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    Organising accountabilities for data quality management - a data governance case study

    118328_10956_V C Organising accountabilities for data quality management - a data governance case study.pdf (467.9Kb)
    Access Status
    Open access
    Authors
    Weber, K.
    Cheong, Lai
    Otto, B.
    Chang, Vanessa
    Date
    2008
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Weber, Kristin and Cheong, Lai and Otto, Boris and Chang, Vanessa. 2008. Organising accountabilities for data quality management - a data governance case study, in Dinter B. and Winter, R. and Chamoni, P. and Gronau, N. and Turowski, K. (ed), Conference DW2008: Synergies through Integration and Information Logistics, Oct 27 2008, pp. 347-359. St Gallen, Switzerland: Koellen Druck+Verlag.
    Source Title
    Konferenz DW2008 Synergien Durch Integration und Informationslogistik
    Source Conference
    Conference DW2008 -: Synergies through Integration and Information Logistics
    Additional URLs
    http://web.iwi.unisg.ch/org/iwi/iwi_pub.nsf/wwwPublYearEng/028D5245B5975BF7C12574F1002EBB0E
    ISBN
    9783885792321
    Faculty
    Curtin Business School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/45062
    Collection
    • Curtin Research Publications
    Abstract

    Enterprises need corporate data quality management (DQM) that combines business-driven and technical perspectives to respond to strategic and operational challenges that demand high-quality corporate data. Hitherto, companies have assigned accountabilities for DQM mostly to IT departments. They have thereby ignored the organisational issues that are critical to the success of DQM. With data governance, however, companies implement corporate-wide accountabilities for DQM that encompass professionals from business and IT. This study examines a large organisation that has adopted an ad-hoc data governance model to manage its data. It was found that its DQM efforts were hampered mainly by the lack of clear roles and responsibilities and the lack of mandate to carry out data quality improvement initiatives. In order to promote effective DQM, this research identifies a data governance structure with the emphasis on collaboration between business and IT to support organisations.

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