When dealing with data, you need to have a proper way of displaying it to your readers. Presenting large volumes of data is difficult, especially if you are a beginner. However, presenting data does not mean anything if you do not understand the art of data visualization. Data can be a mystery, especially when you want to uncover the underlying information.

To uncover insights into your data, you need to learn and master the art of data visualization. Visualization can enable you to detect all the essential insights if you are looking at the data for the first time. This strategy is used to display data reports to readers who are not familiar with analyzing raw data.

Even though data visualization is a key component in data analysis, it involves a variety of components that you need to familiarize yourself with. Visualization involves things to do with charts and graphs to display data to your respective readers. The most difficult part of the entire process is choosing the right chart type to use.

The type of chart you choose can easily impact the accuracy of your data output. Data visualization Excel offers you a multitude of charting options that you can use to analyze your data and draw conclusions. This article outlines some of the best Excel charts and graphs that you can use in data visualization. Check them out!

  • Line chart
  • Radar Chart
  • Box Plot
  • Bar Chart
  • Scatter Plot
  • Dot Plot
  • Bubble Chart

Line Chart

A line chart is one of the popular Excel charts used for data visualization. The chart is mostly used when you want to display changes in the value across continuous data measurement. The movement of the line, either up or down, aids in bringing out the positive and negative changes in your data.

In addition, the line chart can also help you uncover the overall trends that will help your readers make predictions or projections that will impact the business's future success. Remember that making predictions is not easy, especially if you are working on plain ground. Data can help you make the right moves that will impact your organization's progress.

When you create multiple line charts, you will realize that you are forming other types of related charts. This means you stand a better chance to uncover more insights that cover a significant part of decision-making.

Box Plot

As the name suggests, a box plot uses boxes to plot data points. The boxes and whiskers are mainly used to summarize the distribution of values within measured data groups. The position where the whisker and the box ends represents the region where the majority of the data lies. You can easily use this chart when you want to showcase the distribution of your data. 

When you have multiple groups of data, you can use the box plot to compare every data group with one another. The chart is mostly used when dealing with large sets of data. The box plot could accommodate large volumes of data, making it a critical tool for organizations that generate significant amounts of data.

You only need to consider other charting options when you have minimal data.  What makes the box plot a reliable option for data visualization is the fact that the chart is pretty easy to read and understand. Besides, it does not entail technical aspects that need technical skills. You can easily draw conclusions from your data in a matter of minutes.

Bar Chart

The bar chart is among the oldest and more reliable data visualization tools courtesy of Microsoft Excel. When using a bar chart, the values are indicated by the length of the bars. The height of every bar corresponds with a particular data group under measurement. The bar chart design that you choose mainly depends on your requirements.

You can choose to use a vertical or horizontal bar chart depending on the nature of the data you are processing. However, vertical bar charts are mostly referred to as column bar charts. A horizontal bar chart is the most applicable option when you want to display a lot of bars. Also, it's used when you have massive amounts of data.

Also, when dealing with data requiring detailed labeling, you must consider using a bar chart. The chart is pretty easy to digest since every data aspect is outlined clearly. You can create a bar chart in a matter of minutes using Excel. The process does not require any additional application to get the job done.

Scatter Plot

A scatter plot is mostly used when you want to display values on two numeric variables using points. The data variables are outlined on two axes, with every variable on each axis. The chart is mostly used when you want to showcase the relationship between different data groups. When you want to showcase the relative in your data points, use a scatter plot to make this happen.

You can use the chart to showcase whether the correlation is either strong or weak. Also, the chart outlines all the instances of positivity and negativity in your data. The chart displays all the insights you need to know, helping your readers drive to the right point at home. Readers don't need to struggle in order to detect the insights hidden in your data values.

A scatter plot is an awesome choice when you want to uncover outliers in your data. This helps you to fill all the possible gaps in your data which is essential in helping you make the right decisions. Detecting the errors in your data sets makes it easier for you to extract the vital insights you need when making impactful decisions within your organization.

Dot Plot

A dot plot operates the same way as a bar chart. The only difference is that a dit plot works by encoding values depending on a point position instead of the length of the bar. The chart works better when you want to compare data points across different categories. However, the zero baselines are not informative or useful. A dot plot purely outlines data using point variations across the entire chart.

Besides, you can choose to evaluate a dot plot the same way you do on a line chart. The only thing that makes the difference is that the line is removed. When this is done, it becomes easier for the chart to be used by unordered data categories. This means you don't necessarily need to use a dot plot on continuous data.

The nature of the chart gives you the freedom to evaluate different types of data using the chart to uncover insights. The goal is to ensure that you have uncovered all the vital insights existing in your data to enable you to make accurate decisions moving forward.

Bubble Chart

The bubble chart offers another way of displaying relationships between three different variables. However, all this is done through the modification of a scatter plot. The chart is used to showcase the data relationship between three different data variables. When the third data variable is categorical, the data points can use different sizes, shapes, or colors to showcase the membership of a particular team.

When the data points are ordered in the same way, the points can be connected using a line segment to display the sequence of the values. If the third variable is numeric in nature, this is exactly where the bubble charts come in. Note that the bubble chart is mainly built on the foundation of a scatter plot. The size of the third variable is mainly used to determine the size of every point.

Conclusion

Excel charts play a significant role in data visualization. Displaying the insights hidden in data needs you to have a unique approach to uncovering and displaying them to your target audience. The only best way to make this happen is by using Excel charts to display your data in a manner that readers can easily understand.

Besides, readers are always attracted to data that is displayed clearly and concisely. Excel charts offer you a unique way of presenting your data without requiring technical experts' support. You don't need any technical expertise to display data using Excel charts. The charts are pretty easy to outline data and simple to extract insights.