Big Data has arisen as a significant area of interest of study and exploration among specialists and academics. Big data is a great source of information from the frameworks to opposite end-clients. In fact, with the big data spread and constant increase logical systems assume more significant role and inevitability in organizations. So, Predictive analytics is used to find the relations and forms in the data so as to predict future by observing the past and making good decisions. In statistical and analytical techniques the term substantially used is predictive analytics. This term is drawn from Optimization techniques, database techniques, statistics and machine learning. It has been derived from classical statistics. Using the models of predictive analytics, the future events and behaviour of variables can be predicted. The predictive analytics have many advantges. A scoring technique is provided for predictive analytics models. A higher score shows the higher probability of occurrence of an event and a lower score demonstrates the lower probability of occurrence of an event. To find solution for various commercial and technical problems, the past and transactional data patterns are broken by these models. The predictive analytics models have dominated due to the growth of attention in the decision support solutions. This paper, presents applications and techniques of predictive analytics is reviewed. Application of Machine learning Algorithms such as Regression Modelling and ARIMA model.ARIMA (Autoregressive Integrated Moving Average) model and Regression model are applied for Gold price forecasting

Big data technology, predictive analytics, Machine Learning, Techniques of predictive analytics