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 …

Machine learning has become an essential tool for gleaning knowledge from data and
tackling a diverse set of computationally hard tasks. However, the accuracy of a machine …

In the last two decades, interactive visualization and analysis have become a central tool in
data-driven decision making. Concurrently to the contributions in data visualization …

Raw data are often messy: they follow different encodings, records are not well structured,
values do not adhere to patterns, etc. Such data are in general not fit to be ingested by …

As machine learning (ML) systems become democratized, it becomes increasingly important
to help users easily debug their models. However, current data tools are still primitive when …

Exploratory Data Analysis (EDA) is an essential yet highly demanding task. To get a head
start before exploring a new dataset, data scientists often prefer to view existing EDA …

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 …

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 …

In today's databases, previous query answers rarely benefit answering future queries. For
the first time, to the best of our knowledge, we change this paradigm in an approximate …

As machine learning systems become democratized, it becomes increasingly important to
help users easily debug their models. However, current data tools are still primitive when it …