Big Data

How industry will be revolutionised by big data Exclusive interview with Microsoft UK’s chief envisioning officer Dave Coplin | Pages 8-9 MARCH 2015

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Big data

Why Big Data will be one of the star players in this summer’s Ashes clash (After all, England need all the help they can get…)

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Big data

Opening shots Shane Richmond

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HERE ARE more sources of data than ever before, collection is getting easier and storage is cheap, so your company, like many others, has probably already begun to embrace big data. But do you have a clear idea of why you’re doing it?

Earlier this month, amid the usual cacophony of live blogs and hot takes, Apple launched its new Watch range. Knowing it had the attention of media and analysts, the company made them wait an hour for details, concentrating in the meantime on Apple TV, new Apple stores in China, iPhone sales figures and other bits of information.

Among these announcements was a particularly interesting one: ResearchKit. Typically, medical researchers find it hard to recruit test subjects and often have limited access to them to administer repeated tests. Apple’s ResearchKit turns the iPhone into a medical research tool, harnessing the hundreds of millions of iPhones sold to date to take a big data approach to the problem.

Using dedicated apps and the iPhone’s sensors, researchers can give test subjects a range of exercises, such as a finger-tapping test in a Parkinson’s disease study, or even collect data when the phone is in a subject’s pocket.

In an Apple video, Dr Max Little, a mathematician and biomedical researcher at Aston University, says that ResearchKit means “going from data that might be collected, say, once every three months, to data that’s collected, say, once every second.”

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Your big data may well be very big… but do you know how to use it?

This clip underlined just how much data can be collected via smartphones – and that will only increase as wearable devices continue to grow in popularity. The scientists and researchers featured in Apple’s video are all desperate for more data. Their research has been held back by how little they have been able to collect up to this point. Most businesses have the opposite problem – drowning in data but unsure what they should do with it.

There are two lessons to learn from this project.

I’ve spoken to lots of companies who collect vast amounts of data simply because they can, then let it languish. Often that’s because they have started from the wrong point. They have asked whether they should be collecting data and decided that they should. But they should have begun by asking “why should we collect this data?”

ResearchKit users have no doubt – they Twitter: @ are trying to cure diseases. They need data to shanerichmond

understand those diseases and to learn more about the people who have them – and sometimes about those who don’t. Why does your company need data? Is it to increase sales? To improve customer service? To retain employees?

Your answer will help determine the next question: what do we need to know? You might measure one set of data if you are aiming to increase sales and a different set if you intend to improve customer service. It sounds obvious but you would be surprised how many companies opt to measure everything and find they then can’t see the wood for the trees.

The scale of research promised by ResearchKit is impressive but what’s really promising is the kind of focus it allows. Only once you have decided why you are collecting data and pinpointed what you should collect can you move on to actually analysing it. To borrow an old adage: size isn’t everything, it’s what you do with it that counts.

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By Tim Adler

GILL WHITEHEAD, director of audience technology and insight at Channel 4, shows me the television ad trumpeting this month’s relaunch of its 4OD on-demand player. It’s laugh-out-loud funny. Channel 4 will not allow me to share the cheeky and irreverent punchline – but think royal weddings, balcony scenes, a young prince and modern mores. Needless to say, it should grab the tabloid headlines.

Channel 4 was the first UK broadcaster to launch an on-demand service in 2006, leaving other broadcasters, excuse the pun, to play catch-up. Unlike the BBC iPlayer, 4OD offers entire boxsets of recent Channel 4 hits such as Peep Show, The IT Crowd and Utopia, going back to earlier shows from the 90s such as Brass Eye and Father Ted. The broadcaster also started making exclusive shows for online, such as extra episodes of cult teen drama Misfits.

4OD also made its entire archive downloadable, enabling viewers to transfer content onto mobile devices if they watch shows on them. You can watch 4OD on your PC, smartphone, gaming console and all the broadcast platforms such as Sky, Virgin and Freeview.

The board put its weight behind a viewer engagement strategy back in 2012, placing big data at the heart of its business. Channel 4 chief executive David Abrahams used to be in advertising so he understands the value of metrics and data crunching.

“David has been a passionate advocate,” says Whitehead. “One of the things that has made our data program so successful is that it’s so centralised in the business.”

Channel 4 understood that television was increasingly being viewed online, and encouraged 4OD users to supply personal information. Comedian Alan Carr fronted the advertising campaign. The broadcaster made clear that the more personal data viewers provided, the more helpful it would be to advertisers, enabling the broadcaster to make better programmes. This engagement was so successful that 80 per cent even provided home addresses voluntarily.

The channel was also scrupulous about saying what it would do with the data, promising not to sell it on and deleting personal information if a viewer decided to opt out. Just 0.1 per cent of those who signed up have had second thoughts.

Whitehead says: “What I don’t like is being asked for information and then not knowing what it’s going to be used for.”

To date, 11.5 million viewers, or 18 per cent of the UK population, have registered for 4OD. More than half of every 16 to 34-year-old in Britain has registered. And about 25 per cent of those registered are what Channel 4 calls “active” users who dip into the service regularly.

And a smaller subset of those, around 9,000 4OD users, signed up to become a focus group giving continual feedback on what the broadcaster is doing and influencing its future direction.

Meanwhile, Whitehead’s research department started polling viewers’ reactions to 4OD. The overall message was that the on-demand platform had to be less glitchy and needed a redesign.

This month Channel 4 relaunches 4OD as All 4, offering viewers live channels, the on-demand catalogue and exclusive Channel 4’s

Big data

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Channel 4 prepares for cheeky 4OD relaunch

C4’s revamped All 4 will stream shows such as (clockwise from left) Utopia, The IT Crowd and Peep Show in a format designed for big data mining

“The heart of the service will be three sections: On Demand, On Now and On Soon” content. The heart of All 4 is a Netflixstyle recommendation engine, suggesting programmes viewers might also like. It takes 4OD up to the next level, with an increased emphasis on personalisation. The homepage you see will not be the same as somebody else’s.

The heart of the service will be three sections: On Demand, a video-on-demand service with additional behind-the-scenes content; On Now, streaming the live channels; and On Soon, a preview channel premiering some shows before they have aired on the main channel.

