Evolution and impact of Big Data in the business sector

Abstract

The general objective of this article was to understand the historical evolution of Big Data in the business sector. The type of research has a qualitative narrative structure, this design sought to generate an explanation and analysis of the evolution of the concept of Big Data over time, through the collection and review of bibliographic publications of scientific articles, such as ProQuest, Google Scholar, EBSCO, as well as many others. In the same way, the strategy was the collection of bibliographic sources and the tool used was the matrix of references of scientific investigations. In the result, more was learned about Big Data and how it has changed over time and how to implement it such as extract, transform, load (ETL) to achieve greater compression of the data and be able to make more efficient decisions in the industries that use data there. Additionally, the analysis identified various research topics, such as financial and consumer risk management, text mining, and writing and evolutionary algorithms. The analysis concludes with a study of the repercussions for the various spaces of useful administration and the gaps that have existed over time, both in research and in practice.