Profiling data to determine metadata about a given dataset is an important and frequent
activity of any IT professional and researcher and is necessary for various use-cases. It …

Data collection has become a ubiquitous function of large organizations {not only for record
kee**, but to support a variety of data analysis tasks that are critical to the organizational …

Data profiling comprises a broad range of methods to efficiently analyze a given data set. In
a typical scenario, which mirrors the capabilities of commercial data profiling tools, tables of …

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 …

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

Existing methodologies for identifying data quality problems are typically user-centric, where
data quality requirements are first determined in a top-down manner following well …

Process mining techniques require event logs which, in many cases, are obtained from
databases. Obtaining these event logs is not a trivial task and requires substantial domain …

Understanding, analyzing, and ultimately improving business processes is a goal of
enterprises today. These tasks are challenging as business processes in modern …

In this paper, we introduce a new problem termed query reverse engineering (QRE). Given a
database DD and a result table TT—the output of some known or unknown query QQ on DD …

The discovery of all unique (and non-unique) column combinations in a given dataset is at
the core of any data profiling effort. The results are useful for a large number of areas of data …