart. The mode in which they are distributed showcases the nature of your data, enabling you to generate conclusions faster.
4. Pie Chart
A pie chart is one of the unique visualizations you can generate using Excel. The chart is circular in nature and used to showcase statistics in data. It’s divided into different slices to display the numerical proportion of data. The arc length in a pie chart is directly proportional to the quantity it represents. The chart is mainly named after a pie due to its resemblance.
Besides, there are different variations in how the chart can be presented. A pie chart is not suitable if you have multiple data series you intend to represent. This is because when the data series increases, the slices become smaller. As a result, it becomes difficult to read and analyze the data since the chart is likely to become cluttered.
A pie chart is mostly applied to visualize quantitative data to evaluate the proportion of different parameters. Note that the data values outlined in a pie chart are equivalent to 100%. Considering this, arithmetic makes it easier for you to analyze the data and get reliable output.
5. Histogram
What do you use to showcase data distribution? A histogram is one of the creative data visualizations used to display the distribution of numerical data. In addition, a histogram is only used to summarize discrete or continuous data. To make it simple, a histogram is used to offer a visual interpretation of technical data. It displays the number of data points that fall in a given category.
A histogram operates the same way as a vertical bar graph, although a histogram does not have any gaps within the bars. The chart allows for the inspection of data to evaluate the underlying distribution. By analyzing the data with a keen eye for details, you will identify outliers, skewness, and any other crucial aspects within the data.
A histogram is an incredible tool for evaluating quantitative data such as age distribution. The chart gives a detailed approach to evaluating data distribution regardless of its technical elements.
Conclusion
Microsoft Excel is a rich source of charting options you can deploy in your data visualization operations. Provided that you can access the tool, you can create any chart you desire. Excel is a reliable tool that aids in the transformation of raw data into actionable insights that can take part in decision-making.
Using Excel, you can generate creative data visualizations that solve all your . Besides, you don’t need to spend a lot of time in order to create an incredible output. Excel is a friendly tool and easy to use, thus saving much of your time and effort.