Exploratory Data Analysis (EDA) is an important initial step for any knowledge discovery
process, in which data scientists interactively explore unfamiliar datasets by issuing a …

Data preparation is widely recognized as the most time-consuming process in modern
business intelligence (BI) and machine learning (ML) projects. Automating complex data …

A critical challenge in constructing a natural language interface to database (NLIDB) is
bridging the semantic gap between a natural language query (NLQ) and the underlying …

In this paper, we propose a new approach, called Query from Examples (QFE), to help non-
expert database users construct SQL queries. Our approach, which is designed for users …

The purpose of data warehouses is to enable business analysts to make better decisions.
Over the years the technology has matured and data warehouses have become extremely …

Modern Interactive Data Analysis (IDA) platforms, such as Kibana, Splunk, and Tableau, are
gradually replacing traditional OLAP/SQL tools, as they allow for easy-to-use data …

After decades of effort working on database performance, the quality and the usability of
database systems have received more attention in recent years. In particular, the feature of …

The goal of text simplification (TS) is to transform difficult text into a version that is easier to
understand and more broadly accessible to a wide variety of readers. In some domains …

We analyze the workload from a multi-year deployment of a database-as-a-service platform
targeting scientists and data scientists with minimal database experience. Our hypothesis …

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 …