David v Goliath: high performance analytics levels the big data playing field

How big does big data need to be before it is valuable?

High Performance Analytics levels the Big Data playing field

High Performance Analytics levels the Big Data playing field

The value in big data is within reach of everyone.  It could mean wanting to mine a couple of extra fields about the customer or wanting to improve the customer profile using unstructured data about customer interactions using Hadoop. Most articles and hype about big data surround the three Vs;  Velocity, Variety and Volume.  However, we should never lose sight that big data is relative to your business plan. The real conversation to be had is about the value in being nimble. 

The 4th (V)alue: The intersection of big data and high performance analytics
High performance analytics is the next generation of analytical focus as we work our way through the era of big data looking for optimal ways to gain insight in shorter reporting windows. It is all about getting to the relevant data quicker and delivering that information in real time. High performance analytics is equipping David-sized organisations with the tools to level the playing field.  Examples include:

  • How a bank determines credit risk assessment in seconds instead of hours.
  • Where a government agency improves social welfare by analysing unstructured citizen interaction data.
  • An insurance company that uses census data to improve marketing response rates.
  • How an online business analyses social data to understand sentiment, and behavioral data to improve campaign targeting.

Regional healthcare provider and an insurers point of view

I recently listened to an Australian healthcare customer discuss their version of big data and high performance analytics. It went like this.

Through some acquisitions we have increased our data base size by approximately 15 percent.  This has resulted in our marketing teams being frustrated with longer than usual time-to-market for gaining customer intelligence and executing campaigns.  Further compounding the issue is the competitive pressure coming from recent changes in government legislation, which is driving customers to shop around.  This increase in competition means marketing needs to be more nimble.  Meaning more campaigns to fewer people with more relevance.

Another example is a local Insurance customer I met with to discuss their version of big data, high performance analytics and real-time analytics.

We have issued our sales force with iPads.  The challenge we face is, how do we deliver intelligence to our sales representatives in a manner where we know it is relevant, timely and contextual?  We know they are meeting with prospects and customers but how do we analyse customer data, analytical data, transactional data and interaction data to provide a Next Best Offer in seconds?

If we understand how to beat Goliath, do we know what to beat him with?  A high performance approach leads us to think about the problem differently and look for a solution that optimises the analytical jobs and the way they were architecturally executed.  I expect there is a target value proposition heading my way, now.

Under the hood: high performance analytics is not that scary

We often think of new technology as being like a Ferrari, always thinking it is out of reach or too complex for the average David.  The reality is high performance analytics provides various approaches that span the spectrum of your maturity and size, from:

  • Moving existing analytical models into operational processes for real-time decisions.
  • Optmising analytical jobs to leverage your existing in-database power.
  • Using in-memory analytics to take advantage of cheaper hardware.
  • Building an enterprise analytical platform to drive down TCO while always prioritising business value using a grid based approach.
  • Visually exploring big data using high-performance, interactive, in-memory capabilities to understand all your data, discover new patterns and publish reports to the web and mobile devices.

The democratisation of analytics, especially high performance analytics has allowed every company whether Goliath or David-sized to benefit from big data.  Over the next few weeks we will be discussing the impact of the intersection with big data and high performance analytics.  In particular providing examples relevant to the world we live in left of the date line. Join the discussion to find out what the innovators are doing and lessons we can learn locally.  You can see some more examples here.


Question: 
What is your big data opportunity? Tell us in the comments below.

tags: big data, customer intelligence, Hadoop, healthcare, high performance analytics, HPA, in-memory analytics

One Comment

  1. Posted May 30, 2012 at 9:55 pm | Permalink

    There is fundamental challenge in understanding of BIG DATA Analytic nature. No matter what kind of analytic you apply today, it always needs statistician to do it. I call it manually applied statistics. That kind of analytic, was good till it had to deal with a few variables, regression models of linear type, most of the time, and with the delivery time measured in weeks or even months.
    BIG DATA Analytic deals with hundreds of variables, non-parametric models and delivery is expected in hours, may be minutes. Only the analytic which can meet those requirements would deliver on the promise of the BIG DATA. So, what is the analytic that can meet those requirement? I call it, Automatic MultiModel Prediction Production Systems.

6 Trackbacks

  1. [...] Left of the Date Line > Better analytics equals better decisions equals better business « David v Goliath: high performance analytics levels the big data playing field Better analytics equals better decisions equals better business Greg Wood|April 19, 2012 [...]

  2. [...] Like Vince said a few days ago, you don’t have to be Goliath to see how the intersection of big data and high performance analytics creates competitive advantage. Let’s also be realistic though: compared to someone like Walmart, pretty much everyone’s David! While Telstra and the Commonwealth Bank may not be the largest companies by global measures, they’re still great examples of how high performance analytics and big data can drive groundbreaking results. [...]

  3. By Big Data Seats CIOs at the Boardroom Table on May 8, 2012 at 11:52 pm

    [...] debunking the myth that big data is just for the big end of town I set out on the road to listen to what is happening locally.  For the past two weeks I have met [...]

  4. [...] challenge, by announcing that high performance analytics and information management strategy will level the playing field for competitive advantage.  After meeting with over 50+ CIOs in Australia, New Zealand, Singapore [...]

  5. [...] David v Goliath: high performance analytics levels the big data playing field: How big does big data need to be before it is valuable? A look at where the real value is in high performance analytics. [...]

  6. By High Performance Analytics on January 24, 2013 at 8:30 am

    [...] key issues to be addressed by big data tend to be summarised [...]

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    The Asia Pacific region provides a unique set of challenges (ความท้าทาย, cabaran) and opportunities (peluang, 机会). Our diverse culture, rapid technology adoption and positive market has our region poised for great things. One thing we have in common with the rest of the world is the need to be globally competitive while staying locally relevant. On this blog, our key regional thought leaders provide an Asia Pacific perspective on doing business, using analytics to be more effective, and life left of the date line.
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