“We look after all the audience touch points – traditional research, data, and new capabilities in Customer Relationship Management,” says Whitehead, who previously spent six years as the channel’s strategy director. She was recruited from BBC Worldw ide, t he corporation’s commercial arm.

Whitehead will not say how much this relaunch is costing the broadcaster.

“Costs involved in data mining have come down.

We save money by using cloud-based storage and open-source software such as Hadoop. We’re

Gill Whitehead

very clear about the business benefit we derive from big data.”

Audience research has shown that personalisation, or predictive modelling, is one of the things they want most.

Whitehead says: “We researched people’s desire and expectation for personalised features such as recommendations and being pointed towards new, upcoming shows.”

Personalisation also allows advertisers to target viewers more specifically. Sky and Virgin are experimenting with so-called “dynamic ad insertion”, serving different advertisements to individual households.

You may be in the market for baby food and nappies, while next door is more interested in holidays and life insurance. All 4, which already carries pre-roll advertising, is watching developments.

So, does Whitehead envisage a point where the regular broadcast channels disappear completely, and on-demand services – such as the BBC’s recentlyannounced MyBBC and ITV Player – replace live channels altogether?

She shakes her head. “Linear television still accounts for 90 per cent of viewing.

Online only accounts for 10 per cent. Live television responds to human rhythms and needs. Personalisation complements this but it doesn’t replace it.”

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Why getting it right is an all-consuming business

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hinking back to the mutual fund market timing crackdowns in the financial services industry during the mid-2000s, I recall a lawyer calling to ask why I hadn’t responded to her customary close-of-business “could you please do a quick analysis on…” email. I hadn’t received it, and so asked if there were any file attachments, and if they were big. “It says 72 megabytes… is that big?” (It was, then.)

When I explained that she was trying to stuff the equivalent of 15 Bibles into the phone line, she was more appreciative of the reasons for delay.

Introduce “big” data, and attachment size befuddlement becomes bewilderment for many. It is difficult to define, hard to manage, and more challenging still to analyse. Add a moving possibilities horizon and a voracious marketplace for analytics to the inherent challenges, and being a big data consumer becomes, well, consuming.

Gartner has mediated the issue in discussions about “What is it?” by popularising the “3 Vs” as key attributes in identifying big data: volume, velocity, and variety. If there’s a lot of it and/or it’s being added to quickly and/or the information is

in many different forms, then big data may be a relevant characterisation.

Leaders face relentless pressure to extract value from big data – so much so that the regular data is easily forgotten or materially neglected. The risk of an incessant buzz around big data is that corporations neglect the basic information which is central to the daily functioning of the business.

Amazingly, many leading companies have a very difficult time keeping essential components of their data house in order.

The reality is the data centres look nothing like clouds. There is a real bricks and mortar aspect to storing and maintaining information, and a very good chance that some forgotten person in the IT department is managing critical information under conditions that create real exposure for the organisation.

Customer-identifying information, derivatives transactions and positions, regulatory reporting archives, and securities master files are just a few of the neglected structured data sets that have recently been sources of painful regulatory inquiries or litigation events for our clients. In these data analytics projects, poorly kept or ignored data have cost leading firms tens of millions in penalties and legal and consultant fees.

By diverting business leaders’ attention from basic data housekeeping, the big data phenomenon has contributed to business harm. So how can the big data discussion be canted to benefit the whole organisation?

First, ensure that your organisation maintains a robust information governance programme. Second, adopt a mindset that all data is big data, and recognise that the ordinary data of yesteryear is a very relevant subset of today’s buzz.

Getting it right is a difficult task. And while funding and resources can always be found

in a crisis, arguing for proactive investment in operational data maintenance over sexy big data analyses is much more difficult.

Getting it right requires a mindset shift away from abstract cloud imagery to a practical understanding of the nuts and bolts of all business-critical data, and is a necessary part of ensuring that big data promises don’t contribute to real data breaches. +44 20 3727 1343 nick.hourigan@fticonsulting.com

Getting the future right with Datastax and Cassandra

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ata is changing how businesses progress and adapt to their customers’ needs. A technology system called Apache Cassandra™, distributed by enterprise software provider DataStax, is helping companies use their data to give them the edge. Billy Bosworth, CEO of DataStax (below left), says: “What we are doing today is really starting to revolutionise how companies interact with their customers. You are probably a user of our technology right now – you probably use it several times a day and you just do not know it. We are becoming the secret sauce under the covers that is allowing customers to completely and radically change what is possible with their customers.

“How we do that is with a database called Cassandra – an open-source technology that helps our customers overcome the obstacles to innovation.

They are getting crippled with the old relational databases that are too complex and too expensive to manage the current influx of data, such as Oracle. We do it at a fraction of the cost, and as they revolutionise

their businesses they are turning to us.”

Bosworth explains that one way Cassandra helps clients is by being always on. “What an always-on database means is we can keep your systems running through incredible outages and disasters,” he explains.

“We have this capability called Multi Data Centre – what that means is we are going to spread the distribution of the machines and data so, if you lose a couple of machines or an entire data centre, your business will still operate like nothing happened.

“You can distribute and leverage the cloud in conjunction with your physical data centres.

Customers have ultimate flexibility on how they want to configure their infrastructure with us, so that you can have an always-on service level agreement no matter what happens.”

DataStax only started close to four years ago, and it already has more than 400 customers in 39 countries and is used by 25 per cent of the Fortune 100 companies. “The way they are using us is very missioncritical,” says Bosworth. “It is essential for their customer adoption rates.”

Cassandra is used at Netflix to maintain user profile data so that the company knows what entertainment shows they want.

Bosworth says: “They released an incredibly popular Netflix original series called House Of Cards. The way studios would have done such things in the past is that they would have gone out to do a couple of focus studies and listened to 20 people and said ‘I think we have a great idea for a movie – let’s pitch it’.

“As Netflix is in an always-on environment, it is able to capture and understand so much about us as users that they do not have to guess what we are going to like.

They can start now to make predictive accurate decisions about the kind of programming someone is going to want to watch. When they released House Of Cards, the probability of failure was very low because they were able to know what people liked.”

