Davos: a system for interactive data-driven decision making

Abstract

<jats:p>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.</jats:p> <jats:p> 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 <jats:italic>Davos</jats:italic> , Einblick's novel backend. <jats:italic>Davos</jats:italic> combines aspects of progressive computation, approximate query processing and sampling, with a specific focus on supporting user-defined operations. Moreover, <jats:italic>Davos</jats:italic> optimizes multi-tenant scenarios to promote collaboration. Both empirical evaluation and user study verify that <jats:italic>Davos</jats:italic> can greatly empower data analytics for new needs. </jats:p>