Akademik Veri Yönetim Sistemi
Data Quality Matters - Best Practices for Integrity and Assurance, Sebastian Ventura,José M. Luna and Antonio R. Moya Martín-Castaño, Editör, IntechOpen, London, ss.1-16, 2026
This chapter explores the intersection of data governance, data quality, andblockchain technology, presenting a paradigm shift from traditional centralized datamanagement to decentralized architectures. As data solidifies its role as a criticalasset, ensuring its integrity and trustworthiness has become paramount. We begin byestablishing the principles of data governance and quality, highlighting thelimitations of conventional systems that rely on trusted intermediaries, whichintroduce single points of failure and censorship risks. Blockchain technologyemerges as a compelling alternative, offering a decentralized, immutable, andtransparent ledger that fundamentally enhances data integrity and trust. Through ananalysis of its core components – including cryptographic hashing, consensusmechanisms, and distributed networks – we examine the inherent advantages anddisadvantages of blockchain. The chapter delves into the functional extensions ofblockchain, such as smart contracts and Decentralized Autonomous Organizations(DAOs), which enable automated, transparent, and autonomous governance models.However, the transition to blockchain is not without its challenges. We criticallyassess issues of scalability, data privacy, the “oracle problem,” and the “garbage in,garbage out” principle, which persist in decentralized environments. The chapterconcludes that the “quality” of blockchain as a data management solution is notabsolute but is contingent upon the specific requirements of the use case, demandinga careful evaluation of its trade-offs.