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Data Governance Strategies for Maintaining Data Integrity

Authors: Jordon Smith;

Data Governance Strategies for Maintaining Data Integrity

Abstract

Data governance is crucial for maintaining data integrity in an era where data is abundant, diverse, and constantly evolving. This paper explores effective data governance strategies to preserve data integrity. It delves into the importance of data governance, the challenges it addresses, and the best practices organizations can implement. Key topics include data quality, data lifecycle management, data stewardship, and the role of technology in supporting data governance. By examining real-world case studies and industry standards, this paper provides valuable insights for organizations seeking to establish robust data governance frameworks that ensure data integrity, reliability, and trustworthiness.

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Keywords

Data Governance, Data Integrity, Data Quality, Data Lifecycle Management, Data Stewardship, Data Governance Framework, Data Governance Best Practices, Data Trustworthiness, Data Governance Technology, Data Compliance.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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