At HP Discover 2014 in Las Vegas last June, executive vice president for HP Software Robert Youngjohns detailed the three primary categories of data being generated by IT. He described the first, machine data, as being relentless and “often a by-product of what you’re doing, it’s vast in quantity but difficult to make sense of”. Business data and ERP data, on the other hand, was an important but declining proportion of the overall data fundament. Finally, there was human information, which Youngjohns said, was “vast but wholly unstructured”.
But over and above the challenge of the sheer scale of data likely to be generated in the next few years is the problem that while “up to 90% of data in the future will be in the machine and human categories, most of the tools are focused on the business data”.
Noel Crawford, ecosystem development manager at the IBM Innovation Centre, makes a broadly similar point when he identifies growing instrumentation and interconnectivity as “the two main factors driving the growth of Big Data and business analytics” in 2014 and 2015. He cites research from IBM which reveals that as many as 65% of companies “are not using that data to the full advantage of their business”.
Crawford believes this is partly an issue of how business analytics is perceived. He says it was traditionally thought of as information used by business managers and decision makers “and not necessarily for everybody”. That perception “has changed”, he claims, with analytics becoming more significant for marketing, operations, risk analysis and other business areas.
The frame of reference for business analytics has changed, he adds, shifting away from purely focusing on transactional data. Crawford suggests that analysis on sales orders or accounts receivable “is very much an historical, almost passive reporting context in business”.
Today, business analytics “is much more proactive”, he remarks. Companies don’t need to be passive recipients of information. Instead, they can ask questions of that information to gain greater insights and analysis.
Legacy issues
Gerry Murray, country manager at EMC Ireland, expects the main focus for many companies over the coming 12 months will be on “getting to grips with Big Data plans and moving from their legacy BI [business intelligence] systems to big data predictive analytics”. He adds that, unusually for the IT industry, “despite all the hype, Big Data in all of its guises does offer incredible real-time business insight and value”. But, like Crawford, he says many businesses “are still struggling to realise the potential” and how to exploit it.
Crawford observes that Big Data has become “so complex and fast that response to analytics results now is often automated, taking some operations out of the decision making process equation entirely”. This approach, he adds, applies across the board to companies, government departments or educational institutions. Customers are telling IBM: “With so much data being generated, we need deeper analytics, more algorithms and better visualisations to help us understand what patterns there are and what parts of the data is actually relevant to us to guide our business decisions.”
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