Modernizing Data Governance: A Strategic Shift in Enterprise Data Management |
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| © 2025 by IJCTT Journal | ||
| Volume-73 Issue-5 |
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| Year of Publication : 2025 | ||
| Authors : Shamnad Mohamed Shaffi, Jezeena Nikarthil Sidhick | ||
| DOI : 10.14445/22312803/IJCTT-V73I5P111 | ||
How to Cite?
Shamnad Mohamed Shaffi, Jezeena Nikarthil Sidhick, "Modernizing Data Governance: A Strategic Shift in Enterprise Data Management," International Journal of Computer Trends and Technology, vol. 73, no. 5, pp. 75-81, 2025. Crossref, https://doi.org/10.14445/22312803/IJCTT-V73I5P111
Abstract
The field of data governance is changing drastically due to the emergence of AI technologies. The way data is being managed, secured, and gained value is being re-imagined as AI has new capabilities and challenges. AI is rewriting data management rules by allowing for real-time monitoring, automatic decision-making, and predictive analytics on a scale and speeds never before possible. This change that we refer to as Data Governance 2.0 is distinguished by automation enhancement, predictive capabilities improvement, and dynamic approaches to data processing and security (These are not just incremental changes but a paradigm change in how organizations handle data governance. Automated data quality management, AI-driven compliance monitoring, and more are the effects of these technologies in every aspect of data management [3].
Organizations must adjust to the new Data Governance 2.0 since it has become crucial for success in the contemporary business world. Firms that integrate AI tools within their existing data governance systems are in a position of superiority in the market. These advantages include enhanced functioning, analytical skills, and risk management methods. Nevertheless, it is difficult for businesses since they experience numerous obstructions in this transition. They have to address ethical issues related to the use of AI, confront some technical issues and even train their employees so that they can learn new skills. The management groups are usually forced to rearrange their company structure to cope with these changes. Studying the current situation in the business landscape, it is evident that the necessity to understand and align with Data Governance 2.0 is important for firms keen to remain competitive in the current data-oriented economy [4].
Keywords
AI-Driven Governance, Automated Data Quality, Data Governance, Data Quality Management, Predictive Compliance.
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