There was a time recently when the hype about our growing ‘problem’ of Big Data seemed to be growing at an even faster rate than the data itself. It has died away a little, partly because the actual market has not really screamed in pain about the data storage resources required and the costs. But it is also the fact that the holders and owners of those giant data stores recognised from a very early stage that most of it is a resource that either has potential value or that the organisation has to have and hold as part of its remit. Think customer records, transactions of multiple types, meteorological or criminal or agricultural records and archives of all kinds. Social media certainly generates more new data than most of those orthodox and traditional data types, not least because it is full of storage-gobbling images and video. But then so is what we might loosely call professional content, from Netflix and RTE/BBC Player to National Geographic to the ever-growing options in video-on-demand.
But enough about sheer Volume. Yes, it is a challenge to store and manage, but in truth not as huge as the guesses about trillions and gazillions of yottabytes might suggest — even though the Internet of Things (IoT) is poised to take us to an unimaginable level of geometrical progression in data volumes. Looked at objectively and somewhat simplistically, it is all about the analysis, not the data or its superficially intimidating rate of growth. The ICT sector talks about the Five Vs as the salient characteristics of Big Data: Volume is the basis of the term, of course, accompanied by Velocity, Veracity, Variety and Value. It is a perfectly useful set of labels, easily understood, and helps to shift the focus to where it rightfully belongs — analytics. Big data is like underground ore or oil or gas. The value comes only when it is extracted and used.
Pool of talent
Ireland is rapidly developing a deep pool of talent in data analytics and related areas — data science might be the over-arching discipline — with third level research institutions and specialist IT services and a high level of working partnerships between them. One of the leaders is The Insight Centre for Data Analytics, a joint initiative between UCD, NUIG, UCC and DCU, established in 2013 by Science Foundation Ireland with funding of €75 million. Centre for Applied Data Analytics Research (CeADAR) is a joint venture between UCD, DIT and UCC, supported by Enterprise Ireland and IDA, with a more practical focus in that all of its research projects are industry-guided.
Accenture Ireland has been an industry leader in this field for some years, with an Analytics Innovation Centre in its Dublin operation since 2011. Paul Pierotti is one of its leaders and Accenture’s Head of Analytics for Health and Public Sector in the UK and Ireland. “Today we recognise that the key value of smart business analytics is realised when the insights that are generated are integrated into business processes. That is now possible because the combination of advances in IT, especially fast processing and cloud computing, mean that most of the technical and resource constraints on applied business analytics have been overcome.”
CIO agenda
We are increasingly seeing analytics as a central element of the CIO agenda, Pierotti says, pointing out that a number of high profile appointments recently have seen new CIOs coming from an analytics background. “Today what we might call ‘insight-led decision making’ is moving front and centre in everything organisations do. Some are really excelling, knocking the ball out of the park, others are gaining a decent return on their investment but others, unfortunately, are just failing. We are certainly seeing that the most successful analytics adopters have everybody on the bus — the CEO and the CFO are right there and the strategy and investment is led by the business, is not an ICT project, and has clear business outcomes as its objectives.”
“A detail of that approach, but a key one, is starting in the right place with a great business case. If everybody is committed, and you can deliver value relatively quickly, you inevitably start to build momentum. We are talking now about ‘Agile Analytics’, the delivery of many short term improvements that build into a significant total. We are certainly no longer in the world of 18-month projects before value is achieved.
“Most organisations can identify their own areas of potential quick wins,” Pierotti believes. “Fraud identification is a very successful one, in all sorts of sectors, while straightforward sales and customer retention is common to all commercial enterprises regardless of scale.”
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