This paper provides a survey of the state-of-the-art and future directions of one of the most
important emerging technologies within business analytics (BA), namely prescriptive …

The LogicBlox system aims to reduce the complexity of software development for modern
applications which enhance and automate decision-making and enable their users to evolve …

Data provenance has evolved from a niche topic to a mainstream area of research in
databases and other research communities. This article gives a comprehensive introduction …

In large-scale data management systems, failure is practically a certainty. Fault-tolerant
protocols and components are notoriously difficult to implement and debug. Worse still …

Data is a central component of machine learning and causal inference tasks. The availability
of large amounts of data from sources such as open data repositories, data lakes and data …

We study the problem of introducing errors into clean databases for the purpose of
benchmarking data-cleaning algorithms. Our goal is to provide users with the highest …

When debugging a distributed system, it is sometimes necessary to explain the absence of
an event-for instance, why a certain route is not available, or why a certain packet did not …

Causal inference is at the heart of empirical research in natural and social sciences and is
critical for scientific discovery and informed decision making. The gold standard in causal …

As the need for machine learning (ML) increases rapidly across all industry sectors, there is
a significant interest among commercial database providers to support" Query 2.0", which …

This work considers why-not questions in the context of top-k queries and score-based
ranking functions. Following the popular linear scalarization approach for multi-objective …