Big Data and Artificial Intelligence on the Blockchain: A Review

Abstract

As organizations seek to derive greater value from rapidly expanding datasets, they face challenges related to big data governance including security, privacy, regulatory compliance, access controls, and building trust across entities. Blockchain has emerged as a promising technology for managing and analyzing big data in a controlled, transparent manner through its decentralized architecture and cryptographic foundations. This paper explores how blockchain can enable more secure sharing of big data that mitigates systemic impediments to wider application. We first examine unique properties of blockchain technology that allow distrusting parties to collaborate through immutable records, consensus protocols, smart contracts, and permissions management. We then profile real-world use cases in sectors like healthcare, supply chain logistics, and financial services where blockchain strengthens big data usage. Finally, current scaling and architectural limitations are discussed along with an outlook on the remaining technology gaps and skills needed to fully bridge blockchain, distributed data, advanced analytics, and machine learning. The paper ultimately argues blockchain may profoundly expand big data’s capabilities but still requires further innovation across hardware infrastructure, platforms, analytics interfaces, and organizational strategy.