DBScholar

Back to papers

Davos: A System for Interactive Data-Driven Decision Making

Summary: Davos is Einblick’s backend for interactive prescriptive analytics, combining progressive computation, approximate query processing, and sampling while supporting user-defined operations. Its multi-tenant optimizations enable collaborative, accessible data-driven decision making. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12686
Venue
VLDB
Year
2021
Pagerank
7.3008782e-05
Overall Rank
3,570 | 75.51%
DOI
10.14778/3476311.3476370

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shang_vldb21,
        title = {{Davos: A System for Interactive Data-Driven Decision Making}},
        author = {Shang, Zeyuan and Zgraggen, Emanuel and Buratti, Benedetto and Eichmann, Philipp and Karimeddiny, Navid and Meyer, Charlie and Runnels, Wesley and Kraska, Tim},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {12},
        pages = {2893--2905},
        doi = {10.14778/3476311.3476370},
        url = {https://doi.org/10.14778/3476311.3476370},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers