2012, Data Lakes and Data Preparation

Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

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AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. If you want to do the process in a low-code/no-code way, you can follow option C.

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Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML

AWS Machine Learning Blog

AUGUST 4, 2023

Train a recommendation model in SageMaker Studio using training data that was prepared using SageMaker Data Wrangler. The real-time inference call data is first passed to the SageMaker Data Wrangler container in the inference pipeline, where it is preprocessed and passed to the trained model for product recommendation.

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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML

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