Academic and businesses alike are growing increasingly fascinated in business intelligence as the requirement for analyzing patterns in massive databases grows. As sensors nodes and computer crimes platforms expand, the amount of data collected has increased dramatically. Data from cameras, online networks, and economic information are intrinsically worthless due to distortion, unfinished information, and unpredictability. This article serves two purposes. Various big data tools are also addressed in the article, along with their distinguishing features. These areas have many research paths, but the purpose of this article is to allow exploration of these topics as well as the development and execution of optimal Big Data methods. Researchers interested in studying and participating in this rapidly expanding field will be able to learn about present trends as well as potential future directions. This article looks at big data, its challenges, and where it is headed in the future, as well as the Big Data Analytics methods used by various companies to help them make good investment decisions. This research, on the other hand, is limited to big data concepts and the issues they can solve. The goal of this paper is to look at the problems and roadblocks that are becoming more prevalent in this new industry.
Keywords
Analytics, Big Data, Machine Learning, Storage, Technologies.
