Why is Data Visualization Important?
Data visualization is the process of presenting quantitative or qualitative data in a visual format. When you use visualization, you make data more accessible for anyone, not just those who were involved in the analysis itself.
Visualization is a powerful tool because it can convey a message without requiring much explanation or background. The chart to the right depicts statistics on world records in running. By glancing at the chart, you can see that the men’s record is higher than the woman’s record for every race. You can also see that the longer the distance, the slower the average pace, which makes sense. The only exception is with the men’s 100m and 200m, which are run at the same pace. All of these insights can be gained from one chart.
In the business context, visualization can drive decisions by portraying data to decision-makers in a digestible way.This means that decisions are supported with data, and not just intuition, which is beneficial for any organization. The maps below depict the popularity of TV shows in different regions across the U.S. What story does the data tell, and how might this information influence organizations? If you were promoting a product on TV in Mississippi, you would want to book an advertisement during Empire, and definitely not during Modern Family. If you were researching Oregon’s demographics, you might be interested in why Duck Dynasty has a huge fan base in a small portion of Southern Oregon.
How Do I Get Started with Data Visualization?
Data visualization does not need to be complex to be effective – in fact, if you have ever created a bar chart or scatter plot in Microsoft Excel, you have already started. In addition to basic graphs and charts, Excel also has Pivot Tables, where you can create more advanced visualizations on aggregate data.
When it comes to more sophisticated tools, Tableau is extremely popular and user-friendly (although it is not free). Tableau pulls data from common sources like Excel and SQL, and allows you to create beautiful, user-friendly visualizations and dashboards. Another option is R, a statistical programming language where, like Excel, you can perform analysis and create visualizations within one platform. R is free and open-sourced, and has a huge community of users that support each other with packages and helpful tools.
Regardless of the tools you are using, try to become more cognizant about visualization and presentation in your work. Next time you present data, think about who your audience is, what data they care about, and the questions they might have. Interested in learning more about data visualization and analytics in depth? Check out the data analytics programs at Level, which cover the full analytical process.