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Corporate Data Governance Framework and Organisational Success: Evolution and Challenges

Writer's picture: Tejasvi ATejasvi A

Updated: Jan 20

For decades, “governance” has been recognised as one of the most critical themes in organisations. From a corporate governance perspective, assets that need to be protected are physical, intellectual property, financial assets, human resources, and reputation. 


Corporate Data Governance Framework


Data is considered one of the assets that organisations must protect through an excellent corporate data governance framework. Organisations need to ensure that procedures and practices are in place to assess, direct, monitor, and protect data and related infrastructure for the value data provides to a corporation and its stakeholders. 


Over the years, practitioners and scholars have discussed and developed several theories and practical approaches to protecting shareholder value, resolving management problems, and monitoring costs. Good data governance frameworks should align with corporate governance objectives that maintain and strengthen an organisation’s economic performance and market integrity. 


Moreover, data can broadly impact multiple functions in an organisation, including marketing, pricing, accounting, organisational behaviour, corporate law, ethics, operations, and information technology. As data-related technologies, such as big data, generative ai and data quality, become more prevalent, managing data can result in better decisions, reduced costs, and increased customer loyalty. 


Therefore, organisations need to ensure that their data is actively managed and governed to protect their business interests.


Data governance frameworks have evolved in practice over the past fifteen years with significant contributions to literature from professional bodies like DAMA, EDM Council and IQ International. Developed in 2007, the basic data framework focuses on defining roles, responsibilities, and accountability, as well as organisational bodies’ policies, standards, and processes.



Data governance frameworks- Tejasvi Addagada

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