Automated Data and Analytics Workload Modernization
Webinar Speaker: Markum Reed, Research Director for Data Management, TDWI
Panel Speaker: Veena Vasudevan, Senior Big Data Solutions Architect, AWS
Panel Speaker: Samiksha Saraf, Principal Cloud Architect, Impetus
Date: Thursday, November 3, 2022
Time: 12:00 p.m. PT, 3:00 p.m. ET
Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs.
You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.
It is important for organizations to be able to accelerate code transformation without increasing risk and productionize data workloads at the highest standards possible.
Join us to learn the following:
- How serverless architecture addresses productionization concerns
- Overview of Amazon EMR and Amazon EMR Serverless along with the latest features
- A demo of automated and intelligent transformation of on-premises workloads
- Meeting SLAs and seamlessly transitioning migrated workloads into production
Senior Big Data Solutions Architect
Veena Vasudevan is a senior partner solutions architect, analytics specialist at AWS. She has been working in AWS for the past six years as a subject matter expert on Amazon EMR. She helps AWS partners and customers migrate their Hadoop/big data analytical workloads from on-premises and other cloud providers to AWS. As a global Amazon EMR acceleration lead, she creates and delivers enablements focused on big data modernization and best practices to AWS partners worldwide.
Principal Cloud Architect
As principal cloud architect, Samiksha works closely with customers in driving technology plans to enable strategic business initiatives. With 17+ years of experience, she brings deep expertise in architecting and implementing large-scale enterprise systems to address complex business problems.