A Model for integrating data governance and information management systems: Enhancing decision-making across industries
1 Kennesaw State University, USA.
2 Independent Researcher, Texas.
3 TD Bank, Toronto Canada.
4 Guaranty Trust Bank (Nigeria) Limited.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(03), 2635-2654
Publication history:
Received on 21 February 2024; revised on 28 March 2024; accepted on 30 March 2024
Abstract:
In the rapidly evolving digital landscape, the integration of data governance and information management systems has become critical for organizations aiming to enhance decision-making processes across various industries. This model proposes a comprehensive framework that seamlessly integrates data governance principles with advanced information management systems to ensure data accuracy, consistency, security, and accessibility. The model addresses the increasing complexity of data environments by establishing clear governance policies, standardized data practices, and robust data stewardship roles. It emphasizes the importance of aligning data governance with organizational objectives, ensuring that data assets are leveraged effectively to drive strategic decisions. The proposed model also incorporates cutting-edge technologies, such as artificial intelligence (AI) and machine learning (ML), to automate data management tasks, enhance data quality, and provide predictive analytics capabilities. By integrating these technologies, organizations can optimize data processing, reduce operational costs, and improve the timeliness and relevance of decision-making. The model further highlights the significance of a centralized data management platform that facilitates real-time data sharing and collaboration across departments, fostering a data-driven culture within organizations. Moreover, the model underscores the importance of compliance with regulatory requirements and industry standards, ensuring that data governance practices adhere to legal and ethical guidelines. By implementing this integrated approach, organizations can mitigate data risks, enhance data transparency, and build trust with stakeholders. The model is adaptable to various industries, including healthcare, finance, manufacturing, and telecommunications, offering a scalable solution to the challenges of managing complex data ecosystems. In conclusion, this model provides a strategic blueprint for integrating data governance and information management systems, enabling organizations to make informed, data-driven decisions. It supports the transformation of data into valuable insights, driving innovation, operational efficiency, and competitive advantage in the digital era.
Keywords:
Data Governance; Information Management Systems; Decision-Making; Data Quality; Artificial Intelligence; Machine Learning
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0