Practical Applications of Visual Analytics


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Dustin Smith, Community Manager, Tableau Software, presents at the 2012 Big Analytics Roadshow.

Organizations now have the ability to store and process massive amounts of data like never before. And there are huge expectations for turning data into a fundamental driver for business transformation and competitive advantage.

Visual analytics is helping everyday employees gain insight into data in order to solve unexpected problems and challenges, it is changing the way people interact with data and the way business intelligence is defined in organizations. In this presentation, we will share real-world examples of how everyday people can and are using visual analytics to solve some of businesses most challenging issues.

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Practical Applications of Visual Analytics

  1. 1. Practical Applications ofVisual Analytics Dustin Smith Tableau Software
  2. 2. We have been using tabularrepresentations of data for 4,000 years
  3. 3. We’re still using tabularrepresentations of data today
  4. 4. Improved representation can transform reflecting on data to experiencing it“The deep fundamental question in statistical analysis is Compared with what?”, Edward Tufte
  5. 5. The Key to Making Sense of Data is Visualization
  6. 6. Exploit the power of thehuman visual system
  7. 7. Leverage the Human Perceptual System 70% 30% Total Sense Receptors
  8. 8. Iterate, explore, andexperiment
  9. 9. How do people reason about data?Through an unpredictable and iterative process. • Discovering structure; • Finding patterns and outliers; • Deriving causal relationships; • etc. Cycle of Visual Analysis
  10. 10. IncrementalAllow people to easilyand incrementallychange the data theyare looking at and howthey are looking at it. Find the perfect view: People can intuitively explore a broad space of visualizations to find the “perfect” views that answer their questions. Build visual literacy at their own pace: Start simple…and then slowly, over time, build up sophisticated views of their data Perform rapid Q&A: Quickly layer new information into a view to answer new questions
  11. 11. ExpressiveNo single view answers every question.
  12. 12. UnifiedAs people engage in Q&A with their data, they need to be able tochange both: • The data they are looking at, and • How they are looking at that data. Query many times and then generate a summary graph. Traditional Reporting Tools versus Iteratively change the data and image to find the perfect view. Visual Analysis Systems Query once and then iterate on the presentation of the data. Traditional Visualization Tools
  13. 13. The Cycle of Visual Analysis Leads to Monitoring,Sharing and Storytelling
  14. 14. Generate Effective Presentations of Data • Provide the flexibility to generate a wide range of images without encouraging poor design; • Generate effective presentations of data by default.What is effective? Supporting Effective Presentation Communicates all of the data Limiting the visual properties to a simple Communicates only the data and proven set Leverages the human perceptual system Great defaults Is understandable Automatic marks Is interpretable Layout Small multiples Support for titling, captioning, & annotation
  15. 15. Big Data“The Library of Congress has18 terabytes of data. We dothat every three days.” David Stone Senior Manager – Analytics Platform eBay“More data beats betteralgorithms” Anand Rajaraman Teaches Web Scale Data Mining at Stanford University1,048,576 Max rows in Excel 2010 Is that Big Data?
  16. 16. Help peoplesee and understand their data
  17. 17. Tableau Software, Inc. Customers Include:• Fastest growing business intelligence company • Apple in the world • Microsoft • Wells Fargo• Stanford Professor Pat Hanrahan and Dr. Chris Stolte • Bank of America invented the visualization technology • Walmart • eBay• Founded in 2003 – currently on Version 7 of the software • Linked In• Headquartered in Seattle, WA • Zynga • Electronic Arts• 400 employees • GM • Dozens of Universities • A number of Intelligence Agencies + 1000’s more