logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Data Quality Management with Semantic Technologies by Christian Fürber (auth.) ISBN 9783658122249, 9783658122256, 3658122242, 3658122250

  • SKU: EBN-5357200
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.4

40 reviews
Instant download (eBook) Data Quality Management with Semantic Technologies after payment.
Authors:Christian Fürber (auth.)
Pages:230 pages.
Year:2016
Editon:1
Publisher:Gabler Verlag
Language:english
File Size:4.4 MB
Format:pdf
ISBNS:9783658122249, 9783658122256, 3658122242, 3658122250
Categories: Ebooks

Product desciption

(Ebook) Data Quality Management with Semantic Technologies by Christian Fürber (auth.) ISBN 9783658122249, 9783658122256, 3658122242, 3658122250

Christian Fürber investigates the useful application of semantic technologies for the area of data quality management. Based on a literature analysis of typical data quality problems and typical activities of data quality management processes, he develops the Semantic Data Quality Management framework as the major contribution of this thesis. The SDQM framework consists of three components that are evaluated in two different use cases. Moreover, this thesis compares the framework to conventional data quality software. Besides the framework, this thesis delivers important theoretical findings, namely a comprehensive typology of data quality problems, ten generic data requirement types, a requirement-centric data quality management process, and an analysis of related work.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products