DataStax is the secret sauce for progressive companies these days – enabling them to innovate for their customers in ways they never were able to before. www.datastax.com

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Big data

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The inner geek

UK firms ill-prepared for data breaches

Moz & Bradders

How predictive analytics can reveal more than you’d like

By Tim Adler

BACK IN 2003, a man walked into a Target discount store outside Minneapolis and demanded to see the manager. He was clutching coupons that had been mailed to his daughter, and he was angry.

Why had Target been sending his teenage daughter coupons for baby clothes and cribs? Were they trying to encourage her to get pregnant?

The manager did not understand what the man was talking about. He looked at the flyer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologised and then called a few days later to apologise again.

On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”

What the angry father and his pregnant daughter did not know was that the teenager had been enrolled in a programme to pinpoint expectant mothers. As recounted in New York Times reporter Charles Duhigg’s book The Power Of Now, Target was analysing shopper habits to predict which of its customers was pregnant.

That was over a decade ago. Just imagine how big data predictive analytics has moved on since then.

Amazon has patented an algorithmbased system for predicting what you will buy before you even order it. Your order will already be packaged up.

D u h i g g s a y s: “ B i g d a t a i s fundamentally transformative, not only to corporate life but also to healthcare and education, probably more than people realise. It’s giving us the ability to see beyond anecdotal evidence. It reveals correlations that you didn’t know previously existed, allowing us to see relationships.”

Big data is transforming everything in business, helping companies meet customer needs more accurately. All of us are sent advertisements for products we

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£114bn spending on global big data in 2018

90%

of Fortune 500 companies with big data initiatives

Source: ABI Research

are uninterested in. The more data you have, the more targeted you can become in personalising goods and services.

“People don’t really appreciate how much information is being collected about them. Pretty much everybody has a credit card and a smartphone that are little data pumps,” Duhigg says. The term big data, however – redolent of Big Brother watching you – puts people off.

The amount of big data, though, keeps increasing. Gartner forecasts that 4.9 billion connected things will be in use in 2015, up 30 per cent year on year, and will reach 25 billion by 2020.

As the internet of things expands, billions of sensors will surround us, each of them a data point.

In fact, says David Hand, emeritus professor of mathematics at Imperial College, we are in danger of being

overwhelmed by the amount of data flooding in. Last year, Vince Cable, the business secretary, announced £42million of funding for a new body, the Alan Turing Institute, which is intended to position the UK as a world leader in big data. Cambridge, Edinburgh, Oxford, UCL and Warwick have been selected to lead that research.

Says Professor Hand: “Some people say, ‘The numbers speak for themselves’ but that’s nonsense. There’s no doubt that there’s huge promise about this tremendous research, but nobody wants data – they want answers that extract meaningful information from it.” Professor Hand

thinks that Britain faces a skills shortage of people capable of analysing this tsunami of data.

Andrew Flowers, quantitative editor of Fivethirtyeight.com, says that companies complain they have so much information about customers, they don’t know where to begin.

Flowers says: “The real problem is interpretation, learning and skills.

Schools are really trying to keep up by teaching people basic maths and statistical analysis. Numeracy skills are going to be a real hindrance on people understanding what data means.”

Duhigg goes further and suggests that numeracy will become as important in the 21st century as being able to read became after the invention of the printing press.

“If you give people too much information, people get overwhelmed.

Part of the age of big data is giving people statistical literacy, how to think about big data. Companies tell me they have so much data but they don’t have enough people asking the right questions.”

Even having enough people does not mean they will ask the right questions.

Critical thinking is just as important when it comes to interpreting data.

In 1936, The Literary Digest polled 2.4 million Americans asking them how they were going to vote in the upcoming election. They got names and addresses from automobile registrations and phone books. The result predicted a win for the Republicans over President Roosevelt (below). However, the result was an overwhelming win for Roosevelt – what The Literary Digest had overlooked was that the majority of car owners and telephone households were wealthier Republicans.

Professor Hands says: “There’s a potential danger that these vast data sets can be skewed.

Human beings are great at finding narratives that aren’t really there. Yes, there are benefits from the technology but you can easily trip up or fall off a cliff.

NEARLY one fifth of UK businesses have suffered a data breach in the last two years.

Loss of personal information has affected 40 per cent of British consumers, who are less understanding about companies that have been breached, seeing it as their own fault rather than being victims. Two thirds are concerned about falling victim themselves in the future.

Yet one third of UK businesses do not have a data breach response plan in place at all. And only a third have specific budgets set aside to deal with data breaches, despite 81 per cent saying they were concerned about how much it would cost to recover from a breach.

Experian, the financial data company, surveyed 400 senior business executives for its data breach survey.

The UK data breach landscape is going to change rapidly over the next two years, and the frequency of incidents will continue to rise, Experian concludes.

Amir Goshtai, managing director, Affinity Experian Consumer Services, said: “The prevalence and severity of data breach incidents will to continue to accelerate, as will the volume of reported cases.”

Even if they are breached, 39 per cent of companies have no reporting procedures for lost data on mobiles or laptops. Less than half have data breach or cybersecurity insurance in place.

Customers are overwhelmingly less forgiving, saying that data breaches come as a result of a business’s own failures. Eight out of 10 think companies should be penalised for compromising their customers’ personal information. And 83 per cent think companies should be regulated harder to better protect their customers.

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We will have to look at the data That’s what coach Peter Moores said after England’s World Cup shambles. So can the ECB’s head of IT Damian Smith help?

Tim Adler went to Lord’s to find out…

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IG DATA has transformed the of other international cricket teams, have been business of sport. Football, golf swift to embrace data analysis over the last and motor racing have all embraced decade. “sabermetrics” – data-mining When I meet Smith at Lord’s, he jokes: statistics to improve performance “I rather tenuously claim to have won the Ashes or select teammates. in 2005. Ten years ago we were starting to use The Brad Pitt film Moneyball, based on this kind of performance technology in anger, Michael Lewis’s bestseller, told the story of and it became quite a powerful tool.” how the cash-strapped Oakland Athletics The ECB has video cameras analysing baseball team took on much bigger rivals by team performance in every first using data, as opposed to gut instinct, to class county ground. The footage build its team. What Oakland Athletics is scrutinised by analysts and turned did changed the face of team selection. into data – the angle a ball bounces Cricket is no exception. After in front of a wicket, whether it goes England crashed out of the World Cup wide – and feeds that metadata into in Australia earlier this month, head the player development and team coach Peter Moores reflected: “We will selection process. have to look at the data.”

