Apr 21st 2017

The Big Data Experiment

The Big Data Experiment – what can we learn?


Is the big data concept truly running out of steam? Certainly, the time and cost associated with these projects is raising questions – not least from the beleaguered CFO – as organisations are still struggling to deliver the hoped for insights. But as organisations’ demand for data led insight and data democratisation continues to grow, no business can afford to turn its back on analytics. With cognitive analytics now a viable option for even the smallest companies, how can organisations gain the confidence to move forward?


The success or failure of any data/analytics project should be judged on one essential principle: does it make the business better at using available data to make better decisions in real time?  Time to insight is critical – and this is where so many big data projects have gone so expensively wrong; and where the cognitive analytics model differs significantly.


The theory behind big data projects is simple: gather together every possible piece of data, both within and outside the organisation, and leverage unprecedented computing power to sift through for new, invaluable insights. Sadly, this has proved to be more complicated and expensive than hoped. For many companies, the big data jury is still out – it is taking too long, costing too much and, to date, delivering too little value.


Cognitive computing takes a fundamentally different approach – not least in focusing on small, not big, data. By using cognitive analytics on specific, trusted data sources a business can achieve rapid insight within specific business areas, such as merchandising, which are refined through iteration to deliver quick wins.  As a result, cognitive projects are significantly smaller, quicker and cheaper than traditional analytic projects – organisations can achieve new intelligence within days.


The sheer scale of big data projects also required people to prioritise analysis towards specific areas – from buying trends to supplier performance. The truth is, however, that people will pre-judge analysis and will tend to focus on the results that reinforce expectations. The result is a very expensive exercise in proving what individuals already know. In contrast, cognitive takes people out of the equation.  Using cognitive engines and algorithms on an existing data set will provide a completely dispassionate insight that reveals previously unseen and unconsidered connections.


Cognitive also heralds a new investment model – which will be a relief to the CFO community. With cloud based analytics now gaining momentum, organisations no longer need a massive investment in hardware, software and people that spans months and years.  Leveraging cloud based cognitive analytics services is low cost and offers quick results – enabling organisations to pilot the concept without risk.


This is a new era of analytics – so how can organisations make the shift from the legacy thinking and legacy technology that has, to be frank, mired many a big data project? Cognitive analytics is a very different approach that will fundamentally transform the time to insight. The key to making this switch is to forget any idea of a mass of data, of linking social media with manufacturing, financials with customer data. Cognitive is about starting small and working with just one or two specific data sets within a single operational area.  With quick results, the business users have the chance to embark rapidly on an iterative process of refining data and rerunning the analytics to confirm results. This is a new way of thinking that is intuitive, iterative and responsive.


Organisations may be bruised by the fallout from big data projects but with the right approach cognitive analytics can empower business people with fast, trusted insight to support essential innovation.


If you would like to discuss the future of data analytics and the type of big data projects Zizo can support your business with, for just one fixed monthly fee, our team of experts would love to speak with you – drop us a line via our contact page


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