Critical success factors for data governance: a theory building approach

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dc.contributor.advisor Sammon, David en
dc.contributor.advisor Daly, Mary en
dc.contributor.author Alhassan, Ibrahim
dc.date.accessioned 2018-06-22T10:47:00Z
dc.date.issued 2018
dc.date.submitted 2018
dc.identifier.citation Alhassan, I. 2018. Critical success factors for data governance: a theory building approach. PhD Thesis, University College Cork. en
dc.identifier.endpage 234 en
dc.identifier.uri http://hdl.handle.net/10468/6377
dc.description.abstract Thinking about data strategically is a challenge for many organisations today. Governing data has become vital in running a business successfully. In recent years, the volume of data used within organisations has increased dramatically, playing a critical role in business operations. The implementation of data governance remains problematic for the majority of organisations. Data governance is considered to be a relatively emerging subject, and several researchers have proposed different models that help in understanding the concepts related to it. Reviewing the literature, however, reveals a lack of research into the critical success factors (CSFs) for data governance, which shows a need for further studies aimed at understanding the success factors in governing an organisation’s data. This research study aims to identify the critical success factors for data governance that enable organisations to introduce an effective data governance programme. The research follows the building theory from case studies approach by conducting two in-depth case studies in Saudi Arabia. To gather the data, a CSF approach is employed in order to conduct the interviews. The data are then analysed using open, axial, and selective coding techniques in order to inductively identify the CSFs for data governance along with the recommended actions associated with each CSF. This study contributes to data governance research by providing nine CSFs for data governance, as well as identifying a list of recommended actions for putting the CSFs into practice. In addition, follow a rigorous inductive research approach, two theoretical models emerged: 1) a data governance activities model, which helps in better understanding the activities related to data governance that are reported in the literature; and 2) an open, axial, and selective coding framework, which helps in understanding how to use these coding techniques when analysing qualitative data. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher University College Cork en
dc.rights © 2018, Ibrahim Alhassan. en
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/ en
dc.subject Data governance en
dc.subject Critical success factors en
dc.title Critical success factors for data governance: a theory building approach en
dc.type Doctoral thesis en
dc.type.qualificationlevel Doctoral en
dc.type.qualificationname PhD en
dc.internal.availability Full text available en
dc.description.version Accepted Version
dc.contributor.funder Saudi Electronic University en
dc.description.status Not peer reviewed en
dc.internal.school Accounting, Finance and Information Systems en
dc.check.reason This thesis is due for publication or the author is actively seeking to publish this material en
dc.check.opt-out Not applicable en
dc.thesis.opt-out false
dc.check.entireThesis Entire Thesis Restricted
dc.check.embargoformat Apply the embargo to the e-thesis on CORA (If you have submitted an e-thesis and want to embargo it on CORA) en
ucc.workflow.supervisor dsammon@ucc.ie
dc.internal.conferring Autumn 2018 en


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© 2018, Ibrahim Alhassan. Except where otherwise noted, this item's license is described as © 2018, Ibrahim Alhassan.
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