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.
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Senior Research Director - Data Management,
Senior Big Data Solutions Architect,
Principal Cloud Architect,
Impetus Technologies Inc.