Visual Data Center FAQs
Frequently Asked Questions About Data Visualization
Explore these commonly asked questions and this general data visualization information to help you get the most use out of the Visual Data Center. If you cannot find something you are looking for, you can reach out out to us and let us know through our feedback form. Once you have reviewed some of the frequently asked questions, go back to the Visual Data Center to explore more content.
Most people are visual learners. With so much data available today, it’s important to translate that data into well-designed graphics that can help users quickly focus on what important and lets you tell a story with the data.
Data visualization provides a visual way to present complicated data in a an easily way that quickly can be digested by the viewer.
There are a variety of data visualization types that can be explored for different situations. Some of the more common options include column charts, bar graphs, line graphs, pie charts, scatter plots, bubble charts, and spider charts.
These are two different Data Science fields. Data Mining is a process to analyze large sets using machine learning, statistics, and algorithms to clustering, classifying, and summarizing the data. The extracted information can then be used to tell a story by visualizing the data for easy consumption.
Data visualization helps when you want to make sense of a large amount of data. It can help you tell a story by curating data into a form that is easier to understand.
Once data is interpreted and analyzed from a chart or graph, this will allow more understanding of the information that’s visually provided. The brain tends to process visuals a lot faster than text. Thus, the use of data visualization for your business will help improve how your business looks at information.
The human mind is much more comfortable processing visuals better than sifting through large amounts of data. If the data is presented well, decision-makers can quickly process the information and take action based on the new insights.