Data-driven algorithms are only as good as the data they work with, while datasets,
especially social data, often fail to represent minorities adequately. Representation Bias in …

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 …

Data profiling refers to the activity of collecting data about data,{ie}, metadata. Most IT
professionals and researchers who work with data have engaged in data profiling, at least …

Effective query optimization is a core feature of any database management system. While
most query optimization techniques make use of simple metadata, such as cardinalities and …

Functional dependencies (FDs) and unique column combinations (UCCs) form a valuable
ingredient for many data management tasks, such as data cleaning, schema recovery, and …

Data lakes are becoming increasingly prevalent for Big Data management and data
analytics. In contrast to traditional 'schema-on-write'approaches such as data warehouses …

Maintaining data consistency is known to be hard. Recent approaches have relied on
integrity constraints to deal with the problem-correct and complete constraints naturally work …

Fashion retail has a large and ever-increasing popularity and relevance, allowing customers
to buy anytime finding the best offers and providing satisfactory experiences in the shops …

Database administrators construct secondary indexes on data tables to accelerate query
processing in relational database management systems (RDBMSs). These indexes are built …

ABSTRACT A missing value represents a piece of incomplete information that might appear
in database instances. Data imputation is the problem of filling missing values by means of …