Journal of Big Data

Aims and scope

The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.

Author: Sérgio M Dias

Dr. Sérgio M. Dias is a computer analyst of Federal Service of Data Processing (SERPRO) and Professor of Pontifical Catholic University of Minas Gerais (PUC Minas). He is Phd and MSc in Computer Science from Federal University of Minas Gerais (UFMG) in 2016 and 2010. B.S. degree in Computer Science from PUC Minas in 2007.

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