Background

ShopRunner ingests product, logistic, and behavioral data from more than 100 retailers to provide highly personalized and customized experiences for its shoppers. It needs high-quality, fast, and efficient data management.

To automate its data pipelines, ShopRunner uses Databricks Unified Analytics Platform on Amazon Web Services (AWS). Now ShopRunner can improve its product recommendations with better machine learning results.

Watch to learn how to:

• Enhance the strength of product recommendations using Apache Spark
  
  
• Share custom libraries and notebooks for better collaboration
  
  
• Use Amazon SageMaker to deploy your machine learning models
  
  
• Gain greater insights with self-service access to data and data pipeline management
  
  
• Ingest raw data from structured and unstructured file types
  
  

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