Tips for Data Visualization using MS Excel

Presenting an Excel sheet in a meeting turns out to be a boring affair at times, isn’t it? What if you can present your old excel sheet in a communicative way?  Visualizing data is the first step in making sense out of data. And you would be surprised to know the various visualization tools your own Excel has under the hood! Yes – the excel has been known for its data analysis functions, can demonstrate your boring data in an expressive manner. These data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.


What is Data Visualization?

Data visualization is the graphical representation of information and data with the help of visual elements like charts, graphs, and maps. The type of Excel chart you select for your analysis and reporting depends upon the type of data you want to analyze and what you want to do with that data.

Why is Data visualization important?

Every data has to be dragged, dropped, organized if you want to optimize it to its capacity. Data visualization converts your data into a presentable and more understandable format. We discovered some more interesting resources on the benefits of Data visualization for you on

Why Data Visualization using Microsoft Excel?

  • Do a quick data visualization without the need of having a separate license-based tool.
  • Easy to share the visualization with others as the receivers also don’t need a separate tool.
  • Easy to use since there is no need to learn a separate tool.
  • You can learn Advanced MS Excel online.

Check out some tips to avoid common data visualization mistakes thus helping in getting the desired output and escorting you towards productive decision-making.

Common Visualization Mistakes

Types of Chart and Graphs in Microsoft Excel

The following are the most popular Excel charts and graphs:

  • Clustered Column Chart
  • Combination Chart
  • Stacked Column Chart
  • Bar Chart
  • Line Chart
  • Pie Chart

Clustered Column Chart

A Clustered Column Chart is used to compare two to four data series. Avoid creating a column chart if you have more than four data series because it will be very difficult to read and understand. You can also use a clustered column chart when the data series has the same unit of measurement and the data series are of comparable sizes. It is also used when you want to show the minimum and maximum values of each data series.

clustered chart

Combination Chart

Combination Charts are used when you want to compare two or more data series that have different units of measurement. It can also be used when you want to compare two or more data series that are not of comparable sizes.


combincation chart


 Stacked Column Chart

You can use a Stacked Column Chart when you want to compare the data series along with their composition and the overall size of each data series is important.

stacked column chart

Bar Chart

 A bar chart represents data with rectangular bars with heights or lengths proportionate to the values that they represent. They are used whenever the axis labels are too long to fit in a column chart.

Bar chart

Line Chart

Line Charts are used when you want to focus on the data trends such as uptrend, downtrend, short term trend, long term trend, etc. It can also be used when you have too many data points and the order of categories is important.

Line chart

Pie Chart

Pie Charts are used when you want to show a 100% composition of your data. It can be used when you have one data series and less than five categories to plot.

pie chart

MS Excel has various effective and user-friendly visualization tools like the various Excel charts we’ve discussed above. These tools will help you in finding the correlation between various data elements and in deriving useful patterns with the data. Confused with how to learn Advanced Excel online?

Irizpro’s Advanced MS Excel course helps you learn all the concepts of MS Excel and helps you explore all the concepts of Excel, so that next time when you get a data set to analyze, you will have adequate knowledge to visualize your data.



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