In this paper, David Loshin from Knowledge Integrity looks at common data error paradigms - descriptions, examples, and ways that data set quality is impacted by those common root causes for introducing errors. He then considers aspects of metadata management that help to limit the scope of introduced errors, and then how that metadata is used by parsing and standardization utilities to normalize data. Read this paper to learn more.