Quality of data governance and its impacts on corporate performance management
Thesis title: | Quality of data governance and its impacts on corporate performance management |
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Author: | Mammadov, Orkhan |
Thesis type: | Diploma thesis |
Supervisor: | Kučera, Jan |
Opponents: | Maryška, Miloš |
Thesis language: | English |
Abstract: | Nowadays, data plays vital role in life of modern organizations. However, data management and especially, data quality are unsatisfied in most of them. Recently, new methodology, known as Data Governance was developed. This methodology defines roles, responsibilities, standards and policies for Data Management. Literature shows that, complete conceptualization of factors affecting Data Governance quality is missing. There is also a limited research regarding the effects of Data Governance quality on the corporate performance management. This study is prepared to analyze and fill this gap. Through conceptualization of Data Governance based on literature, we have developed conceptual framework or model. Five variables, which affect Data Governance quality were identified in this framework: (1) Data Stewardship and Ownership, (2) Data Integration, (3) Data Modeling, (4) Data Quality and (5) Compliance with policies. This model defines above mentioned factors of Data Governance quality and how Data Governance impacts corporate performance management. The practical part of this study is based on interview, considering this framework. This research also approves, that the poor Data Governance has negative influence on corporate performance. So, organization needs to increase quality of its Data Governance to improve business performance and to realize full business value. |
Keywords: | data governance; data integration; data stewardship and ownership; compliance with policies; corporate performance management; data management; corporate governance; data quality; Data assets; data modeling |
Thesis title: | Quality of data governance and its impacts on corporate performance management |
---|---|
Author: | Mammadov, Orkhan |
Thesis type: | Diplomová práce |
Supervisor: | Kučera, Jan |
Opponents: | Maryška, Miloš |
Thesis language: | English |
Abstract: | Nowadays, data plays vital role in life of modern organizations. However, data management and especially, data quality are unsatisfied in most of them. Recently, new methodology, known as Data Governance was developed. This methodology defines roles, responsibilities, standards and policies for Data Management. Literature shows that, complete conceptualization of factors affecting Data Governance quality is missing. There is also a limited research regarding the effects of Data Governance quality on the corporate performance management. This study is prepared to analyze and fill this gap. Through conceptualization of Data Governance based on literature, we have developed conceptual framework or model. Five variables, which affect Data Governance quality were identified in this framework: (1) Data Stewardship and Ownership, (2) Data Integration, (3) Data Modeling, (4) Data Quality and (5) Compliance with policies. This model defines above mentioned factors of Data Governance quality and how Data Governance impacts corporate performance management. The practical part of this study is based on interview, considering this framework. This research also approves, that the poor Data Governance has negative influence on corporate performance. So, organization needs to increase quality of its Data Governance to improve business performance and to realize full business value. |
Keywords: | Data assets; data management; corporate governance; data governance; data quality; data modeling; data integration; data stewardship and ownership; compliance with policies; corporate performance management |
Information about study
Study programme: | Aplikovaná informatika/Information Systems Management |
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Type of study programme: | Magisterský studijní program |
Assigned degree: | Ing. |
Institutions assigning academic degree: | Vysoká škola ekonomická v Praze |
Faculty: | Faculty of Informatics and Statistics |
Department: | Department of Information Technologies |
Information on submission and defense
Date of assignment: | 24. 10. 2017 |
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Date of submission: | 9. 5. 2018 |
Date of defense: | 11. 6. 2018 |
Identifier in the InSIS system: | https://insis.vse.cz/zp/63641/podrobnosti |