| Summary: | <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>
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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.
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