Big data sob a ótica de modelagem de dados multidimensional para soluções de business intelligence

Abstract

The speed of the spread of global age technologies and the ever-changing consumer characteristics present organizations with significant challenges from a survival strategy perspective. As a result, the management of your information becomes absolutely relevant - this is no longer a matter of mere choice. Technologically consolidated concepts such as Business Intelligence (BI) should be part of the routine of companies. Considering, however, the significant volumes of data from sources such as social networks, the Internet of things, and industry 4.0, approaches such as Big Data are no longer simply experimental. This work is premised on the foundation of these elements and their dependencies, as well as the development of a new process model that combines approaches from ELT (Big Data) and Business Intelligence (ETL): the Extract, Load, Transform and ELTL. To charge). Such a model aims to achieve the optimal and combined adoption of what, best, each of these contexts can present. Speed and quality tests was performed, using SQL and Hadoop family tools. All with the objective of validating the applicability of this new model and showing that BI and BDT are concepts that, although distinct and with different objectives, can be used together, in a non-exclusive way, for better analysis and understanding of the data (sic)