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Event Dates

Thursday, November 18, 2021 3:45pm to 5pm

Virtual Event
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Analysts need the ability to intuitively explore their data before deciding how to clean it, model it, and present it to key decision makers. With the abundance of massive datasets in industry and science, analysts also need exploration systems that can process data quickly and efficiently, otherwise these systems will fail to keep pace with a user’s analytic flow. Addressing these challenges requires a deeper understanding of not only how system behavior influences user performance, but also how user behavior influences system performance.


In this talk, I will first discuss how system performance impacts the way people visually explore large datasets, in particular how system latency encourages user exploration bias. Then I will discuss how we can counteract these effects using behavior-driven optimizations, such as by learning user exploration patterns automatically, and exploiting these patterns to pre-fetch data ahead of users as they explore to reduce system latency. Then I will discuss how I synthesize evaluation methodology from HCI, visualization, and data management into executable benchmarks for testing database management systems under real-time interactive analysis scenarios. Finally, I will discuss my ongoing research to further characterize, optimize, and evaluate interactive data exploration systems to promote more reliable, rigorous, and engaging analyses.

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