With massive returns of predictive analytics in the 21st century, it has indeed become a need of each sector and industries are now heavily relying on predictive analytics to improve their decision making. This can further boost companies' profits along with offering ways to sustain their business for a long term. This study sheds some lights on the advantages of predictive analytics and enlightens how it has captured both academia and the corporate world with incredibly effective results. Based on recent literature, this study will analyze how this analytics is utilized vary from sector to sector such as detecting credit frauds in the financial sector, identifying potential diseases in health care, forecasting weather to save lives in public sector, predicting students' performance and grades in academic environment, examining recommendation engines in social media and analyzing patterns of consumers in retail sector, and increasing customer loyalty in telecommunication sector. Before building a predictive model, it is essential to identify the correct variables and then run a model using those variables. These variables will differ from industry to industry and case to case basis. Nevertheless, there are some challenges associated with these benefits. This study addresses the limitations of predictive analytics which is not limited to data quality, identification of correct variable and right methodology to experience maximum perks of predictive analytics.
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