Sponsored by: AWS | Learn how to Manage Cost for Data and AI Workloads with Databricks on AWS

Enterprise data is often siloed and disconnected, and many data solutions can be technically complex, which can hamper productivity and increase operational costs. Databricks on AWS helps you manage costs of data and AI workload costs using focusing on three key areas: Global Usage Tracking, Measuring Value, and Governance. We will discuss techniques for monitoring usage across various dimensions to identify cost inefficiencies, methods for quantifying the return on investment of data projects, and governance practices that maximize the effectiveness of Centers of Excellence (CoEs) in enforcing cost.Deep dive into best practices on how to efficiently deploy these workloads-Explore how serverless use cases can reduce TCO-Optimize classic compute with spot fleet and Graviton-Scale to zero for LLM serving-How to build observability and monitoring-Conduct a Well-Architected Framework review