To fully embrace the benefits of the cloud, businesses have to distribute existing workloads across hybrid and/or multi-cloud environments. While the benefits of this digital transformation are undeniable, it’s not a process without its challenges.

This can be particularly true for firms with sprawling environments, perhaps as the result of mergers and acquisitions over the years, or those looking to get data in the right shape to be used for machine learning or AI.

How can businesses reconcile these problems at scale? And what are the specific steps to success when it comes to cloud consolidation?

In this episode, Rory speaks to Rajesh Naidu, SVP, chief architect, and head of data platform & data management at Expedia, to discuss the challenges of cloud migration and how converging workloads can help with AI adoption.

Read more:

• How Expedia Group used platform convergence to harness the efficiency of generative AI
• How to prepare and prioritize workloads for cloud migration
• “The tech guys want to move to the cloud, the finance people want the savings”: IT leaders feel ‘rushed’ to the cloud – here’s why slow and steady wins the race
• Consolidate to simplify application security: Why this is a business imperative
• Why 'shadow SaaS' is becoming a major blind spot for enterprise security teams
• Structured vs unstructured data management
• What is machine learning and why is it important?
• What is generative AI?