As the amount of data coming in to business systems continues to grow at an exponential pace, businesses must be prepared to capitalize on the value that data has to offer if they wish to be successful in the modern business era. That being said, these businesses can't expect to deploy the big data projects of tomorrow on the IT systems to today. In order to keep up with data growth and enable advanced analytics projects, organizations need cutting-edge IT solutions that can enable growth, performance and efficiency.
Cloud computing environments can help make these kinds of advanced solutions a reality. In this post, we'll explore some of the reasons that cloud computing is such a good fit for big data projects, and also touch on what kind of considerations should go into designing the ideal cloud environment for big data.
Advantages of big data in the cloud
Of course, the ability to scale systems quickly is a key benefit of cloud in any circumstance, but it becomes particularly important when big data is involved. As the amount of data coming in to business applications continues to increase, it becomes less and less practical for organizations to rely solely on on-premises systems to support that data.
The amount of capital investment required to increase data capacity for an on-premises environment—along with the time it would take to plan and complete that investment—should be more than enough incentive for organizations interested in big data projects to start considering cloud to support those projects. The money they save on storage alone could open up an important source of new funding for innovative analytics technology.
In addition, organizations also have the option to pair the scalability and cost benefits of cloud environments with the reliability and security benefits of dedicated on-premises systems. This kind of hybrid cloud arrangement can be extremely beneficial for big data projects, but only if the hybrid environment is properly designed to meet the needs of the business and its data.
Designing the right cloud environment for big data
Any cloud environment that's going to handle big data will logically require high performance. Since the amounts of data moving to and from the cloud are so large, a cloud environment that isn't up to the performance challenge could result in serious delays, which in turn will make it impossible for the business to derive real-time insight from their big data. This is especially important in the case of hybrid cloud environments, where data needs to be moved frequently in order to make the most of the different elements of the hybrid cloud.
Also, it's important to think about what kind of analytics workloads make sense to deploy in the cloud, and which ones don't. For instance, if the majority of your data is still being generated on premises, it may make sense for you to deploy analytics applications where the data is, and use cloud primarily for proofs of concept and testing. The great thing about big data in the cloud is that it doesn't have to be all or nothing, and for most, it won't be. In the end, designing the right cloud environment for your big data needs is all about looking at the unique aspects of your business and what you're trying to accomplish with big data. Only then can you build a cloud environment that's properly designed to meet those goals.
To get started, sign up for a free RightCloud assessment from Cima Solutions Group. We'll help you review your business' existing workloads, talk about what you'd like to do with big data, and then help you build your ideal cloud environment. We look forward to helping you capitalize on everything cloud can offer in the world of big data!