Smith wonders whether in future, It was a remark that brought instant as data becomes increasingly rich, it derision on Twitter. Moore’s will affect what order team members critics argue he should are paired up as happens already in spend less time hunched statistically-driven Formula One over his laptop and more motor racing. time watching players “Traditional metrics about in action. batting averages are all being L i ke b a s eb a l l , superseded by more cricket is awash with sophisticated statistics – how many runs scored, bowling speeds, wickets taken.

Indeed, Damian Smith, head of IT at the England and Wales Cricket Board (ECB), says the England Damian Smith, head team, along with a host of IT at the ECB

metrics such as the impact an individual has on a game,” he says.

The ECB shares its data insights with the counties but Smith stresses that “it’s an arms race.

Everybody is looking for that competitive edge.”

Smith, who previously worked in banking, defence and tobacco, joined the ECB two years ago as head of IT, but was involved a decade ago in overhauling its IT systems and reinvesting the money saved in installing performance-capture cameras in county cricket grounds.

“It’s lovely to work in an industry that does very little harm,” he smiles. “It’s something that you can be passionate about.”

He downplays the importance of big data, however, when it comes to actually deciding who’s in the team. His role is to provide the IT systems that support and not decide the Test match selection process.

Smith says: “Statistics can help inform a decision but I don’t think it will get to a stage where it picks the team for us. It’s all about a split-second decision, the way a captain reads a player’s mood in the dressing room. The things that separate the best teams from the others because of that indefinable X-factor.

“We’re using stats to inform team selection decisions, but they are the not the overriding

factor and never will be. The beauty of sport is that if it was all statistically-driven, then it wouldn’t be interesting.”

Almost one in five people in Britain follows or takes an interest in cricket, and nearly 1.4 million watched county cricket alone in 2014.

This summer interest will intensify when the Australians arrive for their five-Test series.

The ECB itself earns £123 million a year, bulked up by Sky’s exclusive TV rights to the game – estimated to be worth £70 million annually.

Smith is most enthusiastic about this kind of video performance capture trickling down to village cricket. The video cameras the ECB equipped county cricket grounds with back in 2005 have become commonplace. This means the kind of granular data that Smith and his team pore over is available to every village coach.

“The real wins for me are in grassroots cricket.

The barriers to entry are coming down all the time – a decade ago, cameras were expensive and laptops capable of crunching that amount of information were very expensive. Today, the cameras we introduced a decade ago are not as good as an iPhone.”

Now Smith wants to use data to build cricket’s fan base across the country. “The role of the ECB is to grow and retain participation, either

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Manipulate an n-dimensional data cube? Now you’re talking…

Keil Hubert

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playing or watching – to grow that base so that we can generate as much revenue as possible from government, sponsors and broadcasters,” he says. “Our customers are our product, so the more we know about our customers the more we can attract funding to grow and retain participation.”

Nearly one third of hobby cricketers use an ECB website called Play-Cricket, where amateurs upload scorecards, how often people play and when. Last year, the ECB went deeper and conducted an experiment in four counties – Cheshire, Northamptonshire, Northumberland

Main image: England crashed out of the Cricket World cup in a surprise defeat to Bangladesh earlier this month; Inset above: England coach Peter Moores; Below: happier times winning the Ashes in 2005

and Surrey – reminding amateur cricketers if they hadn’t been playing so much recently, and congratulating those who did if they scored a 50 or a century, or turned in a great bowling performance. The results were heartening. The ECB plans to roll out the system nationally this year.

Smith says: “We got a really encouraging take-up in terms of people who dropped out of playing, encouraging them to get going again.

The real challenge for us is not other sports but other things competing for people’s time – apps, mobile phones and Twitter.”

One difference between the ECB and the other big three sports associations is that it does not own its flagship ground. The Football Association owns Wembley Stadium, while the RFU owns Twickenham. Lord’s Cricket Ground, however, is owned by the Marylebone Cricket Club, while other iconic grounds such as Old Trafford and The Oval are run by county clubs.

This means that the ECB has limited visibility on visitor data.

Cricket fans, however, converge from all over the world to watch cricket, and Smith is keen to learn lessons from this data. “The more that we can understand what prompts people to come great distances for a cricket match, the more that will help us improve the customer experience.”

’M EMBARRASSED to admit that when I first read about business intelligence products in 1997, I thought that BI pertained to covert surveillance kit, like the kind you’d see in a James Bond feature. I was disappointed to learn that that it was actually about trying to find meaningful trends and indicators within massive reservoirs of stored transaction information. How… boring. I just couldn’t picture Daniel Craig hunched over a laptop trying to interpret vodka-buying trends among 17 to 26-year-old single urban university graduates.

By now, everyone’s likely to have read Charles Duhigg’s riveting story published in the New York Times two years ago, where he explained in layman’s terms how US retail giant Target leveraged its treasure trove of big data to know things about specific consumers before the consumers themselves did. In addition to being a gripping read, rife with questions about privacy, invasiveness, ethics, and business impact, Duhigg also touched briefly on a problem I’ve encountered on every big data and BI project that I’ve ever worked on: you don’t get any value from processing your horking gobs of stored data if the data itself isn’t any good.

I was doing IT project management for a large company that had been contracted to install an online analysis processing engine onto a bunch of mainframe systems that controlled cost data for some aircraft maintenance facilities.

The original project team had promised the client this new OLAP capability would allow upper management to (and this is a quote) “manipulate an n-dimensional data cube” to determine whether or not a rainstorm in Oklahoma on a Tuesday would increase the cost of spanners bought for a wing replacement in Ohio. It sounded miraculous.

Since the head implementer was

more of an evangelical prophet than an engineer, he had promised the client’s executives they could divine new places and ways to cut costs in the darkest corners of their sprawling industrial empire.

It took me less than two weeks to realise the project was never going to accomplish anything.

