Browsing by Author "Ebert, D."

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    Towards interactive data exploration
    (Springer, 2019) Binnig, C.; Basık, Fuat; Buratti, B.; Çetintemel, U.; Chung, Y.; Crotty, A.; Cousins, C.; Ebert, D.; Eichmann, P.; Galakatos, A.; Hattasch, B.; Ilkhechi, A.; Kraska, T.; Shang, Z.; Tromba, I.; Usta, Arif; Utama, P.; Upfal, E.; Wang, L.; Weir, N.; Zeleznik, R.; Zgraggen, E.; Castellanos, M.; Chrysanthis, P.; Pelechrinis, K.
    Enabling interactive visualization over new datasets at “human speed” is key to democratizing data science and maximizing human productivity. In this work, we first argue why existing analytics infrastructures do not support interactive data exploration and outline the challenges and opportunities of building a system specifically designed for interactive data exploration. Furthermore, we present the results of building IDEA, a new type of system for interactive data exploration that is specifically designed to integrate seamlessly with existing data management landscapes and allow users to explore their data instantly without expensive data preparation costs. Finally, we discuss other important considerations for interactive data exploration systems including benchmarking, natural language interfaces, as well as interactive machine learning.