A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is
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. Data cleaning exercise often consist of two phases: error detection and error repairing. Error detection techniques can either be quantitative or qualitative; and error repairing is performed by applying data transformation scripts or by involving human experts, and sometimes both. In this tutorial, we discuss the main facets anddoi:10.14778/3007263.3007320 fatcat:5tnfp3bhqffdbpvqgjabp7ctoq