Customers are migrating their analytics, data processing (ETL), and data science workloads running on Apache Hadoop, Spark, and data warehouse appliances from on-premises deployments to Amazon Web Services in order to save costs, increase availability, and improve performance.
Bruno Faria explains how to identify the components and workflows in your current environment and shares best practices to migrate these workloads to AWS.
This session is sponsored by Amazon Web Services.
Bruno Faria is a senior EMR solutions architect at Amazon Web Services. He spends his time helping customers understand big data application architectures and integration approaches for running those applications in Amazon Web Services.
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