Simply put, data visualization is the presentation of data in a visual manner that could be either in a pictorial or graphical format. This enables data analysts and scientists to depict even the most mind-boggling concepts in an interactive way (charts and graphs), thereby changing the way you see and process data.
What Is Data Visualization?
It is the method of consolidating data into a single self-explanatory graphic. Infographics are the traditional examples of data visualization. Historically, the method of representing data using maps and graphs have been traced back to the 17th century.
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However, the advent of computers has made it possible to process and represent large amounts of data at faster rates. This is the reason why data visualization is considered to be a disruptive force that’s capable of transforming the way data is handled.
5 Important Reasons Why Data Visualization Matters
Below are the important reasons why data visualization matters.
1. Helps Represent Data In A Crisp Manner
As human beings grasp most information through the visual medium, data visualization techniques can be used in business intelligence reports and presentations to convey complex information.
Even high volumes of data spread across various data sets can be represented with heat maps, fever charts, and other graphs.
2. Improves Access To Necessary Business Insights
Industry experts are of the view that organizations that use visual data in their business reports were 28-48 percent more likely to find timely information without the help of any support staff most of the time.
3. Provides Better Understanding Of Business Trends
In large corporations, the volume of data would be massive and therefore calls for the need for simple yet effective data visualization techniques. These help decision makers to gauge the right conditions that maximize revenue, discover more opportunities and even spot pitfalls in their business plan even if it’s spread over multiple data sets.
4. Fosters A Direct Interaction with Data
Data Visualization aids companies to manipulate data in a direct manner. This brings practical insights to the surface which can be acted upon. For business executives, a visual representation of datasets prompts good decision-making and a revision of business initiatives if needed.
5. Employs Predictive Analysis
Predictive analytics is an important tool for foreseeing growth of businesses of the future. Real-time data-visualization combines predictive analysis to help sales executives to view up-to-date figures, understand what works and doesn’t, as well as track consumer behavior. This can be helpful in devising new strategies for businesses to perform well.
Common Types Of Data Visualization Techniques
Basically, there are 5 common types of data visualization: 2D area, temporal, multidimensional, hierarchical and network categories.
- Under 2D Area types of data visualization, data that’s geospatial ie, a relative position of things on the earth’s surface can be represented. Cartogram, chloropeth and dot distribution map are the examples of 2D area type
- Temporal visualizations are those that have a start and finish time with values that may overlap each other. The examples include connected scatter plot, polar area diagram, time series and many more.
- Multidimensional visualizations depict data in the form of pie charts, histograms, and scatter plots.
- Last but not the least, hierarchical data sets include dendrogram and ring chart.
To sum it all up, data visualization can help you create more appealing and informative business reports. It can serve as a guide in embracing new business goals and rejecting obsolete ones.
If you enjoyed reading this article you would be keen to learn more about predictive business analytics too, which is covered in this blog post.