The explosive growth of big data projects is no coincidence, and the same applies to data center colocation. A common IT use case for data center colocation is this: you can rapidly scale your data center at only 20% of the cost of building your own infrastructure. You may also have the option of a pay-as-you-go model, paying only for the resources your business actually uses. This is extremely attractive for IT departments that must continually practice frugality while rapidly scaling up or down according to business demands.
However, in the emerging IT industry, there is another use case for data center colocation: Have you considered implementing colocation for big data analytics and high-performance computing?
Can your big data needs be met by low-end business analytics, different from relational databases or data marts, that your enterprise might already have? The answer is likely no. If you find that your business requires near-real-time analytics and HPC-level processing to answer highly complex questions, you will discover that you lack the computational resources and IT skills needed to run these applications in-house.
This is where a data center colocation provider with HPC cluster computing and specialized expertise in managing big data workloads comes into play. A colocation provider with significant big data expertise can offer a fast time-to-market for IT solutions because it addresses the emerging information needs of the end business. It may also tackle another IT dilemma: boatfuls of unstructured and (worse) unclassified big data can potentially be brought under control through deduplication, archiving, and storage provided by colocation services.
Do these strategies make sense?
In the short term, they present a fairly attractive option due to low startup costs and rapid results.
Other risk factors that IT must pay attention to regarding big data colocation facility providers include financial stability. The provider must deliver value that the IT department cannot provide in-house, while also having the capability to meet standards for IT security, governance, regulatory compliance, and intellectual property. Especially if your enterprise is a small or medium-sized business (SMB), big data colocation may be the only way you can ever compete directly with larger rivals in business analytics.
If your enterprise is a large organization, you should perhaps consider an in-house deployment for big data analytics from a long-term perspective. The reason is this: mission-critical big data analytics will be far too important in the future to be completely outsourced to an external provider. To meet current big data needs while planning for the future, some enterprises initially choose to conduct big data analytics with a value-added colocation provider, with a long-term strategy of building an analytics-capable team internally.
Whatever your enterprise’s big data strategy may be, the following three key points should be fully taken into account when formulating your strategy:
Find a colocation provider that understands your business direction, especially if you plan to eventually migrate big data applications in-house.
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