In recent years, many query processing techniques have been developed to better support
interactive data exploration (IDE) of large structured datasets. To evaluate and compare …

In this paper, we present a new benchmark to validate the suitability of database systems for
interactive visualization workloads. While there exist proposals for evaluating database …

Interactive Data Exploration (IDE) is a key ingredient of a diverse set of discovery-oriented
applications, including ones from scientific computing and evidence-based medicine. In …

Traditional DBSMs are suited for applications in which the structure, meaning and contents
of the database, as well as the questions to be asked are already well understood. There is …

Interactive exploration of large volumes of data is increasingly common, as data scientists
attempt to extract interesting information from large opaque data sets. This scenario presents …

Data exploration is about efficiently extracting knowledge from data even if we do not know
exactly what we are looking for. In this tutorial, we survey recent developments in the …

Enabling interactive visualization over new datasets at" human speed" is key to
democratizing data science and maximizing human productivity. In this work, we first argue …

Highly interactive query interfaces have become a popular tool for ad-hoc data analysis and
exploration, posing a new kind of workload to the underlying data infrastructure. Compared …

In this paper, we argue that database systems be augmented with an automated data
exploration service that methodically steers users through the data in a meaningful way …

Generating knowledge from data is an increasingly important activity. This process of data
exploration consists of multiple tasks: data ingestion, visualization, statistical analysis, and …