Udvidet returret til d. 31. januar 2025

Data Quality and its Staleness dimension - Themis Palpanas - Bog

Bag om Data Quality and its Staleness dimension

By its nature, term ¿data quality¿ with its generic meaning ¿fitness for use¿ has both subjective and objective aspects. To demonstrate how one can benefit from measuring and controlling quality of one¿s data, in this book we presented three real world use cases which demonstrate a top-down research approach of the data quality scope in three different real world applications. In particular, we study the following problems: 1) how quality of data can be defined and propagated to customers in a business intelligence application for quality-aware decision making; 2) how data quality can be defined, measured and used in a web-based system operating with semi-structured data from and designated to both humans and machines; 3) how a data-driven (vs. system-driven) time-related data quality notion of staleness can be defined, efficiently measured and monitored in a generic information system. The work should help researchers and professionals working on both generic data quality problems as its understanding in a given context, and on data quality¿s specific applications as measurement its dimensions.

Vis mere
  • Sprog:
  • Engelsk
  • ISBN:
  • 9783848409365
  • Indbinding:
  • Paperback
  • Sideantal:
  • 120
  • Udgivet:
  • 26. juni 2014
  • Størrelse:
  • 229x152x7 mm.
  • Vægt:
  • 186 g.
  • 2-3 uger.
  • 23. november 2024

Normalpris

  • BLACK NOVEMBER

Medlemspris

Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Data Quality and its Staleness dimension

By its nature, term ¿data quality¿ with its generic meaning ¿fitness for use¿ has both subjective and objective aspects. To demonstrate how one can benefit from measuring and controlling quality of one¿s data, in this book we presented three real world use cases which demonstrate a top-down research approach of the data quality scope in three different real world applications. In particular, we study the following problems: 1) how quality of data can be defined and propagated to customers in a business intelligence application for quality-aware decision making; 2) how data quality can be defined, measured and used in a web-based system operating with semi-structured data from and designated to both humans and machines; 3) how a data-driven (vs. system-driven) time-related data quality notion of staleness can be defined, efficiently measured and monitored in a generic information system. The work should help researchers and professionals working on both generic data quality problems as its understanding in a given context, and on data quality¿s specific applications as measurement its dimensions.

Brugerbedømmelser af Data Quality and its Staleness dimension



Gør som tusindvis af andre bogelskere

Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.