In order to take advantage of the revolution in data and analytics provided by the cloud, it’s important to understand why organizations are moving data to the cloud. I’ve outlined seven reasons for using the cloud for analytics.In order to take advantage of the revolution in data and analytics provided by the cloud, it’s important to understand why organizations are moving data to the cloud. I’ve outlined seven reasons for using the cloud for analytics.
1. Elasticity: Because the cloud allows for multi-tenancy and a shared underlying infrastructure across hundreds of thousands of clients, you can pay only for what you use and when you use it, making it cost-effective to support very spikey usage. Queries that might have taken hours or days can be accelerated to minutes or even seconds relatively seamlessly, simply by applying more and faster compute capacity during peak times. This is known as elasticity.
2. Experimentation: Since you’re only paying for the capacity you use, you can spin up and take down environments for experimentation quickly. Since long-term planning for capital expenditures is no longer necessary, innovation is faster and less expensive.
3. Agility: Because big capital decisions are deferred in the cloud, and computation is separated from physical server build-outs, it’s much faster to get started enabling increased agility for bringing solutions to the market or to the enterprise.
4. Gravitational: More and more data is now being created in the cloud. A key principle of data management is “go to where the data is”—if your data is already in the cloud, it makes perfect sense to process it there as well. Data thus creates a gravitational pull to the platforms and services that turn it into insight.
5. Focus on business: While many cloud platforms provide scalable virtualized servers in an Infrastructure as a Service (IaaS) model, increasing maturity in the market has led to explosive growth of Platform as a Service (PaaS) and Software as a Service (SaaS) models. With this shift, more and more low-level maintenance, monitoring and support are included in the service, allowing business owners interaction with increasingly less technical and more business-relevant services. That means more focus on business and less on server maintenance and patching, so scarce resources can work on differentiated business capabilities rather than commodity data center activities.
6. Continuity: Keeping fully operable failover servers and configurations for disaster recovery and business continuity is wasteful. Because it’s a cost-effective way to ensure that services can keep going after a disaster or accident, and an excellent way to distribute location-based risk, more companies are setting up mirrored environments in the cloud and seamlessly swapping over to the cloud when disaster strikes.
7. Workload balancing: Even if core systems are on-premise, having extra capacity in the cloud for peak periods can be an effective workload balancing strategy.
Sirius offers cloud analytics solutions and cloud migration to make moving to the cloud painless. Our team of experts will help you determine what makes sense for your organization by evaluating your current environment and considering your business objectives. Contact us to learn more.