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What can a paper shredder teach us about big data?

Irshad Raihan looks through the similarities between shredders and data solutions

20Jul

The trusty paper shredder in my home office died last week. I’m in the market for a new one. Years ago, when I purchased “Shreddy” (of course, it had a name) after a brief conversation with a random store clerk, choices were few and information scarce. In fact, paper shredders weren’t really considered standard personal office equipment as they are today. Most good shredders were built for offices not homes. Back in the market more than a decade later, it’s clear that the search for a new shredder is going to be trickier than I had imagined.

A paper shredder is a lot like Big Data.

Being a 'bigdataholic', I couldn’t help liken my search to that of a CIO looking for a Big Data solution. Here’s why:

  1. Agility – Whether it’s the type of cut (micro cut wasn’t even an option back then) or what goes into the shredder (CDs, credit cards), agility is a selling point. Similarly, enterprises need to be agile about the expanding types of data they ingest into their data environment and the kind of analyses they run on the data, to stay current with competitive threats.
  2. Cost – Rather than use cheaper parts, some manufacturers are thinking creatively to reduce not just acquisition cost but total cost to the customer. Smart blades that adjust dynamically to the load, and smart motors that allow reduced down time between shredding sessions, are just two such innovations. Having more information readily available to compare models further helps customers make an optimal decision (certainly beats my random conversation with a store clerk who, I’m pretty sure, wasn’t even assigned to the small office products section).
  3. Capacity – Greater identity theft means that more paper needs to be shredded. At the same time, changing regulatory compliance standards requires more printed verbiage be mailed to customers. As a result, shredder motors have gotten more powerful, blades bigger, and waste baskets bulkier – just as the volume and velocity of data being ingested have grown exponentially. As a CIO, planning for this added capacity should be a key tenet of your big data strategy.
  4. Energy – Most new shredders tout energy consumption in their elevator pitch. In the old days, it really wasn’t a concern. Today’s CIOs look at energy as a way to reduce cost. Technologies, such as open source middleware, could help consolidate data silos and address server sprawl, optimizing energy consumption.
  5. Portability – Castors are pretty standard just as enterprises consider portability of their data across mobile, cloud and virtualized platforms, using Infrastructure-as-a-Service (OpenStack), Platform-as-a-Service (OpenShift), and software-defined storage.
  6. Scale – Most high quality shredders were built for office usage with long but infrequent sessions (scale-up) as opposed to home office usage which tends to spread the load across more frequent but shorter sessions (scale-out).
  7. Interoperability – Shredders today give you the option of using third party containers and even waster baskets in some cases. All the shredders of old were locked into a specific size and type of container.

Fortunately, unlike my shredder you don’t have to rip and replace your data management infrastructure and software to cope with evolving big data demands. And yes, if you have recommendations for a big data-esque paper shredder, please add a comment to this blog post – in return you shall receive a lifetime of good karma!

Sources

This article has been excerpted from a blog post published by the author in May 2014. The original blog post is available at http://redhatstorage.redhat.com/2014/06/24/what-can-a-paper-shredder-teach-us-about-big-data/

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