Paige Roberts

One of the reasons databases can be containerized is that many now have the capability to function with data and compute separately to accommodate shared cloud storage architectures.

More and more organizations who went all-in on cloud early are now finding that some analytics workloads are better on-premises and are pulling those workloads back.

As you understand what AI, ML, predictive and prescriptive analytics are, you will see what analytics you need in your organization and how each type can help you.

A unified analytics data warehouse based on a massively scalable architecture with a broad set of analytical functions helps enable the most demanding modern business applications.

Instead of focusing on where the data lives, focus on making the analytics experience as smooth as possible for everyone in your organization.