Bigger is better. It’s a lesson that’s drilled into us from childhood -- whoever ends up with the most toys wins. Everywhere you look there are people, groups or even entire countries trying to be the biggest one thing or another. Biggest building, biggest car, biggest ball of twine -- they're all out there. You ate the biggest steak on the menu? You're awesome -- here’s your big tee shirt.

Bigger is Just Bigger

The modern data center is not immune to the Bigger is Better Syndrome (BIBS). Big servers, big networks and, most of all, big data. Sorry, that should be Big Data with a capital “B” and “D” because Big Data is its own Big Thing and clearly of Big Importance. Everything is about Big Data these days -- how to store it, how to make it accessible, how to manage it, how to secure it and make more of it. And don't forget how to get it back in case you lose it.

Companies talk about the petabytes they've accumulated as if it were at badge of honor -- we have more data than them, so clearly we must be doing something better. A true symptom of BIBS is when a firm rolls out some poor IT Director to explain the yearlong process he or she went through to test the latest storage technology and assemble an infrastructure capable of supporting the latest generation of applications that spew data at rates that were unimaginable only a couple of years ago.

Finding the Needle in the Haystack

The problem with all of this is that while the systems can handle the load from a basic storage perspective, finding data within the pile is becoming more difficult every month. Basic business practices such as e-Discovery and compliance, which were hard to begin with, are now becoming next to impossible because of the breadth and depth of data that must be analyzed. The haystack has gotten bigger and the needles that much harder to find.

Let’s not confuse Big Data analytics with just plain having a lot of storage. Breakthroughs on the analytics side have been some of the more interesting developments during the last couple of years. It’s encouraging to see startups like DataGravity taking a fresh look at storage and understanding that there is indeed a difference between data and information and that the latter often gets lost within the former. Information is stored because it has value.

That value is lost when the information in question cannot be found or can only be dug up after spending lots of hours and lots of dollars looking for it. A common complaint in the not-so-distant past was “there’s not enough data to make a decision.” That has quickly changed to “there’s too much data to make a decision.” Analytics has huge potential value. Sitting on huge amounts of data for lack of another option is a huge potential waste.