The challenge
The client needed to move its data and machine learning estate from AWS to Azure, including a substantial set of pipelines and tables.
Software • Azure
Machine Learning
AWS to Azure Migration of Data and Machine Learning Workloads
Migrated data pipelines and machine learning workloads from AWS to Microsoft Azure to consolidate on a single cloud platform.
Ref: CSWON105859
Video story · 1:01
The approach
Kumulus prepared the data, rebuilt and validated machine learning models on Microsoft Azure, and carried out technical validation of the migrated workloads.
The outcome
Consolidated the client’s data and machine-learning workloads on Azure, giving it a more scalable and governed foundation for cost control and future advanced analytics and AI. The migrated estate comprised approximately 98 transformation notebooks, 48 active pipelines, 12 stored procedures, 95 Logic Apps, 8 Azure Functions, 48 relational databases with 462 tables and 1,065 analytical views.
Built on Azure
Powered by
Could this work for your organisation?
The AI Audit shows where data and AI will deliver measurable value for you first.