Many computer end-users, such as research scientists and business analysts, need to
frequently query a database, yet lack enough programming knowledge to write a correct …

Selecting relevant data subsets from large, unfamiliar datasets can be difficult. We address
this challenge by modeling and visualizing two kinds of auxiliary information:(1) quality–the …

We develop and evaluate an approach for generating Personalized Service Level
Agreements (PSLAs) that separate cloud users from the details of compute resources …

A full-fledged data exploration system must combine different access modalities with a
powerful concept of guiding the user in the exploration process, by being reactive and …

The exploration of large, real-world databases poses major challenges to users due to their
volume and complexity. SQL is the preferred language for data exploration. However, the …

A full-fledged data exploration system must combine different access modalities with a
powerful concept of guiding the user in the exploration process, by being reactive and …

Helping users explore data becomes increasingly more important as databases get larger
and more complex. In this demo, we present PyExplore, a data exploration tool aimed at …

The overhead and burden of managing data in complex discovery processes involving
experimental protocols with numerous data-producing and computational steps has become …

The Database-as-a-Service paradigm has gained a lot of popularity in the past few years [1]–
[5]. There are multiple providers for a generic Database-as-a-Service like SQLAzure [1] …

We consider methods for learning vector representations of SQL queries to support
generalized workload analytics tasks, including workload summarization for index selection …