Moving big data to the cloud
Companies that are succeeding are most likely leveraging big data. Implementing it can be a complicated technical process, big data has benefits but in order to utilize big data, enterprises have to be able to store and process it, and that is why most of the companies move their data to the cloud. State of the Cloud Survey pointed out that 95% of the respondents are using cloud services. 89% use a public cloud, 72% use a private cloud and 67% use a hybrid solution.
Using a cloud service to move and store your big data has many advantages that we have discussed in former articles, even though, some businesses still hesitate to make the transition or full transition because they think the risks are too high. Companies need to know how to handle these types of moves. The following practices will help.
Prepare the management for transferring big data to the cloud
Getting key people behind the move is imperative. Every C-level executive should write down their list of advantages of combining big data with cloud services. For example, CIOs and CHROs could use data platforms for data discovery and integration, which represent a powerful tool for the business. They will be able to get answers they never were able to see in the past, such as why are products being returned or what influences employee satisfaction. Cloud advocates need to see how the implementation will help the company be more agile in responding to opportunities and challenges, as well as improving customer engagement and loyalty.
Big data applications are divided into three broad categories: storage, processing, and development. Many big data clouds are configured to support a combination of two or all three types. The best big data clouds will simplify the deployment plan and configuration process. But companies still can’t predict exactly what the mix of workloads they’ll need to use in the future. They should instead invest in the right category of big data, the one they use the most, and that will represent the foundation for change.
Before deciding what to do, companies need to do a sophisticated analysis of the existing data applications and workloads to determine which type of cloud is more suitable to be implemented. Companies need to identify all the data, analytics, cloud service layers, and the platform necessary to support the estimated workload. Enterprises also need to evaluate and test various cloud deployments and service models and then decide which is the best solution for their needs.
Privacy, security and compliance requirements
Big data cloud is a complicated thing to control and keep an eye on. Where safety is a primary factor to consider, there is no reason to be concerned. In fact, the security vulnerabilities in big data cloud might have more to do with the unfamiliar platforms and the necessity to combine and harmonize distinct legacy security systems. Generally speaking, companies will face the need to adapt existing controls in order to fit the new platforms of data in the cloud. So, launching new controls that address the data domains managed in the cloud is definitely a must.
Ready to use!
The readiness of the system will depend on the uses and the applications being changed. Providing a basis for reorganizing data management and IT analytic processes. In this way, the system will be able to support big data cloud initiatives. For example, firms could implement continuous deployment of big data applications, because the traditional development cycles are no longer applicable.
Companies are starting to understand the benefits of moving their big data to the cloud. While some are still hesitant due to misconceptions and groundless uncertain, learning about what to do and expect from the change could dispel those uncertainties. The sooner companies adopt this strategy, the sooner they will enjoy big data tools and benefits. Today, effectively utilizing big data analytics almost always requires a move to the cloud.
Are there any concerns that cross your mind? Let me know in the section below.
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