Time series models make forecasts by learning from history, using data that ranges from individual transactions to data collected daily, weekly, or over a longer term. But turning that data into accurate predictions can be a very complicated process, involving a balance between finding the best data sources and creating the best features from them. It also means incorporating a deep understanding of your business.
Knowing how to approach time series projects is crucial for organizations in their quest to become AI-driven. Our ebook, Next-Generation Time Series: Forecasting for the Real-World, Not the Ideal World, looks at the many ways organizations are tackling some of the most valuable, yet difficult, time series problems.