Every business possesses data, from customer and transaction information to manufacturing and shipping statistics. The vital aspect is to figure out how to use it to enhance the business’s future. One compelling strategy for companies is to use predictive analytics. This includes combing through previous information to derive models and analyses that can help predict future outcomes. Predictive analytics applies to all facets of an organization. It can help determine what customers need and don’t need and help a business augment efficiency. It can help a company spot and deal with issues when they occur. What is Predictive Analytics? To be honest and straightforward, predictive analytics makes predictions about future outcomes by analyzing historical data together with data mining techniques, statistical modelling, and machine learning. As a part of advanced analytics, predictive analytics can help businesses discover patterns within data sets and identify risks, opportunities, and tendencies. It is associated with big data and data science. With huge volumes of data hovering across transactional databases, images, videos, sensors, log files, etc., we must embrace them to derive value. Here’s where data professionals employ deep learning and machine learning algorithms to analyze the data and drive predictions. These algorithms include neural networks, linear, and non-linear progression, decision trees, and support vector machines. Surprisingly, the insights acquired using predictive analytics can be further employed within prescriptive analytics to decide future action outcomes.