Big Data Processing Solutions

Dragoş Cătălin BARBU
Bucharest University of Economic Studies

Abstract: This paper aims to describe the current scientific context for Big Data Processing. The topics discussed were structured in two major directions: information technology – Big Data Processing, Big Data Analytics, Machine Learning and IoT, and the implementation of the theoretical principles in the business area, respectively regulations and policies. In the context of Big Data, traditional data processing techniques and platforms are less efficient, with a slow response and lack of scalability, performance and precision. Over the last decade, the challenges that Big Data has generated have been highlighted by both scientists, programmers and mathematicians as well as specialists in the field, experts, consultants and even politicians, their results being published both in research papers, articles, promoting the development of solutions and advanced technologies, but also creating a legal framework necessary for the implementation of strategies through regulations or normative acts of competent institutions or organizations, such as the European Parliament.

Keywords: Big Data analytics, IoT, Data mining, Hadoop, Data Storage, Cloud computing, Big Data processing.

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Dragoş Cătălin BARBU, Big Data Processing Solutions, Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 29(2), pp. 35-48, 2019.