As the real world is massively complex, providing power for faster application processing and problem-solving has been a turning point in plenty of disciplines through the use of big data analytics with efficient tools such as predictive models, statistical algorithms, and what-if scenarios.

Over the years, and with the changing of the data landscape, the mature technology introduced a parallelization processing for big data that could drive more efficient and productive solutions for large complex problems without compromising the quality within a temporal sequence.