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As time moves forward, the world accumulates data. What are the challenges and how do we make use of big data?
Big Data has been a problem for decades. As companies generate more of it, data centers are tasked with the challenge of managing it, storing it and providing access to it all in a timely manner. Are modern data centers up to the task?
The Challenge of Data Storage
Every company, every individual is continually generating new data that must be saved. The problem is, the cost of storage isn’t going down as fast as we’d hoped.
Solid state drives are faster in terms of processing speed but they too cost too much. A cheaper alternative would be to use hybrid drives in order to save money with in a data center, but even this hardware has limited capabilities. So what’s the solution?
Phase Out Old Data
Some experts are suggesting companies ditch their old, often useless data, especially if they aren’t using it for anything specific. Other companies may move to outsource data storage to cloud providers and such but even that approach has its limitations. Fact is, SDDs and HDDs have limits to what they can accomplish. Infrastructure will just have to keep up with the ever increasing demand big data poses. Furthermore, how do companies go about deciding which data gets dumped?
There’s no telling what information companies might need in the future, after-all, a lot of decision future makings depend on what was decided in the past. So where does this leave us? Dealing with Big Data still remains a huge challenge. As data centers upgrade existing infrastructure they will have to compensate for the future. This means investing in scalable storage systems all while keeping up with new efficiency standards.
Come to think of it, it’s amazing our industry is doing this well considering data generation ceases to slow in any way shape or form. The cost of SDDs will come down eventually, and cloud computing structure will enable us to keep up with big data. But until we create some crazy new technology to address the problems of big data entirely, storage and analysis will continue to be a challenge.