Once I chatted with the people who actually worked at the client’s depots, I discovered that the data that was supposedly being manipulated by our new cubethingy was actually worthless.

Historically, the various subelements within the umbrella company had always managed their profit margins by obfuscating their actual costs and issues from upper management.

The data they entered into the cost-control mainframes represented an agreed-to interpretation of realty; what they wanted the auditors to see, not what was actually transpiring. The actual cost data existed separately – on paper – locked securely in the line managers’ offices. The big bosses could play with their new OLAP all day long, and they’d never come close to implementing any sort of meaningful change – it was the IT equivalent of giving your toddler a toy steering wheel while they’re buckled into their car seat and telling them that they’re driving.

If you’re pouring money into a big data project, put the spadework in up-front to ensure the data that you’ll be analysing is actually valid.

Audit your core business processes to ensure that what employees are entering into your systems reflects what they’re doing, and not what they want you to think they’re doing. And when you find a discrepancy, invest in fixing it before you try to perform any analysis on it.

Business Technology · March 2015

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Big data

Tim Adler

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TANDING IN the atrium of the Microsoft Research in Cambridge, you face a glass sculpture remeniscent of the DNA double helix. Quite fitting considering what Dave Coplin, chief envisioning officer of Microsoft UK, tells me about how big data will transform how all of us will live (and die). Look up, and you see that mathematicians have scribbled equations on the inside of their office windows.

Microsoft Research only moved into these slick, well-appointed offices two years ago.

Microsoft employs about 1,000 researchers worldwide in seven research centres with a footprint covering China and India. Last year, it spent $11.4billion on research, representing 13 per cent of total revenue.

Areas that Cambridge specialises in include machine learning, computational science, networks and programming. “But really everything that we do here is about big data,” says Dr Kenji Takeda, solutions architect and technology manager. “Big data is an interesting term that’s been used for around a decade: managing information in terms of volume, velocity and variety – the three ‘Vs’ of big data.

“We’re a small ‘r’ and a big ‘D’ when it comes to research and development. Our job is to push the boundaries in computer science and take those ideas to make sure there’s innovation in the products and services that Microsoft delivers.”

You get the impression that Microsoft Research is really an exercise benefiting humanity with trickle-down benefits for Microsoft’s day-to-day business. Its researchers are, after all, recruited from the cream of academia – lured, no doubt, by a healthy pay packet. One scientist has a photo of himself standing next to Bill Gates proudly pinned to his door.

“As we’re in the industrial research business, we’re part of the commercial team, not an academic team,” says Takeda. “That said, there are very few research labs that give their researchers so much freedom, letting us explore ideas that will disrupt the future.

A lot of the research we do feeds into our commercial work. You never know what it will lead to.”

Practical applications of the Cambridge centre’s work includes helping develop the Bing search engine, essentially a series of linked data sets; the Xbox Kinect, the games console control system which uses people’s movements; and Cortana, Microsoft’s rival to Apple’s Siri, a digital assistant that interacts with big data to keep growing exponentially (“We call that ambient intelligence because the technology disappears into the background,” says Takeda).

What computers are really good at is pattern recognition, being able to spot patterns in humungous amounts of data. Dave Coplin talks about businesses struggling with “the digital deluge”. The exponential growth in data that will come from the so-called internet of things will be solved by this computing ability to spot patterns, Coplin tells me.

And, in doing so, it will do away with human bias when pulling apar t data.

Counter-intuitively, the more data you have, the better the computer can spot patterns, seeing models that humans may have missed.

It also helps avoid the human tendency to impose narrative on data that may not be justified.

Cambridge used pattern recognition when

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The big interview Dave Coplin Chief envisioning officer Microsoft UK

I cannot imagine any industry that is not going to be revolutionised by big data Whether the weather A look at the research that predicts how environmental data will affect agribusiness and food retail – as well as developing new “smart plants” that are resistant to it ONE EXAMPLE of how Microsoft Research pays off in the commercial world is the work being done by computational ecologist Dr Drew Purves. Dr Purves, who studied at Princeton and Cambridge before joining Microsoft, is developing a computer model of climate change.

On the face of it, knowing where dustbowls will appear and which seas will rise has little to do with commerce. Yet the volume and complexity of data that Microsoft’s head of computational ecology handles can be used in other models – modelling nature is more complex than, say, modelling architecture.

“We’re faced with the challenge of looking at the world how it is,” says Dr Purves. “A lot of business works in the same way – you cannot regulate business to make it more predictable.

The predictive models that we work on may well fit into the commercial world and its thinking about sustainability.

“A lot of business decisions involve thinking about the environment, such as where to build your next shop. Any business decision will be affected by the environment. We’re helping them to make the right business-critical decision.”

For example, better environmental data will

help farmers predict demand from supermarkets, reducing food waste and therefore helping the environment. The same models that can predict huge environmental shifts can also be used on a micro level, predicting changes to how a stalk of wheat grows.

Dr Purves shows me a mind-boggling interactive map of Britain that he has worked on in his spare time, showing the best sites to build windfarms or avoid flooding. He talks excitedly about genetically modifying plants so they can be warned of impending storms or droughts by shining lights on them. Plants could be told to grow more roots quickly if a drought is coming, or shed leaves in the face of an oncoming storm.

Dr Purves’s vision of radio-controlled plants leaves my head swimming.

“And the beauty of it is that all this is that we can do all this in the computer, or ‘in silico’ as we say,” he says.

developing its beta Skype Translator product, which enables people in different countries to talk to each other in real time even if they cannot speak one another’s language. Microsoft previewed Skype Translator, translating Spanish into English just before Christmas. The translation improves the more people use it – or, put another way, the more patterns it recognises. Microsoft plans to extend Skype Translator to French and German.

“It’s a bit like the Babelfish in The Hitchhiker’s Guide To The Galaxy,” laughs Takeda. “A number of different technologies that have existed for a long time came together. There’s a piece of technology called Deep Neural Networks that dramatically improved the accuracy of speech recognition.”

