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Need for Learning Data Visualization
Data visualization in simple terms is a computerized version of visual communication.
By
Apac CIOOutlook | Monday, January 08, 2018
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Data visualization in simple terms is a computerized version of visual communication. It is a way of ensuring a person who does not have a very sound knowledge of technology understands what data is, and more so, understanding terms such as Big Data. Pictorial representation of data with an objective to provide a better understanding is what data visualization is about. Non-technical people can grasp and analyze links and patterns better with a graphical option. Now visualization tools, historical forms of data visualization and graphs that were once catered by MS Excel and PowerPoint have witnessed a major jump.
There are numerous data visualization tools that businesses can choose from. Having data visualization tools is an essential part of business intelligence, and it's important to be inculcated in it. An ever-increasing number of firms are digging into it and are thriving. Going past the customary and standard types of visualizing the data, these visualization tools have moved towards becoming most widely used language for business intelligence.
Graphics have another critical part in visualizing data both statistically and informatively. Accessibility of data is relative to how simple it is to comprehend. Graphics that are utilized for data visualization ensures there is space for modulation and comparison. Living in an age where technology is flourishing day by day, and technology such as AI, IoT, and Big Data becoming the core, data visualization becomes a reason for its further growth.
Tableau, a data visualization technique doesn't require the skills of a programmer yet doesn't completely do away with it. And being the most well known and popular platform for data visualization, Tableau has become a significant part of the business analysis and process requirements.
Be it for description, analysis or prediction, data visualization is pivotal in understanding data.
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