Hybrid cloud strategy is the future of enterprises. As vital as the cloud can be to improving the economics and agility of Enterprise Data Warehouse (EDW) provisioning, most enterprises will need some on-premises capability as well to satisfy requirements for performance, privacy, and security, for both them and their customers. In addition, a lot of enterprises already have a substantial investment in on-premises hardware, and it makes no sense to just scrap on-premises deployment and move all data and workloads to the cloud.
Every successful enterprise needs a secure and scalable infrastructure. If you need to scale your infrastructure up and down based on changing workloads. Cloud deployment, with its ease of adding and subtracting compute capability is the key.
Most enterprises today are forced to deal with sensitive data that is important to store and analyze. An on-premises deployment model helps enterprises retain such data with full control and authority, something not possible in any cloud deployment model. When handling sensitive data that you feel should be guarded, yet rapidly accessible, on-premises deployment makes the most sense.
No one size fits all.
A combination of data storage and management strategies provide optimum business benefits.
Hybrid deployment is the way forward.
“The trending hybrid architectures will allow organizations to maintain control of sensitive data while still meeting soaring demands for more capacity and increased computing capabilities closer to the consumer.” (Jan 2020, source).
The Need for Hybrid
When enterprises seek to remain competitive, they often look to maximize analytic performance and responsiveness. By adapting their business to run on a mix of on-premises and cloud(s), enterprises enjoy the advantages of both these forms of deployments.
For example, by adopting a hybrid cloud approach, enterprises can mitigate costs by running historic analytics on-premises without moving the data, and data analysis on current, business-critical data in the clouds. Public cloud resources can be used to handle sudden spikes in demand, while on-premises resources can operate on more steady, predictable workloads that rarely change.
“According to Gartner research (2020), ‘By 2025, 85% of infrastructure strategies will integrate on-premises, colocation, cloud, and edge delivery options, compared with 20% in 2020.” (Sep 2020, source)
The advantages of a hybrid environment
Consider some of the key advantages a hybrid data analytics architecture strategy brings to an enterprise:
- Better workload management: A hybrid cloud approach helps you manage changing workloads in a more efficient manner. Workloads that are subjected to constant change can fit in an elastically scalable analytics data warehouse in the public clouds, while workloads that are more stable can be handled on-premises on industry standard hardware inside the enterprise’s own data center.
- Better data control: A hybrid cloud strategy gives businesses much-needed control over data that is both critical and sensitive. Rather than relying solely on a cloud provider, businesses can tailor their architecture to meet their specific security needs. Enterprises can keep full control of essential applications that rely on immediate access to sensitive data.
- Better cost control: As businesses evolve and their data management requirements increase, it may be easier to scale cloud resources to handle increases in data and changing workloads. Cloud practices can automatically handle sudden changes in demand without compromising on performance and efficiency. Stable workloads can be run on-premises on existing hardware, which reduces the need for comparatively expensive pay-per-use compute resources on the cloud.
- Better management of change: When an enterprise data warehouse facilitates hybrid cloud deployment, you can function with the freedom to adapt to change. For example, if your company has a mandate to move analytics to the cloud, you need not move all your data to the clouds at once. See what works best for your enterprise by mixing and matching your workloads and if moving to the clouds is the right path, then transfer your data to the clouds at your own pace.
- Freedom from vendor lock-in: Most cloud analytics databases lack an on-premises offering. Many offer their data warehouse running on one public cloud provider only, locking customers on that cloud vendor to store, control, and operate their data. Some cloud databases even charge “egress fees” for you to move your data. That data is yours, and a good data analytics database has the flexibility and freedom of deployment to let you make decisions about your analytics.
A data warehouse technology that supports a hybrid cloud strategy has become increasingly vital as the business landscape changes. It allows you to match your actual data workloads to the public cloud, private cloud, or on-premises infrastructures that are most suited for the job.
An Enterprise Data Warehouse that supports hybrid cloud deployment allows you to keep control of your sensitive and business-critical data while also allowing you to improve on your data analytics costs, and future-proof your analytics implementation.