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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 4, 2019.
Abstract: The importance of data analysis in companies grows every day, with a global market that generates large amounts of transactions. Industry 4.0 is one of the technological trends, which is a set of diverse technologies whose objective is the digitalization and technological connectivity of the entire value chain of organizations. Data analysis and decision making in real time have a positive impact on efficiency. One of the technologies that support this concept is big data, which can support companies to use and manage large volumes of data as support in decision making. In this research project, the computational environment of Apache Hadoop software has been analyzed to create a technological strategy that supports companies in creating a roadmap to know and implement big data technology; as a result, a computer laboratory for big data has been created at the Autonomous University of Coahuila, Mexico to support medium-sized manufacturing companies in their data analysis strategy for decision making.
Alicia Valdez, Griselda Cortes, Sergio Castaneda, Laura Vazquez, Angel Zarate, Yadira Salas and Gerardo Haces Atondo, “Big Data Strategy” International Journal of Advanced Computer Science and Applications(IJACSA), 10(4), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100434
@article{Valdez2019,
title = {Big Data Strategy},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100434},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100434},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {4},
author = {Alicia Valdez and Griselda Cortes and Sergio Castaneda and Laura Vazquez and Angel Zarate and Yadira Salas and Gerardo Haces Atondo}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.