Data Integrity as a Code (DIaC): A New Paradigm in Data Governance

Rukhsana Said; Revathi Bommu,

Rukhsana Said Department of Computer Science, University of Leads
Revathi Bommu, University of Illinois Springfield, One University Plaza, Springfield, IL 62703

Keywords: Data Integrity, Data Governance, Data Management, Data Quality, Automation, Version Control, Testing, Collaborative Development, Big Data

Abstract

Data Integrity as a Code (DIaC) represents a groundbreaking paradigm shift in data governance, blending principles of software engineering with traditional data management approaches. This innovative concept treats data integrity not as a mere objective but as a dynamic, code-driven process. This paper explores the emergence of DIaC, its core principles, and its implications for data governance practices. We discuss the role of automation, version control, testing, and collaborative development in the DIaC paradigm, highlighting how organizations can leverage this approach to maintain data integrity, improve data quality, and enhance decision-making. By adopting DIaC, organizations can transform their data governance strategies and navigate the complexities of big data environments more effectively.

Data Integrity as a Code (DIaC): A New Paradigm in Data Governance

Abstract

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