|By Adrian Bridgwater||
|November 16, 2013 02:00 PM EST||
So Big Data is everywhere, well - it is if you believe all the hype.
But hype and hyperbole or not, what matters now is that we're talking about Big Data a lot because vendors are continuing to develop their applications, data models, cloud frameworks and supporting analysis functions around the definition of massive data sets that we have become used to.
But there's a problem and it's called ROI.
ROI or Return on Investment is the point where we see whether real world implementation of technology is actually viable, i.e., the truth is money talks and, well, you know the rest.
It's a bit like the difference between pure and applied mathematics (or indeed pure and applied economics) in motion. As you will know, in pure theories we can model and calculate what should work on paper and in the lab; but in applied theory we need empirical evidence, tangible results and (if there is money involved) ultimately some pecuniary proof of concept, or ROI and IT value basically.
For Big Data, this is a shame.
Well it might be a shame because the potential for Big Data is enormous. The German Bundesliga football club TSG 1899 Hoffenheim is said to be using Big Data analysis to improve player performance by placing special sensors in shin guards, clothing and the ball itself. With this kind of analysis we can start to produce what we call "capability characteristics" focused on measurable data such as acceleration, speed and ball contacts in real time for individual players or the whole team.
What is even better is that what was an incomprehensible stream of Big Data is now being translated into visual and configurable user interfaces.
The difficulty here is that German Bundesliga football clubs have a lot of money, so ROI is probably not perhaps as much of a worry as it is for firms in other industries.
If we look closer to the real world, organizations like Amnesty International are working with scientists, analysts, coders and hackers to try and determine how Big Data could help us solve some of the world's most pressing problems. The organisation is trying to harness the massive amounts of data available to determine predictive patterns of human rights abuses.
If we can do this kind of Big Data analysis competently, we could start to build an early warning system to impartially alert authorities as to where trouble spots might flare up. This could lead us to a point where we start to be able to predict crime, civil unrest and (if you develop the methodology fully in your head for now) to a point when we can even potentially prevent war.
Big Data could help save planet Earth, but ROI will always be our bottom line and so we need to address the monetary end of the Big Data equation before we can say whether these solutions will be implemented.
What does this mean for average CIO?
For our average CIOs not involved with international football or world famine issues there is still a lesson here and that lesson hinges around IT value and effectiveness (and therefore profitability) of implementation.
Do we have to prove that saving the planet is profitable before we do it? One hopes not. HP has a broad offering in this space with its HAVEn technology stack for what it calls connected intelligence and analytics-driven decision making.
HP's Big Data website quotes Chris Swahn, who is vice president and general manager for Avnet Technology Solutions, Americas, HP Solutions group. "HAVEn is a truly revolutionary new platform from HP... [enabling] our customers to transform their businesses and profit from Big Data, is a visionary solution brought to life for the real world," said Swahn.
But you'll notice how this spokesperson was quoted using the world "profit" and how he referenced the "real world" for some tangibility here right?
Getting IT value out of Big Data is not simple and it is certainly not as simple as the pure non-applied technology theorists would have us believe. With a little more time and an obedient eye on IT value and RIO, we just might get there though.
The list of ‘new paradigm’ technologies that now surrounds us appears to be at an all time high. From cloud computing and Big Data analytics to Bring Your Own Device (BYOD) and the Internet of Things (IoT), today we have to deal with what the industry likes to call ‘paradigm shifts’ at every level of IT. This is disruption; of course, we understand that – change is almost always disruptive.
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