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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Towards Higher Quality Data: Impact of Perception of Data Quality on IT Investment - Ghana

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Author Kenneth Kwame Azumah, Henry Osborn Quarshie
ISSN 2079-8407
On Pages 1614-1621
Volume No. 3
Issue No. 12
Issue Date January 01, 2013
Publishing Date January 01, 2013
Keywords Data, quality, perception, quality monitoring, quality initiative, IT investment, e-business.


Quality like beauty is a subjective term that lies in the “eyes of the beholder”. Thus the concept of Data Quality is also mostly intuitive: it depends on the user of the data. The perception of employees about the quality of the data used in their organizations plays a critical role in determining the level of attention given to organizational information. The perception may impact negatively on the level of IT investment needed to build and maintain information systems which are critical in national and organizational governance. Four data quality dimensions namely accuracy, completeness, consistency and timeliness may be measured for any organizational data. A data quality survey could at best reveal the level of usefulness of the data to an employee in his job or to an organization in its operations. In this study, a survey was conducted among employees about the perceived quality of their data based on the four mentioned dimensions of data quality and the data quality initiatives that have been put in place. In the results an average of 66% of the respondents expressed their satisfaction on the data they were collecting, consuming or had in their custody. An even lower percentage of 53% said their organization had adopted some form of data quality management. The results also suggested that the issue of data quality has not been given enough attention by organizations whereas the consumers, custodians and collectors of the information report that there were between 25% to 40% deficiencies in quality of data used in their jobs. A general recommendation was the implementation of data quality initiatives and provision of mechanisms for obtaining feedback from employees on unsatisfactory data items in the workplace.

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