With the continuous and vast increase in the amount of data in our digital world, it has been
acknowledged that the number of knowledgeable data scientists can not scale to address …

Exploratory data science largely happens in computational notebooks with dataframe APIs,
such as pandas, that support flexible means to transform, clean, and analyze data. Yet …

Automatic Exploratory Data Analysis (EDA) focuses on automatically discovering pieces of
knowledge in the form of interesting data patterns. However, the conveyed knowledge by …

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 …

As datasets continue to grow in size and complexity, exploring multi-dimensional datasets
remain challenging for analysts. A common operation during this exploration is drill-down …

We present smart drill-down, an operator for interactively exploring a relational table to
discover and summarize “interesting” groups of tuples. Each group of tuples is described by …

Exploratory data analysis (EDA) has emerged as a critical tool for users to gain deep
insights into data and unearth hidden patterns. The integration of recommendation …

Visualization recommendation (VisRec) systems provide users with suggestions for
potentially interesting and useful next steps during exploratory data analysis. These …

Multiple lines of research have developed Natural Language (NL) interfaces for formulating
database queries. We build upon this work, but focus on presenting a highly detailed form of …

The big data revolution is an exciting opportunity for universities, which typically have rich
and complex digital data on their learners. It has motivated many universities around the …