What is Business Analytics?Business analytics, a data management solution and business intelligence subset, refers to the use of methodologies such as data mining, predictive analytics, and statistical analysis in order to analyze and transform data into useful information, identify and anticipate trends and outcomes, and ultimately make smarter, data-driven business decisions.The main components of a typical business analytics dashboard include:Data Aggregation: prior to analysis, data must first be gathered, organized, and filtered, either through volunteered data or transactional recordsData Mining: data mining for business analytics sorts through large datasets using databases, statistics, and machine learning to identify trends and establish relationshipsAssociation and Sequence Identification: the identification of predictable actions that are performed in association with other actions or sequentially Text Mining: explores and organizes large, unstructured text datasets for the purpose of qualitative and quantitative analysisForecasting: analyzes historical data from a specific period in order to make informed estimates that are predictive in determining future events or behaviorsPredictive Analytics: predictive business analytics uses a variety of statistical techniques to create predictive models, which extract information from datasets, identify patterns, and provide a predictive score for an array of organizational outcomesOptimization: once trends have been identified and predictions have been made, businesses can engage simulation techniques to test out best-case scenariosData Visualization: provides visual representations such as charts and graphs for easy and quick data analysisThe essentials of business analytics are typically categorized as either descriptive analytics, which analyzes historical data to determine how a unit may respond to a set of variables; predictive analytics, which looks at historical data to determine the likelihood of particular future outcomes; or prescriptive analytics, the combination of the descriptive analytics process, which provides insight on what happened, and predictive analytics process, which provides insight on what might happen, providing a process by which users can anticipate what will happen, when it will happen, and why it will happen.