Coplin adds: “Skype Translator is a good example of the transformational potential of big data and pattern recognition.” The ponytailed chief envisioning officer wonders half-jokingly if big data will do away the need for anybody to learn a foreign language. He says: “The thing for business is, ‘What are the patterns that are important to you?’ And how can you make use of them? That’s the big challenge for business when it comes to data.”

Coplin says the world is moving away from using data to reflect on the past and, instead, everybody will have to get used to spookily accurate predictions. This means using data proactively rather than reactively, he says.

“Prediction is a seismic change that will have a big effect on your business,” says Coplin.

Microsoft used predictive big data to correctly

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Big data

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BIG DATA INSIGHTS A 2013 Microsoft survey of 280 information technology decision makers at mid- to large-sized organisations revealed that…

62% of respondents store at least 100Tb of data

32%

expect the amount of data they store to double in the next two to three years

89%

72%

already have a dedicated budget for big data

have already begun the planning process

Source: microsoft.com/news, microsoft.com/bigdata

Dave Coplin portrait

by Andras Rac

forecast the outcome of the Scottish Referendum and Germany winning the 2014 World Cup. Coplin adds that whole new ways of doing business may be sparked by big data in ways we cannot foresee. Having lots of data does not only give you lots of information about your existing business, it provides new revenue models for the future. Business should not just use the technology to replicate what it has done in the past, stresses Coplin.

“I cannot imagine any industry that is not going to be revolutionised by big data. For me, it’s about taking an entrepreneurial approach.

It is up to businesses whether they are going to reach up and grasp this opportunity as opposed to just replicating what they’re doing now. Most organisations do not think about data in this way… data is the stuff you leave on the floor when you’ve finished doing business.

“My fear is that we’re in a place where we’re using technology to replace old ways of working, and that all we’re doing is the old Victorian way rather than realising its transformational potential.” For example, very few organisations look at data they do gather and see if they could sell it for repurposing elsewhere.

Happy accidents can happen when you put disparate data sets together, creating new business opportunities.

“The magic of data comes when you joi n toget he r multiple data sets, including social,” he says. Coplin suggests that when any business is beginning a new project, it

should think about the data that will be generated and how it could have multiple uses. A shop that installs CCTV to prevent shoplifting, for example, could also use that footage for measuring footfall, he says.

A lot of Microsoft’s big data work is predicting when existing technology will fail. Sending out an engineer before something goes wrong is less disruptive than technology failing and then having to be fixed. ThyssenKrupp uses Microsoft software to predict when its lifts will mechanically fail.

And the principle of predicting when machines will fail could be extended to human beings as well. Big data has huge implications for healthcare.

Microsoft Research worked with the University of Manchester on the genetic and environmental factors behind asthma. What came out was a technology being used in Clutter, an automatic Outlook mailbox clearing out system that launched in November. “It could be a nirvana for healthcare. There’s so much packed inside the term ‘big data’,” says Takeda.

Even today there are private companies that will offer to map your DNA, looking for common or known conditions such as cancer or obesity.

However, these companies only scratch the surface, analysing around 200,000 strands of DNA compared to the three billion making up the human body.

“Imagine what would happen when it’s possible to look at all three billion pairs and the cost of that falls to below $100,” says Coplin. “What we understand about our individual futures will fundamentally change.”

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The sky’s the limit for Met Office data power IMAGINE WATCHING around 10,000 hours of television without pausing to eat or sleep – that would take you over a year flat out. That’s the amount of data that the Met Office manipulates daily to produce weather forecasts. Currently, it stores a fraction of this – a total of 26 petabytes; this will rise to more than 300 by 2017. By comparison the large hadron collider stores about 100 petabytes.

In October the government announced it was funding the construction of a new Met Office supercomputer to the tune of £97million. Charlie Ewen, director of technology at the Met Office, has described what it does as gathering information so it can be “embedded in a whacking great computer model”.

The model that Ewen is referring to is what’s called the Unified Model (UM), a system on which the Met Office can predict tomorrow’s weather but also the longerterm effects of climate change. Looking ahead, the new supercomputer will also enable the Met Office to zoom in on everfiner detail – useful for customers such as Heathrow Airport, which needs precise predictions (for example, of fog, ice and crosswinds) in order to operate efficiently.

Aviation is one area where the Met Office already makes a contribution. It supplies wind speed forecasts and temperature charts for aircraft flying above 24,000 feet. The idea is to save airlines money by using upper atmospheric winds to push the aircraft along. One of the big expenses is fuel cost so accurate predictions can save huge amounts of money.

Spread out over three machine rooms, the High Performance Computer (HPC) will perform 16,000 trillion calculations a second, giving the Met Office 15 times its current computing power. It will be one of the most powerful computers in the world and the most powerful for weather and climate.

Ewen is not one of those evangelists who claims that big data will solve everything – for him, it’s all about the interpretation. “Big data is not the new currency,” he says. “The real value is in the information contained in the data.

Extracting it requires high-quality analysis as well as technology.”

No sooner had the government approved the 140-tonne supercomputer than Ewen and his colleagues started thinking about its replacement. “Science is constantly developing and we can clearly demonstrate the benefits to the UK of ongoing investment. The new supercomputer is only supposed to last for five years – this is the 10th supercomputer the Met Office has crunched through.”

Business Technology · March 2015

10

Big data

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Don’t overlook valuable payment data could improve your business. Receiving in-depth response chargeback codes may also provide clarity regarding chargeback challenges.

I

n a time when data is in greater abundance than ever before, payment data is one area that often gets overlooked by e-tailers. Data from the checkout and payment process can offer a valuable source of business intelligence, delivering insights that can then be incorporated into a strategy to help enhance profitability, customer experience and efficiency.

Our research shows that while most multichannel e-tailers have access to at least some payment data, only 50 per cent have access to all the relevant data they may need and 58 per cent lack checkout data visibility across all channels. Yet despite this, only 33 per cent of e-tailers questioned stated that they planned to invest in better analysis of customer data over the following 12 months (Dynamic Markets, Online Retail Challenges: 2014, March 2014).

In order to benefit from the wealth of payment data available, it is important to focus on the key target indicators that help drive business success. We have identified four areas where payment data can help boost operational efficiencies:

Authorisation analysis E-tailers should monitor how successful authorisations change over time in order to identify trends and adapt accordingly.

