ABSTRACT
Analytics can be used for improving performance, driving sustainable growth through innovation, speeding up response time to market and environmental changes, and anticipating and planning for change while managing and balancing risk. These benefits are achieved through a framework that deploys automated data analysis within the business context. The paradigm shift is from intuition-driven decision-making to data-driven, computer-assisted decision-making that takes advantage of large amounts of data or data from multiple sources. Predictive analytics models are very popular in predicting the behavior of customers based on past buying history and perhaps some demographic variables. Prescriptive analytics determine actions to be taken to make the future happen. Text analytics is an important and growing area of predictive analytics. Text analytics draws from a variety of disciplines, including linguistics, communication and language arts, experimental psychology, political discourse analysis, journalism, computer science, and statistics.
