The Imperative of Data Integrity: A DIaC Approach

Hassan Ali

Hassan Ali Department of Computer Science, University of Cambridge

Keywords: Data Integrity, Data Governance, DIaC (Data Integrity as a Code), Big Data, Data Quality, Automation, Version Control, Compliance, Trust, Data Management, Data Security, Data Assurance, Data, Data Ethics, Data Stewardship, Case Studies

Abstract

Data integrity is a cornerstone of effective data governance in the era of big data. Ensuring that data remains accurate, reliable, and secure is essential for organizations to make informed decisions, comply with regulations, and maintain trust with stakeholders. This paper explores the imperative of data integrity and introduces the concept of Data Integrity as a Code (DIaC) as a forward-looking approach to address the challenges of modern data management. DIaC leverages automation, version control, and collaborative practices to embed data integrity into the fabric of data governance. This paper discusses the principles of DIaC, implementation strategies, benefits, and case studies to illustrate its real-world impact. Embracing DIaC is not just a choice but an imperative for organizations seeking to thrive in the data-driven landscape while safeguarding the trust and integrity of their data assets.