Analytics refers to the process of creating mathematical and statistical models to analyze data, uncover patterns, and support decision-making. These models help organizations interpret complex data sets, predict future trends, and optimize strategies.​ There are various types of Analytical Models: Descriptive Models: These models summarize historical data to identify patterns and trends, and what had happened in the past to predict the future. A whole subject of actuarial science is based on that framework and uses the Econometric modeling for building either a times series or a cross sectional data based forecasts. Then there are also Diagnostic Models that get into deeper problems solving or behavior pattern predictability and consist of Factor or Eigen analysis such as PCA methodology Predictive Models: Utilizing statistical techniques and machine learning algorithms, and econometric algorithms, to forecast future probabilities and trends, to what can happen in the future with some level of probability Lastly there are Prescriptive Models: Building upon predictive insights, these models recommend specific actions to achieve desired outcomes, answering, "What should we do? After we know what the predictive path is outlines. Key Components of Analytical Modeling: Data Collection and Preparation: Gathering relevant data from various sources and ensuring its quality through cleaning and preprocessing.​