The seventh edition of Forecasting and Predictive Analytics with ForecastX™ builds on the success of the previous editions. While a number of significant changes have been made in this edition, it remains a book about prediction methods for managers, forecasting practitioners, data scientists, and students aspiring to become business professionals and have a need to understand practical issues related to prediction in all its forms. The text is designed to lead through the most helpful techniques in any prediction effort. Most of the examples in the book are based on actual historical data and the techniques are explained as procedures that users may replicate with their own data. Highlights: 1. Four new chapters on predictive analytics, classification models, ensemble models and clustering and text mining 2. New topics such as trend, seasonal and cyclical components of a time series including new data, steps to obtain better forecasts, mean absolute percent error (MAPE), the ARIMA philosophy of modelling, etc. 3. Presents a broad-based survey of business forecasting methods, including subjective and objective approaches 4. Provides major updates to predictive analytics, chapter learning objectives, and ForecastX™ software 5. Delivers practical forecasting techniques and numerous real-world data sets