State of play: Big data trends

June 2015

Data graphAccording to the IBM ‘Systems Journal’ it was in 1996 that digital storage became more cost-effective for keeping data than paper. But the use and benefits of big data are now far beyond costs benefits. Brian Runciman MBCS looks at the latest trends in big data.

Big data has a huge crossover with the business intelligence world. But recently analyst Forrester commented that most organisations still analyse structured and unstructured data in silos, using different tools and serving different use cases. ‘The techniques used, such as statistical analysis, machine learning, natural language processing and artificial intelligence are now bringing text analytics closer to the world of business intelligence’ they say.

Burgeoning technology such as the internet of things (IoT) with its obvious connection to big data due to the sheer amount of data that can be produced means that there will be some tensions in the use of the data. Forrester mention in a recent paper that ‘enterprise applications must handle IoT data in two ways: 1) analyse large volumes to find patterns and insights that can be valuable in the future and 2) perform streaming analytics to glean immediate, actionable insights.’

2015 will be the year, say the likes of PricewaterhouseCoopers (PwC), that analysing the data collected via sensors from the internet of things will really kick in. But as more data is collected, processes will need to be decentralised to provide agility in its use. In their survey ‘Guts & Gigabytes’ PwC showed that 41 per cent of British executives use their intuition and experience in the decision-making process but only 23 per cent uses data and analytics.

Getting big impact from big data

Earlier this year McKinsey Quarterly ran an item on the efforts that organisations are making to turn their use of big data and data analytics into large-scale benefits. They note that some of the obstacles to that include a lack of willingness among leaders to invest in analytics and the fact that when analytics are undertaken users are either unable to correctly understand it, or don’t have the confidence to implement the changes suggested by the results. The piece goes on to suggest ways to make an organisation more receptive to analytics through change management and redefining jobs where needed.

As with their pioneering use of 3D printing, Formula One racing teams are making good use of big data analytics and have been for some time. The technical demands are high, with hundreds of sensors providing thousands of data points for analysis. In Formula One these include such things as tyre pressure and fuel burn efficiency, which have to be collected in real-time for very quick analysis by race engineers onsite. A Forbes piece by Frank Bi on this looks at how Red Bull Racing and driver Sebastian Vettel used big data in 2012 to fix damage to his car during a pit stop, leading to a race strategy change that helped Vettel win the world championship.

More recently, and progressing from the US’s recent social media driven election, ‘The Guardian’ ran a piece from Adriana Coppola of SapientNitro on using big data to be smarter in targeting floating voters. The piece discussed that by building a propensity model including more than just a ‘few data points, such as postcode, parties could build models that plug in tens of different data sets from across the internet, such as what online newspaper you read, where in the country you are, your age, what school you went to and even look for keywords such as “NHS” in your Twitter feed.’

So 2015 was not the first big data-driven election, but it was a step on the way.

Image: iStock/178804463

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