Year: 2023
Type: dissertation
Abstract: Higher Education Institutions (HEIs) collect data from their internal operations, external databases, and research activities on a daily basis. Previous studies indicated most HEIs were facing difficulties to unlock (i.e., to obtain) value from their data assets. Effective data governance can enhance HEIs to manage their institutional data by establishing frameworks, responsibilities, accountabilities, policies, procedures, guidelines, and processes. This study attempted to bridge the gap by exploring the challenges and opportunities pertaining to data governance practices in Finnish Higher education Institutions (HEIs). An appropriate data governance framework was drawn from the literature which focuses on decision domains of data governance to meet the objectives of the study. This study is qualitative research in which exploratory research approach was adopted to gain in-depth understanding of the research domain. Alongside, data was collected through semi-structured interviews. Heterogeneous purposive sampling was employed to choose experts from different roles. Professionals who were working ICT, Library, and administration areas at two HEIs were interviewed. The respondents were selected purposively based on their familiarity with the topic of this study and acquaintance with utilization of data for decision making. Moreover, qualitative research methods such as thematic analysis and deductive coding were used to analyze, and categorize the themes based on the chosen framework The result of the study revealed that in the majority of the data governance decision domains, the HEIs have developed policies, procedures, and guidelines to ensure management of data assets and maintain quality of data. Moreover, by considering data as institutional assets, the HEIs were able to generate reports and the statistics, open and reuse research data, and publications, comply with regulations and laws, measure academic performances, manage data security risks, and control data flow. The finding of the study also revealed challenges pertaining to data governance practices. Most of the challenges stemmed from the absence of clear policy, lack of expertise, lack of establishing comprehensive roles regarding data-related activities, and lack of plans in data quality audits and data inventory areas. The findings of the study showed that majority of data governance challenges are more strategic than operational. Therefore, decision makers at HEIs are required to bridge the identified gaps through establishing comprehensive framework, policies, procedures, and plans that covers all data governance decision domains.
Source: Doria (University of Helsinki)
Author: Gutema, Dandi
Language: English
Topic: Data Quality and Management
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7115301130