Data quality

Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning".[1][2][3] Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose. People's views on data quality can often be in disagreement, even when discussing the same set of data used for the same purpose. When this is the case, data governance is used to form agreed upon definitions and standards for data quality. In such cases, data cleansing, including standardization, may be required in order to ensure data quality.[4]

  1. ^ Redman, Thomas C. (30 December 2013). Data Driven: Profiting from Your Most Important Business Asset. Harvard Business Press. ISBN 978-1-4221-6364-1.
  2. ^ Fadahunsi, Kayode Philip; Akinlua, James Tosin; O’Connor, Siobhan; Wark, Petra A; Gallagher, Joseph; Carroll, Christopher; Majeed, Azeem; O’Donoghue, John (March 2019). "Protocol for a systematic review and qualitative synthesis of information quality frameworks in eHealth". BMJ Open. 9 (3): e024722. doi:10.1136/bmjopen-2018-024722. ISSN 2044-6055. PMC 6429947. PMID 30842114.
  3. ^ Fadahunsi, Kayode Philip; O'Connor, Siobhan; Akinlua, James Tosin; Wark, Petra A.; Gallagher, Joseph; Carroll, Christopher; Car, Josip; Majeed, Azeem; O'Donoghue, John (2021-05-17). "Information Quality Frameworks for Digital Health Technologies: Systematic Review". Journal of Medical Internet Research. 23 (5): e23479. doi:10.2196/23479. PMC 8167621. PMID 33835034.
  4. ^ Smallwood, R.F. (2014). Information Governance: Concepts, Strategies, and Best Practices. John Wiley and Sons. p. 110. ISBN 9781118218303. Archived from the original on 2020-07-30. Retrieved 2020-04-18. Having a standardized data governance program in place means cleaning up corrupted or duplicated data and providing users with clean, accurate data as a basis for line-of-business software applications and for decision support analytics in business intelligence (BI) applications.

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