Simulations model the behavior of a system, while predictive analytics uses models for insights into the future. Simulation and predictive analytics are related because both require models. Furthermore, complex data analysis using machine learning techniques is becoming simpler thanks to platforms such as Microsoft’s Project Bonsai, H2O.ai’s automatic machine learning, and Pathmind AI.Īs predictive analytics software increases in popularity, the more stored data is analyzed, and the more its value is realized. User interfaces are also improving and making predictive analytics tools more accessible and understandable. Due to data management advances, the increasing size and complexity of data sets is not a limiting factor.Įase-of-use - Continuing advances in data storage and processing reduce costs and increase access to quick and complex analytics. Rapidly growing data sets - Data collection is widespread and growing because storage costs are low, and the activities of people and devices are increasingly online. Predictive analytics is increasingly common thanks to two trends in computing: Supply Chain – for design, planning, sourcing optimization, inventory management, transportation planning, risk management - see anyLogistix.Business Processes – for optimization, investment analysis, impact analysis, and more.Oil & Gas – for operations planning, field production optimization, storage management, and more.Healthcare – in clinical trials, predictive scheduling systems, pharmaceutical market analysis, and more.Manufacturing – to optimize production processes, improve maintenance scheduling, plan inventory, and more.Predictive analytics is valuable wherever there is data. In general, the insights provided by predictive analytics help optimize processes and manage risks. Or, in another example, modern Android phones have an adaptive battery system that prioritizes battery power for the most-used applications. In a consumer credit system, for example, each of us is given a credit score that represents the probability we will repay a loan. Almost everyone is subject to and may benefit from predictive analytics. Practitioners analyze past events with statistical algorithms and machine learning techniques to produce probabilities and predictions for systems in the future. Predictive analytics is about making forecasts based on historical data. In this article, we introduce the broad field of predictive analytics, its connection with machine learning, and how simulation works as a predictive analytics technology.
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