Hybrid Cloud and the Evolution of Analytics

2 Minute Read

Organizations are moving to hybrid cloud architectures – both between on-premises and cloud systems, and among cloud platforms – to help ensure their business operations and analytics can keep up with real-time events.

Hybrid Cloud and the Evolution of AnalyticsWith a newfound focus on real-time event data, data-driven companies have the opportunity to take an unprecedented advantage of event-level information. Organizations can take streams of real-time information and gain insights on internal operations, partners, supply chains, customers, and market trends like never before. These real-time events have great value, but that value needs to be capitalized upon and linked to an organization’s business operations quickly, so operators can truly take advantage.

Gone are the days when competitive enterprises could take as many as 12-18 months to deliver an IT project supporting new data initiatives. Enterprises need to ingest, process, and organize information at the pace of their business rather than at the pace their IT infrastructures, such as on-premises data centers, allow. The addition of cloud-based resources to the mix of deployment options provides the ability to quickly and nimbly provision technical resources for storage, processing, and analysis. Now, organizations can flexibly select infrastructure to use. The infrastructure options are:

  • On-premises data centers to run bare-metal installations if capacity allows
  • Private cloud deployments to utilize existing infrastructure but gain elasticity and flexibility of provisioning
  • Public cloud resources, such as Amazon AWS, Microsoft Azure, or Google Cloud Platform environments to quickly gain access to resources and utilize them on an as-needed basis
  • Hybrid combinations of the above

This has given deployments that include cloud-based resources an impressive leg up on legacy, bare-metal-only deployments. Now, organizations can take advantage of a flexible and elastic process that allows them to try, evaluate, and validate technology configurations with reduced risk of establishing the wrong architecture. This deployment style has spread from public resources to private data centers where virtual private cloud deployments serve the needs of organizations with sensitive data.

With this move toward cloud-based resources, organizations are also choosing to implement architectures that require less “friction” as part of the data acquisition and process components. Data lake architectures, with their flexible schema-on-read approach as opposed to the more cumbersome schema-on-write methodology of legacy analytical environments, offer that level of flexibility. When this flexibility is coupled with the elasticity of being able to implement on-premises, cloud-based, or a combination in a hybrid, this means the underlying architecture no longer constrains real-time events.

To learn more about the benefits of hybrid cloud, visit our “Hybrid Cloud Integration” solutions page, or schedule a demo to speak with a Striim technologist regarding your hybrid cloud integration use case.