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 …

As key decisions are often made based on information contained in a database, it is
important for the database to be as complete and correct as possible. For this reason, many …

Data cleaning with guaranteed reliability is hard to achieve without accessing external
sources, since the truth is not necessarily discoverable from the data at hand. Furthermore …

Data cleaning (or data repairing) is considered a crucial problem in many database-related
tasks. It consists in making a database consistent with respect to a given set of constraints. In …

Despite the increasing importance of data quality and the rich theoretical and practical
contributions in all aspects of data cleaning, there is no single end-to-end off-the-shelf …

Data cleaning techniques usually rely on some quality rules to identify violating tuples, and
then fix these violations using some repair algorithms. Oftentimes, the rules, which are …

We study the problem of introducing errors into clean databases for the purpose of
benchmarking data-cleaning algorithms. Our goal is to provide users with the highest …

Data cleansing approaches have usually focused on detecting and fixing errors with little
attention to scaling to big datasets. This presents a serious impediment since data cleansing …

Data integration solutions dealing with large amounts of data have been strongly required in
the last few years. Besides the traditional data integration problems (eg schema integration …

As key decisions are often made based on information contained in a database, it is
important for the database to be as complete and correct as possible. For this reason, many …