research-article

Davos: a system for interactive data-driven decision making

Authors:

Emanuel Zgraggen,

Benedetto Buratti,

Philipp Eichmann,

Navid Karimeddiny,

Wesley Runnels, and

Tim KraskaAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 14, Issue 12

Pages 2893 - 2905

https://doi.org/10.14778/3476311.3476370

Published: 01 July 2021 Publication History

Abstract

Recently, a new horizon in data analytics, prescriptive analytics, is becoming more and more important to make data-driven decisions. As opposed to the progress of democratizing data acquisition and access, making data-driven decisions remains a significant challenge for people without technical expertise. In this regard, existing tools for data analytics which were designed decades ago still present a high bar for domain experts, and removing this bar requires a fundamental rethinking of both interface and backend.

At Einblick, an MIT/Brown spin-off based on the Northstar project, we have been building the next generation analytics tool in the last few years. To overcome the shortcomings of existing processing engines, we propose Davos, Einblick's novel backend. Davos combines aspects of progressive computation, approximate query processing and sampling, with a specific focus on supporting user-defined operations. Moreover, Davos optimizes multi-tenant scenarios to promote collaboration. Both empirical evaluation and user study verify that Davos can greatly empower data analytics for new needs.

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Cited By

Duan SLyu FZhu XDing YWang HZhang DLiu XZhang YRen J(2023)VeLP: Vehicle Loading Plan Learning from Human Behavior in Nationwide Logistics SystemProceedings of the VLDB Endowment10.14778/3626292.362630517:2(241-249)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.14778/3626292.3626305
Wang ZLi C(2023)Building a Collaborative Data Analytics System: Opportunities and ChallengesProceedings of the VLDB Endowment10.14778/3611540.361158016:12(3898-3901)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.14778/3611540.3611580
Omidvar-Tehrani BPersonnaz AAmer-Yahia SAl Hasan MXiong L(2022)Guided Text-based Item ExplorationProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557141(3410-3420)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3511808.3557141

Index Terms

Davos: a system for interactive data-driven decision making
1. Human-centered computing
2. Information systems
  1. Data management systems
    1. Database management system engines
  2. Information systems applications

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 14, Issue 12

July 2021

587 pages

ISSN:2150-8097

Editors:
Xin Luna Dong
Amazon
,
Felix Naumann
HPI, University of Potsdam

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VLDB Endowment

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Published: 01 July 2021

Published in PVLDB Volume 14, Issue 12

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Cited By

Duan SLyu FZhu XDing YWang HZhang DLiu XZhang YRen J(2023)VeLP: Vehicle Loading Plan Learning from Human Behavior in Nationwide Logistics SystemProceedings of the VLDB Endowment10.14778/3626292.362630517:2(241-249)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.14778/3626292.3626305
Wang ZLi C(2023)Building a Collaborative Data Analytics System: Opportunities and ChallengesProceedings of the VLDB Endowment10.14778/3611540.361158016:12(3898-3901)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.14778/3611540.3611580
Omidvar-Tehrani BPersonnaz AAmer-Yahia SAl Hasan MXiong L(2022)Guided Text-based Item ExplorationProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557141(3410-3420)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3511808.3557141

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