Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and wrong business decisions. According to a report by InsightSquared in 2012, poor data across businesses and the government cost the United States economy 3.1 trillion dollars a year. To detect data errors, data quality rules or integrity constraints (ICs) have been proposed as a declarative way to describe legal or correct data instances. Any subset of data that does not conform to the defined rules is considered erroneous, which is also referred to as a...
Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and wrong bus...
