Posted On: Oct 3, 2022
Amazon SageMaker Canvas now supports quicker set up of time-series forecasting models with simplified administration of required permissions. SageMaker Canvas is a visual point-and-click service that enables business analysts to generate accurate machine learning (ML) models for insights and predictions on their own — without requiring any machine learning experience or having to write a single line of code.
SageMaker Canvas supports a number of use cases, including time-series forecasting used for inventory management in retail, demand planning in manufacturing, workforce and guest planning in travel and hospitality, revenue prediction in finance, and many other functions where highly-accurate forecasts are important. As an example, time-series forecasting allows retailers to predict future sales demand and plan for inventory levels, logistics, and marketing campaigns. Time-series forecasting models in SageMaker Canvas use advanced technologies such as Amazon Forecast to ensemble model statistical and machine learning algorithms, and deliver highly accurate forecasts.
Previously, setting up time-series forecasting models in Canvas required IT administrators to manually configure Identity and Access Management (IAM) policies in the AWS management console and add explicit permissions for time-series forecasting. Starting today, time-series forecasting permissions are enabled by default making it intuitive for IT administrators while setting up a SageMaker domain. This allows Canvas users to quickly set up time-series forecasting models, train these models, and generate predictions to achieve effective business outcomes.