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| Peter Simpson is our VP Research & Development. He is responsible for all development, pre-sales, support and consulting activities. Peter holds a Master of Science degree in Information Systems Engineering and a Bachelor of Science degree in Physics with Space Science & Technology. |
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| Hugh Heinsohn is Panopticon's VP Marketing. He has over 20 years experience working with software companies and telecoms equipment manufacturers. |
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Statistics by themselves are often hard to understand and difficult to analyze objectively. The right software makes it possible to develop interactive information graphics that do more than dazzle: They help people truly understand and analyze the underlying data in large statistical databases.
Even the most accurate and complete data set is useless if people cannot easily analyze and interpret its contents. The proper selection of data visualizations combined with best practices and use of color, size, layout and organization can make even the most dense material comprehensible. Beyond that, such information visualization tools can reveal hidden truths that may be obscured by the weight of controversial statistics.
As Edward Tufte pointed out in his book, Beautiful Evidence: "Making an evidence presentation is a moral act as well as an intellectual
activity. To maintain standards of quality, relevance, and integrity for evidence,
consumers of presentations should insist that presenters be held intellectually
and ethically responsible for what they show and tell. Thus consuming a presentation is also an intellectual and a moral activity."
Attendees will learn:
- How to create visual analytics dashboards that support fast discovery through clustering, outliers, correlations and contributions.
- How to enhance analytical dashboards using calculations across time, through time and between set time windows.
- How to use the special time series tools available in Panopticon's software to focus on a particular time slice or the performance across a defined time window and how to play back through all the data in a time series.
Please fill out this form to view the webinar.
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