Recognising trends around unsuccessful authorisations – issuer specific, time specific,

Business intelligence Another area where payment data may be helpful is in ensuring that customer card data is up to date in a recurring business model. Payment data can also be beneficial when looking for patterns that precede a customer leaving a business for example, failed payments. Trending over time is important so it is critical to have access to BI to test your assumptions and react quickly.

reason codes – may help to improve overall authorisation success rates. This analysis can also help to identify where business comes from and may support development of a more tailored payment option to suit each market.

Fraud analysis Monitoring fraud rates on a regular basis can help detect changes and spikes in transactions volumes. It is also worth reviewing fraud rules to ensure that those currently in place do not

prevent genuine sales coming through the sales funnel. Additional potential efficiencies may be found from automating the review process.

Chargebacks Use payment data to detect particular products, payment types, locations or other common attributes that ultimately end up as a chargeback. Understanding chargeback rates may help to benchmark against the competition and implement changes which

Change is constant in the payments landscape and e-tailers need to ensure that they are working with a partner who can not only offer advice on today’s challenges, but can also provide guidance on how to navigate the challenges of tomorrow while maintaining a high level of security within a controlled and regulated environment.

For more information, contact Chase Paymentech 0845 399 1120 www.chasepaymentech.co.uk

Chase Paymentech Europe Limited, trading as Chase Paymentech, is a subsidiary of JPMorgan Chase Bank, N.A. (JPMC) and is regulated by the Central Bank of Ireland. © 2015, Chase Paymentech Europe Limited. All rights reserved.

Location, location, location: It’s still the main challenge to big data analysis

I

f you want your business to grow, and if you want greater understanding of land transactions, then you need big data.

Organisations already have vast amounts of data and, while many people think of maps as being old-fashioned pieces of paper, the truth is that location-based data is becoming increasingly important.

In the past, this was all done on spreadsheets, but today geographical data is in real time, that you can watch, manipulate and measure.

Companies talk about linking dynamic service provision with dynamic services. This is not just about co-ordinating things in real time but analysing that data afterwards.

For example, insurance companies need to be able to map flood risks and other potential building hazards.

Mortgage underwriters have to make location-based assessments about when and whether to approve home loans or not. High-street banks and retailers also depend on accurate location-based data.

Retailers need geographical information when planning a new store, while today banks may be looking to consolidate

high street branches. Another example might be a gas or electricity engineer knowing more about where he is being sent to, ensuring that he has the right equipment to complete the repair. Or closing a road well in advance and giving people warning, rather than a last-minute disruption.

Whether you are digging up a road, planning a new supermarket or building a block of flats, you need a co-ordinated approach. If you are involved in anything geographical, measuring the geography helps plan better services.

Ordnance Survey licenses a suite of products, including a range of open data products, right up to its premium dataset OS MasterMap, which is updated 10,000 times a day, making it the most detailed and accurate mapping product in the world.

The MasterMap is OS’s most comprehensive product, containing a suite of different layers, each of which provides a different aspect of valuable mapping data. It contains 450 million geographic features, from individual addresses to roads and buildings.

You will not find a bigger geographic database in the world, and this data can act as a platform for everybody

involved in a project. Ordnance Survey helped support the London 2012 Olympics and the Glasgow 2014 Commonwealth Games using this technology. On the private client side, Ordnance Survey has 350 partners it works with. These include Garmin, the in-car satnav provider, Esri, the Geographical Information System (GIS) software supplier, and Landmark, the European commercial and residential property data company.

And the future is going to be increasingly about location-based data, whether it is steering driverless cars or every connected device pumping information out in the internet of things.

OS does not only talk about the value of its data but its velocity.

It is all very well capturing so much geographical information, but the speed at which things change only gets faster. That is the new challenge.

There are not many organisations or business that would not benefit from location-based data.

Miranda Sharp is head of commercial sales, Ordnance Survey +44 (0)23 8005 5558 Miranda.sharp@os.uk

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Big data

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Inspector Dogberry One business that has resisted the inexorable rise of big data is the venerable Lloyd’s of London insurance market. Its directors still meet in the 18th century Robert Adam boardroom, overlooking the vast atrium where brokers scurry between desks placing business.

Lloyd’s has not been quick to embrace big data, and according to a report by Morgan Stanley and Boston Consulting Group the traditionally staid insurance industry as a whole is in danger of being left behind. The report highlights Germany’s Allianz

as a good example of an insurer transforming its business model through big data. It is investing €400-500million a year on digital initiatives such as setting up an innovation lab to work, among other initiatives, with big data.

Jon Hocking, head of the European insurance equity research team at Morgan Stanley, said: “Big data will change the types of data insurers use to assess risk, the way in which it is analysed, the way claims are notified and managed, and, ultimately the size and structure of the actual risk pools.”

Economists in Glasgow believe they can predict May’s general election result using Google search data after they accurately forecast the vote in last year’s Scottish independence referendum. Analysing live data on Google searches for the name Alex Salmond combined with commercial polling figures allowed the researchers to predict the yes vote would hit 45 per cent – five days before that actual result in the referendum on September 18.

Professor Ronald MacDonald, economist and currency expert at Glasgow University, said they were able to track the yes vote rise with several complex methods routinely used by financial markets to analyse Google big data trends in commodity prices and stock markets.

Better data could reduce home and motor risk pools – combined emergency funds that insurers can call on in the event of catastrophic loss – by 37 per cent to $62billion.

Lloyd’s of London once famously insured dancer Michael Flatley’s legs for £47million. Dogberry is proud to announce that his paws are covered by a similar policy.

Big data is not just the preserve of e-commerce, insurance companies and election pollsters. It is having an effect on the world of belles lettres as well. Matthew Jockers, a professor of English at Stanford University, has built a computer programme that can handle a huge amount of literary data.

It has analysed more than 40,000 novels and concluded there are just six essential plots.

Professor Jockers has yet to reveal what those plots actually are, though.

Almost half of UK consumers are worried that their data is not safe, according to Symantec’s 2015 State of Privacy Report.

Nearly 60 per cent have had a problem with data protection.

