As businesses strive to stay ahead of market trends, predicting future demand is no longer optional, it's a competitive necessity. This hands-on workshop addresses the practical challenges of processing massive datasets and building predictive models.

You will implement a time-series forecasting strategy using BigQuery Machine Learning to analyze historical patterns and predict future demand. Using the public NYC Citi Bike Trips dataset as our sandbox, you will learn how to:

• Explore and query large-scale public datasets directly in BigQuery.

• Train a forecasting model using the powerful ARIMA algorithm to handle parallel multi-item pipelines.

• Evaluate model performance using key statistical metrics like AIC to ensure accuracy.

• Generate batch predictions for the next 30 days of demand.

Join us to learn how to combine SQL-based machine learning with deterministic data analytics to make your applications smarter, predictive, and data-driven.