Abstract

Blockchain technology has recently gained significant attention in various industries due to its unique features such as decentralization, immutability, and transparency. These features make it an ideal technology for data science, which involves the analysis and interpretation of large amounts of data. This paper explores the potential of blockchain in data science and discusses the various ways in which blockchain can enhance the data science process. The paper first provides an overview of blockchain technology and its key features. It then discusses the current challenges faced by data science and how blockchain can help to address these challenges. Specifically, the paper highlights how blockchain can improve data quality, data security, and data privacy. The paper also presents several use cases where blockchain has been successfully applied in data science. These use cases include supply chain management, healthcare, and finance. The paper analyses these cases and explains how blockchain has helped to improve data management and decision-making processes. Finally, the paper concludes with a discussion of the limitations and future research directions of blockchain in data science. While blockchain has several potential benefits, it is not a one-size-fits-all solution. Further research is needed to explore the scalability and interoperability of blockchain in data science. Overall, this paper highlights the potential of blockchain in data science and provides a comprehensive analysis of its impact on data management and decision-making processes. Keywords—Data Science, Blockchain, Decentralized, cryptography, Smart Contract.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call