Big Data to Have Major Impact on Infrastructure Strategies

The big data movement is revolutionizing how companies use information to inform strategies and operations, but it also creates major challenges in the data center. These difficulties can come out in almost every aspect of operations because big data is so disruptive. This holistic impact on the data center, however, is particularly noticeable in the infrastructure segment of operations.

3 Major Big Data Infrastructure Challenges

A recent Data Center Knowledge report explained that big data has begun having such a far-reaching impact on infrastructure that it is guiding the development of broad infrastructure strategies in the network and other segments of the data center. However, the clearest and most substantial impact is in storage, where big data is leading to new challenges in terms of both scale and performance.

Accessibility

Big data presents a broad infrastructure challenge because it depends on users who access the information from multiple sources. Furthermore, the data comes into the storage environment in structured and unstructured ways. The end result is a storage environment that must be much more accessible than traditional models. The news source said that cross referencing data and finding ways to connect key pieces of information is becoming much more important in light of big data’s rise. As a result, infrastructure models that are conducive to handling information from a diverse range of source systems is vital to operational success.

Flexibility

When it comes to big data, the flexibility and accessibility issues are closely tied to one another. The report explained that the combination of capacity and performance challenges created by big data force IT managers to establish an incredible flexible storage environment that must be adaptable and responsive. As a result, it must be possible to make major changes without a complete data migration. This needs to be accomplished without making performance sacrificing, an issue that presents added challenges considering that big data comes with a business intelligence layer that can have a major impact on storage functionality, particularly in terms of performance.

Scalability

According to Data Center Knowledge, organizations enter the big data realm when they start storing a petabyte or more of data. At this scale, the amount of data created can escalate quickly, and the aforementioned flexibility requirements become even more important. If IT managers must add capacity to the configuration in a hurry, a common need when dealing with big data, they must be able to scale capacity without having to shut other storage systems down.

At the same time, this scalability challenge adds onto itself because of the need to add more structure to information stored in big data archives. The report explained that the metadata burden alone in big data systems can be crippling because it creates incredible capacity demands.

These scalability concerns create an environment in which the costs associated with capacity requirements alone can be crippling.

Responding to Big Data Challenges

Cut costs when it is reasonable. IT managers facing big data challenges are going to need financial freedom to develop a storage architecture that can meet their needs. This means avoiding unnecessary hardware refreshes, avoiding expensive support warranties and ensuring the entire storage setup is reliable and resilient enough to function without problems, possibly even beyond equipment end-of-service-life dates.

Working with a third-party hardware maintenance and operating system support provider is one path to cutting support and hardware costs without taking on risk. Generally speaking, dedicated support providers are much less expensive than the OEM, but can offer the maintenance services that IT managers need to use equipment beyond the EOSL dates. As a result, organizations can avoid making premature hardware refreshes, extend the life of infrastructure and keep costs under control.