Causal inference is fundamental to empirical scientific discoveries in natural and social
sciences; however, in the process of conducting causal inference, data management …

Causal analysis is essential for gaining insights into complex real-world processes and
making informed decisions. However, performing accurate causal analysis on observational …

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 …

Query performance (eg, execution time) prediction is a critical component of modern
DBMSes. As a pioneering cloud data warehouse, Amazon Redshift relies on an accurate …

What-if and How-to queries are fundamental data analysis questions that provide insights
about the effects of a hypothetical update without actually making changes to the database …

We live in a world dominated by data, where users from different fields routinely collect,
study, and make decisions supported by data. To aid these users, the current trend in data …

SQL queries with group-by and average are frequently used and plotted as bar charts in
several data analysis applications. Understanding the reasons behind the results in such an …

While counterfactuals have been extensively studied as an intuitive explanation of model
predictions, they still have limited adoption in practice due to two obstacles:(a) They rely on …

The resilience of a query q (RES (q)) measures the minimum number of source tuples
responsible for a specific query answer. If q is an IQ query, whose at most one attribute from …

SQL queries with group-by and average are frequently used and plotted as bar charts in
several data analysis applications. Understanding the reasons behind the results in such an …