The amount of information being created continues to rise at a rapid pace, and many organisations struggle to work out how they can take advantage of this wave of data.
Big data and analytics are often touted as the answer to these problems. With big data technology, firms are able to feed in all this disparate information, crunch it, measure it and manage it, and receive useful nuggets of insight about their business, their customers or their competitors.
Here, we round up four industry sectors where big data is being used to great effect, and offer insight into the firms using analytics systems and the results they have seen.
Retail is one of the most advanced sectors in the big data revolution, and stores are well-versed in the practice of customer data collection and targeted offers.
As IT systems have advanced, retailers have been able to take an ever more sophisticated approach in their marketing strategies based on the increasing amounts of data on offer.
As Miya Knights, senior research analyst, EMEA at IDC Retail Insights, explained: "The amount of data retailers generate has grown in line with their reliance on electronic networked IT systems to automate key operations, such as transactions, fulfilment, pricing and promotions.
"A proliferation of sources of information from competitors, user-generated content, social media and sensors has created massive volumes of structured and unstructured data available for analysis, which is increasingly required in real time."
And retailers are well aware of the value of mining this data. IDC research revealed that around 50 percent of retailers invested in big data analytics in 2013.
Knights added that this investment can offer retailers the opportunity to support increasingly complex and sophisticated customer interactions.
"To retailers, big data presents a challenge and an opportunity to derive value from this analysis to inform business insight on four fronts, identified by IDC as customer loyalty, revenue growth, cost reduction and new business models," she noted.
"The use of sales, customer and social data, as well as internal and external market and supply chain data, can help retailers optimise planning and forecasting capabilities in these areas."
Cosmetics retailer Lush is using these capabilities to change store displays around if it notices that a particular item is often purchased with another; while Amazon, the king of the online offer, always states which items other customers bought along with that particular book or kettle.
The big data revolution is helping retailers overhaul their marketing strategies. Past campaigns centred around offers sent through the post to the mass market, and then migrated to emails sent to customers based on previous buying habits. Big data technology means retailers can now collect, analyse and use this data on the fly.
When Germany lifted the World Cup on 13 July 2014 it was a triumph of teamwork, tactics, talent - and big data.
The German Football Association had worked with another German powerhouse, SAP, to build a new service called Match Insights that runs on its HANA platform and is powered by Intel processors.
This helps coaches and training staff sift through the huge amounts of data created by players to gain insights on key moments in games.
This is a key benefit, as Germany team manager Oliver Bierhoff explained: "Imagine this: in just 10 minutes, 10 players with three balls can produce over seven million data points. Our team can analyse this huge amount of data to customise training and prepare for the next match."
Another famous example of a sports team using data to achieve amazing results is the Oakland A's baseball team.
The team garnered much attention by basing player decisions on statistics, not intuition or nous. This was radical and many wrote the team off, but the manager, Billy Beane, was validated when the team went on a run of 20 unbeaten matches.
The story has been subsequently told in the Hollywood film Moneyball, and data analysis is now a key part of the strategies of other teams such as Manchester City.
The power of big data in sport is only just starting to be realised. The rise of tiny sensors such as those developed by Intel will soon make it possible to gather data from all aspects of certain sports - embedding them in players' boots, racquets or even the ball itself - to gather data in real time.
For coaches, players and even fans this will present a huge array of data that will deliver insights on performance, capabilities and areas of concern that need addressing. The success of the German football team is proof that such activities have merit.
So don't be surprised in the future if, rather than scribbling notes on clipboards, we see coaches and managers staring at tablets and ultrabooks, rushing to understand the real-time data being collected and sent back live from the field.
Modern cars are stuffed full of sensors, processors and other electronics that harvest data from almost every part of the vehicle. Everything from basic fluid levels through to suspension parameters and fuel injection can be monitored and recorded for later analysis.
Once collated and analysed, this raw data can be turned into useful information, giving engineers and manufacturers greater insight into how vehicles perform in the field rather than just in a testing lab or wind tunnel.
In the racing world big data has become a critical part of separating positions on the podium. Technology companies often partner with renowned race teams to provide platforms that collect and process data to tailor the car precisely for each race circuit.
The Caterham F1 team uses Intel as one of its technical partners. Intel, together with Dell, provides technology that helps with the initial design of Caterham's race cars, through to providing a mobile data centre for trackside support.
Big data can also benefit drivers as well as car brands. Telematics harvest a wealth of information from a vehicle's sensors, as well as recording its location and the time of day it is being driven.
This can all be fed back to insurance firms, which can then analyse the raw data and generate accurate quotes tailored specifically to an individual driver's behaviour and lifestyle.
Motorists who drive in what the insurer considers a safe manner will often find that their insurance premium is lower than those who indulge their inner rally driver.
The peak of big data use resides with driverless cars. These vehicles use internet connectivity to continuously stream data back and forth, effectively enabling a car to drive itself.
With a wealth of data gathered through its services, Google is making some headway with its take on the driverless car, which has a start-stop button in place of a steering wheel and pedals. Thus far, the car has completed over 300,000 miles of incident-free autonomous driving across California.
While it may be some time before the roads are filled with driverless cars, the role big data plays in the automotive world is only going to increase, and is likely to fuel a wave of innovations.
Banking has become somewhat blighted. Racked by controversy and shaken by distrust, the banks are turning to new ways to raise revenues and keep customers on side. One way of making more of what they have is through big data, its structuring, and the use of the resulting information.
This can present itself in a number of ways. User patterns could be tracked, so that the bank can better tailor services for customers or study the causes of churn and, importantly in this modern age, big data studies can help limit the risk of security breaches and credit theft.
Capgemini noted that banks ignore the big data opportunity at their peril, explaining that there are a number of things currently holding back the financial services sector. Chief among these is that data is disparate and locked away in a range of systems.
Not embracing this information, and the opportunities it presents, denies access to a market that could save banks millions of pounds a year.
Capgemini said that, while around a third of financial organisations have 'hands-on experience' of using big data, the majority, 63 percent, are flirting with pilots and experiments.
Those that have made real investments already a have a 12 point lead over their competitors, the consulting firm added, while warning that dissatisfaction causes 10 percent of customers to change providers every six months.
Tony Lock, an analyst with Freeform Dynamics, agreed that banks could benefit from big data when it comes to fraud detection and discovery.
"Banks really want to get better at real-time analytics to reduce 'fraud' and increase cross-sell opportunities," he noted.
Lock explained that firms that have used their big data in this way have claimed success, adding: "The ones who have, say they see real value and cost savings."
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