The relentless rise of the Big Data tribute act

You’d think anyone using social media, reading the technology press, or even watching the News at Ten would be fed up of Big Data by now. Nevertheless, new entrants in the buzzword Top 10 are climbing over each other in a desperate race to launch their own ‘X Data’ tribute acts.

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We don’t need an X Factor for Big Data tribute acts

I along with others have a number of issues with the term ‘Big Data’. Not least because it doesn’t actually describe what it‘s for. Yes, I can break it down into the 3 or 4 Vs or whatever, but that just refines the problem definition. It doesn’t add clarity. And of course, big is inherently a relative term: One man’s big today will soon become another man’s “You call that big?” tomorrow.

The Big Data industry is its own worst enemy. Before succeeding in explaining to business leaders the real value behind the over-simplistic buzzword, vendors who missed out on the first Big Data wave are complicating the landscape by spawning a whole family of new terms.  A dizzying list of crafted adjectives opportunistically stuck in front of “data” is emerging:

  • Clever data
  • Continuous data
  • Dark data
  • Deep data
  • Fast data
  • Fat data
  • Fuzzy data
  • Intelligent data
  • Lean data
  • Narrow data
  • Real-time data
  • Semi-structured data
  • Small data
  • Smart data
  • Thick data
  • Wide data
  • ….. ad infinitum

This frantic scramble to pitch new tents on Big Data’s lawn means more confusion for the end-buyer. How can they process “Forget Big Data, you need to worry about Thick Data” when they haven’t figured out what Big Data is yet? And how are they going to feel about the whole thing once they realise the confusion is a contrived ploy to occupy a less saturated marketplace.

Leading with the end value, and the difference your offering makes to realising it, is a significantly more effective message than inventing a buzzword for a variant on the technology theme.

Confusion poured upon scepticism

So when in September 2015 Gartner quoted an increase of only 1% of Big Data solutions deployed since 2014, my surprise was not profound. These are underwhelming results for an industry with so much transformation potential. All of these wannabe Big Data tribute acts cause further dilution and confusion in an already sceptical marketplace, struggling for confidence. Adding more ‘X Data’ adjectives does nothing to accelerate or de-risk investment decisions by C-suite decision makers interested only in outcomes.

If you have data, what business problem does it solve?

Your data, of course, is vital. It’s a hard-won representation of your business, spanning R&D groups, operations, governance and regulation, through to sales. It holds your understanding of both yourself and your customers. So how do you approach exploiting that data to actively improve your business?

Start by asking a number of basic questions, but critically answer them in the right order.

  • What aspect of my business do I need to improve and why?
  • Do I have a valid business case so I can understand the right level of investment to make?
  • What are the additional insights and understanding that I need to create better options, choices and drive my decision making?
  • What data do I need to drive the analytics to provide this insight?
  • Do I have that data already, or do I need to get more?
  • Do I have access to the right skills to deliver what I need?

Questions relating to the details of the data come at the end, not the beginning. If someone comes to you and starts talking about the critical importance of Thick Data, tell them to come back later once they can talk about the real business outcomes first.

See http://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/ and follow the breadcrumbs for an interesting look back (into the 90s) at where it came from.

Matt Jones

Matt Jones

Matt has over 16 years' experience of working in Research and Development groups within the ...

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Nick Clarke

Nick Clarke

Following a career in academic research, I have worked in the commercial IT industry for about 15 ...

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