Learn how to use the power of Salesforce Data Cloud and Amazon SageMaker to query, import, and analyze your Data Cloud data …
Here are highlights from article Work with Data Cloud Data using Amazon SageMaker ML Capabilities
1. Viewing metadata in Amazon SageMaker:
– Connect Salesforce Data Cloud org to Amazon SageMaker
– View data lake objects, data model objects, fields, and data in fields
2. Querying data and metadata in Amazon SageMaker:
– Use SOQL to query data lake objects and data model objects
– View query results and create datasets for ML models
3. Preprocessing data in Amazon SageMaker Data Wrangler:
– Use built-in transforms or create custom transformations with code
– Common transforms include dropping columns or missing values, and one-hot encoding categorical variables
4. Analyzing data in Amazon SageMaker Data Wrangler:
– Generate visualizations and perform data analysis using built-in analyses
– Custom analyses can also be created using code
5. Using data in an ML model:
– Data from Data Wrangler flow can be used as input for ML models
– Import data into SageMaker Jupyter notebooks for implementation
You can read it here: https://sfdc.blog/aXJAD
Source from developer(dot)salesforce(dot)com