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Cloud

Key considerations when making a decision on a Cloud Data Warehouse

Making a decision on a cloud data warehouse is a big deal. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Scaling Service Mesh Across Clouds

In the traditional datacenter, distributed workloads simply existed across multiple datacenters. As businesses evolve their applications in the cloud native era, this degree of distribution scales as well. Workloads landing in multiple VPCs grow in commonality, and in many cases exist between cloud environments. In this Destination: Scale session, Cody De Arkland - Principal Technical Marketing Engineer, Service Mesh, Office of the CTO - shows how Kuma provides a method to connect these applications through its advanced multi-zone capabilities, and how this model enables global scale.

ThoughtSpot Analytics Cloud

Get consumer-grade analytics for your modern data stack. ThoughtSpot empowers everyone to create, consume, and operationalize data-driven insights. Our consumer-grade search and AI technology delivers true self-service analytics that anyone can use, while our developer-friendly platform ThoughtSpot Everywhere makes it easy to build interactive data apps that integrate with your existing cloud ecosystem.

Automating CDP Private Cloud Installations with Ansible

The introduction of CDP Public Cloud has dramatically reduced the time in which you can be up and running with Cloudera’s latest technologies, be it with containerised Data Warehouse, Machine Learning, Operational Database or Data Engineering experiences or the multi-purpose VM-based Data Hub style of deployment.

Quantifying the value of multi-cloud deployment strategies with CDP Public Cloud

In this article, I will be focusing on the contribution that a multi-cloud strategy has towards these value drivers, and address a question that I regularly get from clients: Is there a quantifiable benefit to a multi-cloud deployment? That question is typically being asked when I explain the ability to leverage container technology that offers a consistent deployment environment across multiple clouds and form factors (public, private, or hybrid cloud).

Automating and Governing AI over Production Data on Azure - MLOPs Live #14 w/Microsoft

Many enterprises today face numerous challenges around handling data for AI/ML. They find themselves having to manually extract datasets from a variety of sources, which wastes time and resources. In this session, we discuss end-to-end automation of the production pipeline and how to govern AI in an automated way. We touch upon setting up a feedback loop, generating explainable AI and doing all of this — at scale.

Reasons Why Cloud Migrations Fail & Ways to Succeed

Organizations are moving big data from on-premises to the cloud, using best-of-breed technologies like Databricks, Amazon EMR, Azure HDI, and Cloudera, to name a few. However, many cloud migrations fail. Why? And, how can you overcome the barriers and succeed? Join Chris Santiago, Director of Solution Engineering, as he describes the biggest pain points and how you can avoid them, and make your move to the cloud a success.

How a journey to the cloud helps a fintech leader deliver quality products

Securrency is a technology products company that delivers a complete suite of security and compliance tools. Their complex suite of financial technology needs to have top performance and security. Currently, Securrency has 50 developers working across their multiple software products and this software requires thorough testing. They have a dedicated QA team that does manual and automated testing.