際際滷shows by User: SeanKandel / http://www.slideshare.net/images/logo.gif 際際滷shows by User: SeanKandel / Tue, 29 Oct 2013 15:47:17 GMT 際際滷Share feed for 際際滷shows by User: SeanKandel 2013.10.24 big datavisualization /slideshow/20131024-big-datavisualization/27707535 2013-131029154717-phpapp01
When the number of data elements gets large - thousands to billions or more data points - standard visual representations and interaction techniques break down. In this talk, we will survey methods for scaling interactive visualizations to data sets too large to process or explore using traditional means. I will compare data reduction techniques such as sampling, aggregation and model fitting, as well as interesting hybrid approaches, and discuss their trade-offs. I will also describe methods to enable real-time interactive exploration within standards-compliant web browsers. Attendees will learn effective visualization techniques and interaction methods that are applicable to billion+ element databases.]]>
When the number of data elements gets large - thousands to billions or more data points - standard visual representations and interaction techniques break down. In this talk, we will survey methods for scaling interactive visualizations to data sets too large to process or explore using traditional means. I will compare data reduction techniques such as sampling, aggregation and model fitting, as well as interesting hybrid approaches, and discuss their trade-offs. I will also describe methods to enable real-time interactive exploration within standards-compliant web browsers. Attendees will learn effective visualization techniques and interaction methods that are applicable to billion+ element databases.]]> Tue, 29 Oct 2013 15:47:17 GMT /slideshow/20131024-big-datavisualization/27707535 SeanKandel@slideshare.net(SeanKandel) 2013.10.24 big datavisualization SeanKandel When the number of data elements gets large - thousands to billions or more data points - standard visual representations and interaction techniques break down. In this talk, we will survey methods for scaling interactive visualizations to data sets too large to process or explore using traditional means. I will compare data reduction techniques such as sampling, aggregation and model fitting, as well as interesting hybrid approaches, and discuss their trade-offs. I will also describe methods to enable real-time interactive exploration within standards-compliant web browsers. Attendees will learn effective visualization techniques and interaction methods that are applicable to billion+ element databases. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2013-131029154717-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> When the number of data elements gets large - thousands to billions or more data points - standard visual representations and interaction techniques break down. In this talk, we will survey methods for scaling interactive visualizations to data sets too large to process or explore using traditional means. I will compare data reduction techniques such as sampling, aggregation and model fitting, as well as interesting hybrid approaches, and discuss their trade-offs. I will also describe methods to enable real-time interactive exploration within standards-compliant web browsers. Attendees will learn effective visualization techniques and interaction methods that are applicable to billion+ element databases.
2013.10.24 big datavisualization from Sean Kandel
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