Understanding Data Quality. Philosophical Position and Important Definitions. D ata quality dimensions in the literature. include dimensions such as accuracy, reliability, importance , consistency, precision, timeliness, understandability, conciseness and usefulness
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Kahn et al. (1997) developed a data quality framework based on product and service quality theory, in the context of delivering quality information to information consumers.
A more formal approach to data quality is provided in the framework of Wand and Wang (1996) who use Bunge’s ontology to define data quality dimensions.
Concern with physical and physical media for communications of data
Discuss the strategies for ensuring quality data in all the categories listed in the form according to levels given.
“Data quality is the foundation for any data-driven effort, but the quality of information globally is poor. Organizations need to centralize their approach to data management to ensure information can be accurately collected and effectively utilized in today’s cross-channel environment.”
Thomas Schutz, senior vice president, general manager of Experian Data Quality