Preprint Review Version 1 This version is not peer-reviewed

Enhancing Decentralized Decision-Making with Big Data and Blockchain Technology. A Comprehensive Review

Version 1 : Received: 23 July 2024 / Approved: 24 July 2024 / Online: 25 July 2024 (00:10:25 CEST)

How to cite: Theodorakopoulos, L.; Theodoropoulou, A.; Halkiopoulos, C. Enhancing Decentralized Decision-Making with Big Data and Blockchain Technology. A Comprehensive Review. Preprints 2024, 2024071977. https://doi.org/10.20944/preprints202407.1977.v1 Theodorakopoulos, L.; Theodoropoulou, A.; Halkiopoulos, C. Enhancing Decentralized Decision-Making with Big Data and Blockchain Technology. A Comprehensive Review. Preprints 2024, 2024071977. https://doi.org/10.20944/preprints202407.1977.v1

Abstract

Big Data and blockchain technology are coming together to revolutionize how decisions are made in a decentralized way across various industries. This review looks at how these technologies, along with distributed systems, can improve data security, transparency, and real-time processing, making decision-making more efficient and informed. The integration enhances data security with unchangeable records, increases transparency and traceability, and supports real-time data analysis. However, there are challenges to overcome, including scalability, data privacy, interoperability, regulatory compliance, and high costs. By examining case studies such as Estonia's healthcare system, IBM and Walmart's Food Trust, and the Brooklyn Microgrid project, we explore the practical applications and benefits of combining Big Data with blockchain. Despite these hurdles, the review finds that the ongoing advancements and innovative solutions in these technologies offer significant promise. They are set to drive the adoption and effectiveness of decentralized decision-making, ultimately leading to better efficiency and outcomes across multiple sectors.

Keywords

big data analytics; distributed systems; consensus mechanisms; decentralized systems; real-life case studies.

Subject

Computer Science and Mathematics, Computer Science

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