The subcategory called Big Data is emerging out of the shadows and into the mainstream.
What it is.
Definitions abound (who would have thought it? – quite usual in the technology market). For Big Data, we quite like the definition that originated with Doug Laney (@doug_laney), formerly META Group, now a Gartner analyst. It goes something like this:
” … increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources)”
Gartner continue to use this “3Vs” model for describing Big Data.
Unsurprisingly, others are claiming Gartner’s construct for Big Data (see Doug’s blog post, 14 Jan 2012).
Put another way, Big Data is commonly understood to be:
“… a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools. The challenges include capture, curation, storage,search, sharing, analysis,and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to “spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions.” read more on Wikipedia.
Big Data could be executed on-premise if you have sufficient compute and storage in your corporate data centre. And some do, especially some large banks, and with good success. Several solutions are already out there on the market; Oracle’s Big Data Appliance is just one example. But it does also beg the question “why would you” ?
If you don’t want the CapEx of purchasing more tin, or don’t want to gobble up capacity in your own data centre, then there are alternatives. For example, a cost model now exists with cloud-based compute and cloud-based storage (for example, think of Amazon’s announcement of 25 percent reductions in the price of Amazon S3, it’s storage solution) that puts Big Data in the Cloud well within the reach of all UK enterprises. A cost model like that islikely to win friends in procurement and in corporate governance as well as in IT.
Hinging on technologies including Apache Hadoop clusters, Amazon Elastic Map Reduce (Amazon EMR) and others, Big Data is delivering a degree of analytics and visualisation not previously possible at affordable levels.
Don’t just take our word for it, ask around. We could point you to other experts in Big Data, such Matt Wood ( @mza ), Chief Data Scientist at AWS.
What it isn’t.
Big Data isn’t business intelligence (BI). What I mean is that Big Data isn’t BI in any traditional sense of the term. It is altogether another level on from that. Granted that some tooling enterprises may own may be recycled for use in Big Data analytics. But it isn’t another species, it’s another race.
Big Data isn’t a lame attempt at reviving a management information system (MIS); those should be left to rest in peace.
What it means for you.
By now, if you’ve read this far, something should be niggling away at you that you could be missing a trick. I trust it won’t be those voices in your head again. But it might be your instincts telling you how Big Data could answer those tough business questions – y’know, those “I can’t be asked” questions that existing systems just cannot deliver.
Now, you would not necessarily get our CTO to come right out and say that Big Data is the next big thing. But evidence we are assembling so far does seem to point to a new capability to deliver. For those with an appetite to understand their business in new ways, Big Data is delivering tangible intelligence that lets them see new dimensions, new possibilities and new revenue streams.
I did get a full radar lock on something our CTO said in the summer. It was a throw away line at the time but it stuck with me and with others. So, when the time came to consider an appropriate go-to-market message for our quarter three (Q3) focus, we decided to wheel out his one-liner as part of our messaging.
“It’s not about survival of the fittest -
it’s about survival of the best informed”
Robin Meehan, CTO, Smart421 Ltd.
Making no apologies to Charles Darwin or evolutionists, the statement is resonating with decision makers in the enterprise space, not least those in the Insurance sector. Why? Well, we think it is because a lot of the big insurers operate under many names in their brand portfolios.
The capability to see and understand impacts of brand activities, such as Insurance Quotes, delivered using Big Data analytics in the AWS Cloud, is illuminating new gains that would otherwise have remained out of reach.
Don’t forget – brand analysis is only one use case for Big Data in the Cloud.
If the world is going Big Data crazy then you need to know what it is, what it isn’t and what it means to your enterprise.
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