December 12, 2019

218 words 2 mins read

Architectural design for interactive visualization

Architectural design for interactive visualization

Creating visualizations for data science requires an interactive setup that works at scale. Bargava Subramanian and Amit Kapoor explore the key architectural design considerations for such a system and discuss the four key trade-offs in this design space: rendering for data scale, computation for interaction speed, adapting to data complexity, and being responsive to data velocity.
Talk Title Architectural design for interactive visualization
Speakers Bargava Subramanian (Binaize), Amit Kapoor (narrativeVIZ)
Conference Strata Data Conference
Conf Tag Making Data Work
Location London, United Kingdom
Date May 22-24, 2018
URL Talk Page
Slides Talk Slides
Video

Visualization is an integral part of the data science process and includes exploratory data analysis to understand the shape of the data, model visualization to unbox the model algorithm, and dashboard visualization to communicate the insight. This task of visualization is increasingly shifting from a static and narrative setup to an interactive and reactive setup, which presents a new set of challenges for those designing interactive visualization applications. Creating visualizations for data science requires an interactive setup that works at scale. Bargava Subramanian and Amit Kapoor explore the key architectural design considerations for such a system and discuss the four key trade-offs in this design space: rendering for data scale, computation for interaction speed, adapting to data complexity, and being responsive to data velocity.

algorithm complexity dashboard data science visualization
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