Blockchain Technology in Data Engineering: Enhancing Data Integrity and Traceability in Modern Data Pipelines

Author(s)	Sainath Muvva
Country	United States
Abstract	Data integrity and traceability present formidable challenges in contemporary data engineering, exacerbated by the exponential growth of data-centric applications. This paper investigates the transformative potential of blockchain technology in addressing these issues within data pipelines. We delve into blockchain's capacity to revolutionize data provenance tracking, establish tamper-resistant audit mechanisms, and facilitate secure, decentralized data collaboration. Our analysis encompasses a spectrum of industries, from fintech to healthcare, showcasing real-world implementations and their outcomes. We critically examine the hurdles in blockchain adoption, including performance bottlenecks, legacy system integration complexities, and evolving regulatory landscapes. The discourse extends to emerging paradigms, such as blockchain-AI synergies and quantum-resilient distributed ledgers, offering a forward-looking perspective on data engineering's evolution. By synthesizing current implementations with future projections, this research aims to provide a comprehensive blueprint for leveraging blockchain to enhance data integrity and traceability in next-generation data ecosystems.
Keywords	-
Field	Engineering
Published In	Volume 4, Issue 7, July 2023
Published On	2023-07-05
DOI	https://doi.org/10.5281/zenodo.14646547
Short DOI	https://doi.org/g8zrxh

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