The ubiquity of data lakes has created fascinating new challenges for data management
research. In this tutorial, we review the state-of-the-art in data management for data lakes …

We discuss scalable data integration challenges in the enterprise inspired by our
experience at Tamr1. We use multiple real customer examples to highlight the technical …

Data collection is a major bottleneck in machine learning and an active research topic in
multiple communities. There are largely two reasons data collection has recently become a …

Entity matching (EM) identifies data instances that refer to the same real-world entity, such
as (David Smith, UWMadison) and (DM Smith, UWM). This problem has been a long …

Data visualization is invaluable for explaining the significance of data to people who are
visually oriented. The central task of automatic data visualization is, given a dataset, to …

Inferring meta information about tables, such as column headers or relationships between
columns, is an active research topic in data management as we find many tables are …

We present a new solution for finding joinable tables in massive data lakes: given a table
and one join column, find tables that can be joined with the given table on the largest …

Data only generates value for a few organizations with expertise and resources to make
data shareable, discoverable, and easy to integrate. Sharing data that is easy to discover …

Many modern data science applications build on data lakes, schema-agnostic repositories
of data files and data products that offer limited organization and management capabilities …

Detecting erroneous values is a key step in data cleaning. Error detection algorithms usually
require a user to provide input configurations in the form of rules or statistical parameters …