SeeDB: automatically generating query visualizations

Data analysts operating on large volumes of data often rely on visualizations to interpret the results of queries. However, finding the right visualization for a query is a laborious and time-consuming task. We demonstrate SeeDB, a system that partially automates this task: given a query, SeeDB expl...

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Bibliographic Details
Main Authors: Vartak, Manasi (Contributor), Parameswaran, Aditya (Contributor), Polyzotis, Neoklis (Author), Madden, Samuel R. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery (ACM), 2016-01-20T18:41:32Z.
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