Allison Quinn

Discover how to architect scalable, intelligent analytics solutions using Amazon Redshift's multi-cluster capabilities and serverless offerings. Through real-world examples learn to design cost-effective analytics systems that meet enterprise demands for performance, security, and compliance.

Many SAP customers seek to modernize their existing analytics and reporting capabilities to adapt to changing business requirements. In this workshop, explore how extracting SAP order-to-cash data into a data lake and using AI/ML services can help organizations gain valuable insights while reducing manual effort.

Learn how organizations are combining SAP and non-SAP data in AWS data lakes to unlock business insights, improve real-time visibility, and make better decisions across their businesses.

By combining SAP data and non-SAP data in AWS data lakes, organizations are using AWS analytics, artificial intelligence, and machine learning services to drive new insights that support their business transformation. This chalk talk describes data extraction patterns for SAP on AWS, as well as common use cases that can help you get more value from SAP and other key enterprise data sources.