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It covers chart selection fundamentals (line, bar, scatter, bubble, and pie), then extends to big-data considerations such as volume, semistructured and unstructured variety, visualization velocity, and filtering. 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The information originally appeared in papers presented at SAS Global Forum 2012 and SAS Global Forum 2011.  \nData Visualization Techniques: From Basics to Big Data with SAS® Visual Analytics   \nIntroduction  \nA picture is worth a thousand words – especially when you are trying to understand and gain insights from data  . It is especially relevant when you are trying to find relationships among thousands or even millions of variables and determine their relative importance  .  \nOrganizations of all kinds generate huge amounts of data each minute, hour and day .  \nEveryone – including executives, departmental decision makers, call center workers, and employees on production lines – hopes to learn things from collected data that can help them make better decisions, take smarter actions and operate more efficiently .  \nIf your data has billions of rows, one of the best ways to discern important relationships is through advanced analysis and high-performance data visualization  . If sophisticated analyses can be performed quickly, even immediately, and results presented in ways that showcase patterns and allow querying and exploration, people across all levels in your organization can make faster, more effective decisions  .  \nTo create meaningful visuals of your data, there are some tips and techniques you should consider . Data size and column composition play an important role when selecting graphs to represent your data  . This paper discusses some of the basic issues concerning data visualization and provides suggestions for addressing those issues  .  \nIn addition, big data brings a unique set of challenges for creating visualizations  . This paper covers some of those challenges and potential solutions as well  . If you are working with large data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming  . You may need a new way to look at the data that collapses and condenses the results in an intuitive fashion but still displays graphsand charts that decision makers are accustomed to seeing  . You may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time  .  \nSAS® Visual Analytics is a new business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data  . It creates the best possible visual based on the data that is selected  . SAS Visual Analytics uses high-performance analytic ","cbCaie7LXcCNyWrd","https://ap.wps.com/l/cbCaie7LXcCNyWrd","pdf",943079,21,"English","# Introduction\n# Generating the Best Visualizations for Your Data\n## The Basics: Charting 101\n## Visualizing Big Data\n# Conclusion","[{\"question\":\"How does the paper recommend choosing the right chart type for data?\",\"answer\":\"It recommends understanding the data’s size and cardinality, clarifying the goal and message, knowing the audience’s visual processing, and selecting the simplest visual that conveys the intended information effectively.\"},{\"question\":\"Which basic chart types are discussed in the guide?\",\"answer\":\"The paper covers line graphs, bar charts, scatter plots, bubble plots, and pie charts, explaining how each helps communicate relationships or patterns for different data needs.\"},{\"question\":\"What challenges does the paper highlight when visualizing big data?\",\"answer\":\"It emphasizes handling large data volumes, accounting for different data varieties (semistructured and unstructured), maintaining visualization velocity, and using filtering so exploration and results are not overwhelming.\"}]","Data Visualization Techniques - From Basics to Big Data with SAS® Visual Analytics - White Paper | PDF",53]