Automated Forecasting at Scale with SAS Viya

Organizations today generate massive amounts of time-series data across thousands of products, regions, and departments. Managing and automating forecasts at this scale requires robust, modern pipelines that minimize manual effort while maintaining high accuracy. In this text-only course, you will learn the foundational concepts of automated forecasting and how to implement them. You will gain the skills to structure time-series data, configure automated modeling pipelines, and manage large-scale forecasting projects from start to finish. What you'll learn: - Understand core time-series concepts, including seasonality, trends, and hierarchical data structures. - Configure automated forecasting pipelines in SAS Viya to select the best-performing models automatically. - Apply statistical methods and modern machine learning algorithms to large-scale data sets. - Manage hierarchical reconciliation to ensure consistency across different organizational levels. - Automate pipeline execution and monitor forecast performance over time. - Analyze model diagnostics and selection criteria to optimize forecasting accuracy. The curriculum begins with essential forecasting terminology, data preparation principles, and foundational definitions. You will then progress through setting up pipelines, selecting models, and implementing automation strategies through clear, written explanations, step-by-step configuration workflows, and practical scenarios. This course is designed for beginner data analysts, planners, and aspiring forecasting specialists. No prior experience with SAS Viya or advanced statistics is required. Start reading today to build scalable, automated forecasting systems that drive smarter business decisions.