Business analytics is the process of transforming the raw data businesses collect on their customers, performance, and the marketplace into applicable models so they can make informed decisions. It is an iterative, systematic, and statistical exploration of a company’s data to improve its operation or profitability. Business analytics is divided into three primary categories: descriptive, predictive, and prescriptive. Descriptive analytics uses historical data to answer the questions “what happened” or “what is happening.” Predictive analytics uses historical data to try to predict future outcomes. Prescriptive analytics combines the other two. It uses historical data to offer insights into what happened and then predict what will happen when it occurs and why. For example, a Las Vegas casino with an extensive buffet can use prescriptive analytics to determine when the most customers will want to eat and when staff should start preparing the food to have it ready on time.

Business analytics uses tools to transform raw business data into valuable reports. Businesses today gather vast quantities of data. Data aggregation or collection filters and organizes it. Data mining, sequence identification, and text mining are all business analytics tools that use artificial intelligence and machine learning to identify trends, sequences, and relationships within large data sets. Forecasting or descriptive analytics takes filtered data from a specific period to make informed estimates about future events. For example, a clothing manufacturer may want to know seasonal purchasing trends over the past five years. Once enough descriptive analytics are done, predictive analytics applies statistical techniques to predict what is likely to happen. Optimization allows businesses to test those predictive models in different scenarios. Finally, visualization tools like graphs and charts help people understand the reports and extract new insights.