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Beyond data quality. Data excellence challenges from an enterprise, research and city perspective

 
: Sautter, Johannes; Litauer, Rebecca; Fischer, Rudolf; Klages, Tina; Wuchner, Andrea; Müller, Elena; Schaj, Gretel; Dobrokhotova, Ekaterina; Drews, Patrick; Riess, Stefan

:

Bernardino, Jorge (Ed.) ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
DATA 2018, 7th International Conference on Data Science, Technology and Applications 2018. Proceedings : July 26-28, 2018, in Porto, Portugal
Setúbal: SciTePress, 2018
ISBN: 978-989-758-318-6
S.245-252
International Conference on Data Science, Technology and Applications (DATA) <7, 2018, Porto>
Bundesministerium für Bildung und Forschung BMBF
16FDM027; HEFE
Heterogene Forschungsdaten im Stadtkontext: Governance für Analyse-, Planungs- und Echtzeitdaten
Englisch
Konferenzbeitrag
Fraunhofer IAO ()
Fraunhofer IRB ()

Abstract
Researchers and practitioners widely agree on data quality as one of the major goals of data management. However, data management departments in enterprises and organisations increasingly realise needs for data availability, compliance, operational excellence with regard to the domain and other data-challenges. In raised case studies in the enterprise, research and city domain, challenges regarding data availability, operational integration, compliance and quality of data management processes are analysed. Based on the concept of data quality, this paper argues for a similar concept with a broader scope for assessing an organisation’s data suitability. Based on literature and case studies this paper proposes a definition of the term data excellence as the capability of an organisation to reach its operational goals by ensuring the availability and integration of suitable, transparent and compliant high quality data.

: http://publica.fraunhofer.de/dokumente/N-506685.html