Data analytics leaders in companies of all sizes know that fast, modern analytics is the difference between thriving and barely surviving. In a world where data is becoming more distributed across private data centers, public clouds, and even the network edge, that goal is hard to reach—and neither legacy platforms nor most cloud data warehouses are equipped to help.
The Gartner Top Strategic Technical Trends for 2021 report suggests that the distributed cloud model will emerge to address this explosion of data growth outside the data center. However, to take full advantage of the benefits that distributed clouds offer, we must rethink our approach to how data is managed, processed, and analyzed in such a heterogeneous, geographically separated, and logically interconnected environment.
In this session, you'll learn:
- Why the most useful data management and analytics applications for distributed clouds will be based on Kubernetes-based microservices and managed by a unified control plane
- How cloud-native benefits like elasticity can extend to private data centers and out to the network edge as well
- Yellowbrick's vision for bringing Kubernetes-based data warehousing to distributed clouds