Big Data is an essential research area for governments, institutions, and private agencies to
support their analytics decisions. Big Data refers to all about data, how it is collected …

Generative AI has made significant strides, yet concerns about the accuracy and reliability of
its outputs continue to grow. Such inaccuracies can have serious consequences such as …

With the abundance of raw data generated from various sources, Big Data has become a
preeminent approach in acquiring, processing, and analyzing large amounts of …

One of the main challenges that data cleaning systems face is to automatically identify and
repair data errors in a dependable manner. Though data dependencies (aka integrity …

Data cleaning is frequently an iterative process tailored to the requirements of a specific
analysis task. The design and implementation of iterative data cleaning tools presents novel …

We study the problem of self-supervised and interpretable data cleaning, which
automatically extracts interpretable data repair rules from dirty data. In this paper, we …

We present Falcon, an interactive, deterministic, and declarative data cleaning system,
which uses SQL update queries as the language to repair data. Falcon does not rely on the …

Data cleaning, a prerequisite to subsequent data analysis, has always been the focus of
data science research. Datasets with errors can severely detract from the quality of …

While the potential benefits of Big Data adoption are significant, and some initial successes
have already been realized, there remain many research and technical challenges that must …

Data cleaning is, in fact, a lively subject that has played an important part in the history of
data management and data analytics, and it still is undergoing rapid development …