
Amazon Redshift ML now enables users to perform time series forecasting using Amazon Forecast through simple SQL commands, allowing data analysts to create, train, and deploy forecasting models for business applications like demand prediction and resource planning without learning new tools.


<div><p>This article demonstrates how to perform time series forecasting using Amazon Redshift ML integrated with Amazon Forecast through simple SQL commands.</p><ul><li>Redshift ML enables SQL-based creation and training of forecasting models without new tools</li><li>Amazon Forecast automatically trains multiple ML algorithms on historical time series data</li><li>Two use cases demonstrated: electricity consumption forecasting and bike sharing rental predictions</li><li>Models support target time series data and related time series features</li><li>Forecast results exported to S3 and loaded into Redshift tables for analysis</li><li>No additional Redshift costs; users pay only associated Forecast service fees</li><li>Training takes 10-15 minutes setup plus asynchronous model training by Forecast</li></ul><p>Redshift ML simplifies time series forecasting for business planning, resource optimization, and demand prediction without requiring ML expertise or complex data pipelines.</p></div>


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