How to Use Machine Learning to Enrich Salesforce Data Using Amazon AppFlow With Amazon Sagemaker

Опубликовано 20 ноября 2020, 19:10

Amazon AppFlow is an integration service that helps you securely transfer data between SaaS applications (like Salesforce, Marketo, Slack) and AWS services (like Amazon S3, Amazon Redshift) in just a few clicks. In this video - learn how to use machine learning to enrich Salesforce data using Amazon AppFlow’s event-based data transfer capability with Amazon Sagemaker’s ML toolkit.

With AppFlow, you can run data flows at nearly any scale at the frequency you choose - on a schedule, in response to a business event, or on-demand. You can configure data transformation capabilities like filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

AppFlow automatically encrypts data in motion and allows users to restrict data from flowing over the public Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security threats.
Find the list of SaaS application integrations offered by AppFlow: aws.amazon.com/appflow/integra...
Link to the code used in demo: github.com/aws-samples/amazon-...

Learn more -
Amazon AppFlow: amzn.to/36RJzOC
Amazon Sagemaker: aws.amazon.com/sagemaker

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