Provide a highly effective way to communicate any insights that surfaces to others.Reveal patterns - identify correlations and unexpected connections that could not be found with specific questions and.Capture trends - the use of appropriate techniques can make it easy to recognize this information.Enable decision-makers to understand what the amount of data means very quickly.The problem for companies is that data is only useful if valuable insights can be extracted from large amounts of raw data and read by who can analyze them - data literacy in near real-time.īig Data visualization techniques are important because they:
The amount of data is growing every year thanks to the Internet and innovations such as operational systems, sensors, and the Internet of Things. Why is it important to have a good method of visualization? Thus, it goes far beyond typical graphs, bubble plots, histograms, pie, and donut charts to more complex representations like heat maps and box and whisker plots, enabling decision-makers to explore data sets to identify correlations or unexpected patterns. Visualization resources rely on powerful tools to interpret raw data and process it to generate visual representations that allow humans to take in and understand enormous amounts of data in a few minutes.īig Data visualization describes data of almost any type - numbers, trigonometric function, linear algebra, geometric, basic, or statistical algorithms - in a visual basis format - coding, reports analytics, graphical interaction - that makes it easy to understand and interpret. Today’s companies collect and store vast amounts of information that would take years for a human to read and understand.
What is Big Data visualization?Ī defining characteristic of Big Data is volume.
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