Get a firsthand look at Einstein Studio with AWS SageMaker and see how it allows you to leverage data within Data Cloud to train a model and ultimately score live data back within Data Cloud.
As the engagement platform of choice for many sales, marketing, and customer service teams, Salesforce is home to a massive amount of valuable customer data. By leveraging the data you connect with Salesforce Data Cloud to train your predictive models in Amazon SageMaker, you can maximize the value of your data and enable predictive and prescriptive insights your team can trust and take action on.
In this demo, we walk you through using Einstein Studio to leverage Salesforce Data Cloud data within Amazon SageMaker and bring that information back into Salesforce to create actionability.
It all starts in Amazon SageMaker Studio, where we’ll create a project and select the model deployment for Salesforce, then pull in some data from Data Cloud using Data Wrangler and the standard Salesforce Data Cloud connector. Then, we’ll show you how to make some additional adjustments in SageMaker Studio, run the full notebook, and deploy the model.
You’ll also get a look at Einstein Studio within Salesforce Data Cloud and see how we create a model there, set the endpoint, variables, and show where we want the model output to be written (e.g., in a new Salesforce object). We’ll also show you the data in Data Explorer and discuss potential ways the data can be used, now that it exists within the Salesforce platform.
Looking for more help? Atrium is a consulting firm focused on delivering data-driven CRM strategy by applying the principles of data, analytics, and AI. We’re partners with Salesforce, AWS, and other leading cloud platforms. Get in touch for more information.
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