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Wesley Runnels

dblp:300/4579 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 87% Database system architecture and tuning · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization
approximate query processing
0.512021
Davos: A System for Interactive Data-Driven Decision Making · Proc. VLDB Endow. 2021
Query processing and optimization › approximate query processing
sampling-based approximate query processing
0.512021
Davos: A System for Interactive Data-Driven Decision Making · Proc. VLDB Endow. 2021

Methods — techniques the papers use, named apart from their topics

sampling · 0.5progressive computation · 0.5
YearPublicationVenuePosition
2021 Davos: A System for Interactive Data-Driven Decision Making
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.
Zeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Philipp Eichmann, Navid Karimeddiny, Charlie Meyer, Wesley Runnels, Tim Kraska
Proc. VLDB Endow.7