Root cause analysis of data quality issues using the Odigos framework – A case study

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School of Business | Master's thesis
Degree programme
Information and Service Management (ISM)
75 + 5
Data quality issues are a significant concern for companies, but it can be difficult to address. With technological advancement, the number of data quality issues increases, adding complexity to efforts aimed at identifying their root causes. This research study focuses on the applicability and generalizability of the Odigos framework in identifying root cause of data quality issues. The Odigos framework has not been widely applied and extended beyond process mining and hospital digital data area. Therefore, this study contributes to filling an existing research gap. This thesis is a single-case study that collected empirical data by conducting semi-structured interviews with the data organization and system end users of a Finnish forestry company. Based on the interview and stakeholders’ insight, the Odigos framework is employed to identify data quality root causes which implies enablement of data quality evaluation and implementation and better management of data quality. The result of this thesis supports past research that data quality root causes can emanate from three worlds – personal, material, and social. By using the proposed framework, organizations can establish a starting point for operationalizing the assessment and enhancement of data quality. This, in turn, leads to a greater appreciation of data quality and results in improved processes for data maintenance, IT solutions, data quality itself, and the relevant expertise. This research acts as an advocate for the strong applicability and generalizability of the Odigos framework in revealing data quality complications in business settings. Based on perceived limitations, this thesis calls for more research to evaluate and extend the framework in other settings.
Thesis advisor
Liu, Yong
data, quality, root, cause
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