Ramiz M. Aliguliyev, Yadigar N. Imamverdiyev

Big data technologies provide important approaches and tools for the creation of data management systems in oil and gas industry. The paper proposes a conceptual architecture for a hybrid Big data platform for storing and analyzing large volumes of data gathered from oil and gas industry systems in real-time by deep analytics and machine learning methods in distributed cluster systems. We also consider the question of selection of necessary tools from Hadoop ecosystem for building of a viable Big data solution (pp.3-13).

Keywords: oil and gas industry, Big Data, Hadoop, Apache Spark, MapReduce, Big Data analytics, Big Data architecture.
DOI : 10.25045/jpit.v08.i1.01
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