We’re excited to announce the addition of Amazon SageMaker to the Data Lake Foundation on AWS Quick Start, developed by 47Lining.  The Quick Start provides customers with a get-started Data Lake in AWS that covers common use cases spanning ingest to visualization.  The new inclusion of SageMaker enables users to build and deploy machine learning models atop curated datasets that are managed within their Data Lake.

When launched in Demonstration mode, Step 8 of the Quick Start carries users through how EcommCo, a fictional company, leverages SageMaker to predict sales.

Amazon SageMaker uses transformed data (stored in an S3 bucket as curated datasets) to train a machine learning model. The model is then deployed into the Amazon SageMaker hosting service and used for real-time inferences.  SageMaker Notebooks make it easy to iterate on the model and visualize results.

To learn more about the Quick Start, including how to launch it in your own AWS Account and available credits and co-funding for qualified PoCs, visit AWS’ Solution Space: Data Lake Foundation on AWS

You can also view the Solution Brief, or the Quick Start Deployment Guide.

Contact us to discuss how 47Lining can help you apply agile analytics, machine learning and AI atop your enterprise data lake.