Unleashing Machine Learning onto Big Data: Issues, Challenges and Trends

Abstract

In modern digital world, we have data deluge, but still starving for information. Big Data era is characterized by vast amounts of data sized in the order of petabytes or even exabytes coming at high speed from variety of sources. These unstructured data have got tremendous potential, but Big data by itself has no value unless it is processed leading to derivation of meaningful insights. This is where Machine Learning comes into picture which helps machine to learn and act on its own. Machine Learning can help us to sniff through enormous quantities of data, process them and get meaningful results. The confluence of Big Data and Machine Learning is allowing organizations to automate and improve complex descriptive, predictive and prescriptive analytical tasks and arriving at informed decision making. This is to say that, harnessing the value & power of Big Data can offer great insights to the companies with the help of Machine Learning (ML) increasing their revenues and providing a competitive advantage over their rivals. Machine Learning is acting as a catalyst to derive tangible value from Big Data and serving as key to unlocking the potential of Big Data Analytic. The management of big data gives rise to concerns regarding data collection efficiency, data processing, analytic, and security thereby opening new paradigms of research & innovations. This is a hot research area and amalgamation of Machine Learning with Big Data is proving to be major performance booster providing information which were hidden and not to be seen earlier. ML based algorithms and development in the area are explored and discussed at length in this chapter. It focuses on applications of Machine Learning to Big Data, issues, challenges and most recent trends in the area.