The report says that 53 per cent of people avoid putting personal data online in order to protect their privacy, while one in three give fake personal information to protect their identity.

Retailers and social media companies are the least trusted when it comes to keeping data safe. Medical institutions, followed by banks, are the most trusted.

Twitter: @dogberryTweets

By Matt Smith, web editor

Microsoft Azure http://azure.microsoft. com/blog/topics/big-data The people behind Microsoft Azure provide their thoughts on big data in this section of the cloud computing platform’s blog. As well as taking a look at related projects at Microsoft, the blog also provides practical tips and how-tos on how to get the most from your big data solution.

Big Data Transforms Business http://bigdatablog.emc.com/

The value of privacy The research also suggests that consumers are starting to understand how much their personal data could be worth.

More than 55 per cent of those surveyed valued their private information as being worth above €1,000 (£705), and 8 per cent valued it higher at above €10,000.

How can your business use big data analytics to make its marketing more efficient and innovative? What skills should you look for in staff that work with it? Find the answers to these questions and more on EMC’s Big Data Transforms Business blog, which is run by senior marketing manager Mona Patel.

By mastering risk, CEOs can increase their market share and corporate value, and create wealth.This summit, being held at the iconic British Museum in central London, will look at the best ways to reduce risk in a range of areas, including credit, fraud, payment, liquidity, compliance, cyber and even the weather. www.risktoreward.co.uk

Forrester Big Data http://blogs.forrester. com/category/big_data Research specialist Forrester runs this blog on big data in business. Its analysts’ recent posts explore the notions of open data and trust and how to prepare data ahead of processing, as well as posing an interesting question to those already using the technology: is big data enough?

Terracotta http://blog.terracotta.org

Databox (FREE – Android and iOS)

There are many business data dashboard apps on the market, but few do it with the clarity and style that Databox offers.

The Human Face Of Big Data (£2.29 – iOS)

This ebook app features more than 60 pages of essays, stories, infographics, photography and more to help put a human face to big data.

Wednesday, April 29 • The British Museum • London THE ALLEVIATION of risk is big business and business leaders increasingly need to incorporate risk management strategies into their everyday decision making.

11

For mo re inform ation a bout attend ing Ris k to Rewar d 2015 p le ase call +4 4 (0)2 0 8349 4363

Themes

Software company Terracotta runs a big data blog that explores both specific models and wider issues, as well as news in the technology industry, including ways to improve your business’s big data analytics, reports on cutting-edge research in the field, and a look at the internet of things-enabled future.

P Risk and innovation P Risk man agement strategy P Global operating exposure P Talent manageme nt P Corporat e risks P Risk gov ernance P Counter ing fraud P Cyber c rime

12 · Business Technology · March 2015

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INSIDE TRACK

London calling: Capital location providing true resilience

W

hether you have always been a traditional business and are seeking wider horizons for competitive advantage, or you belong to the online generations already analysing their data, how well positioned you are in the current revolution caused by big data will, if it hasn’t already, determine where you stand in the competition. How much do you understand both your existing and potential customers? Could you track their trends and behaviours? Do you know how they get information and what/who influences them? Could you predict their next steps so you don’t lose any existing customers, and gain new customers before your competitors do?

Big data has become more important than any analytics that anyone could ever imagine, and cloud-based analytics plays an imperative role in big data strategies, with the ability to enable optimised behaviour.

But, Every Cloud Needs A Home™, and it cannot be just any home. In order to effectively run rapid and complex analytics across massive datasets to get ahead of the game, the pressure is on

high-performance computing located in a 100 per cent uptime environment achieving essential scalability, flexibility and resilience in IT delivery. Having your IT infrastructure in the right data centre is therefore advantageous, if not critical, in supporting the evolving business model to satisfy your hybrid cloud needs.

The problem for the data centre industry, however, especially in central London, is that a significant proportion of available space is no longer fit for purpose and continued reliance on traditional technology models – from low-density racks to legacy CRAC cooling – will without doubt compromise the long-term viability of data centre space.

Which is why we created Volta Great Sutton Street (GSS) data centre to exponentially increase the availability of high-density, future-proof capability within central London. Location is always a key consideration.

At the heart of the UK’s internet infrastructure, with specially developed row-based cooling systems that can cool high-density computing racks (60kW plus per rack)

alongside low density networking ones, we are future-proofed for big data.

This modular system offers adaptable power during a project or business’s life cycle, allowing our customers to scale up and down their demand as and when they require without adding or reducing rack space. Two separate, on-site 33kV power supplies from two main grid substations provide two direct feeds on separate redundant rings, and together with diverse fibre connections, we are able to offer a level of true resilience that no other central London facility can match.

Given the limitations regarding power supply and difficulty of getting diverse entry points into a building in London, this kind of resilience is becoming harder and harder to achieve, creating potentially huge risks for big data process and analytics.

The right data centre, just like a suitable home, can help an organisation to better prepare in the harnessing of data and better realise the promise of big data in this new era.

Matthew Dent (left) is CEO of Volta Data Centres 020 7054 9390 sales@voltadatacentres.com

Exploiting ‘enriched’ payments data – a delicate balance?

I

nnovations in the use of data in payments processing and the drive to make financial data held by banks more accessible have the potential to benefit both consumers and the businesses that receive and process that data. But the uses these vast data sets can be put to, and the insights they can provide to lifestyles and spending habits, also have significant privacy implications.

The Payments Council has identified the use of more detailed or “richer” data as a key aspect of their payments roadmap, a vision to transform payments systems processes in the UK. By transmitting additional reference data such as copies of invoices, remittance advice, location data and details of goods and services purchased, suppliers could more easily associate payments with the correct transactions through automated invoice reconciliation, improving efficiency and reducing costs.

Consumers could receive more granular information relating to card payments and direct debits, making it easier to monitor spending and potential fraud.

The government believes greater use of data sharing and open data has the potential to radically boost competition and innovation

in banking. It believes that delivery of an open standard for application programming interfaces (APIs), improving the ability of third parties to access banks’ customer data, would enable service providers to develop services using that data.

Detailed profiling of personal data can be used to improve consumers’ understanding of their finances, helping them to make better-informed decisions. These innovations have the potential to extend profiling to encompass virtually every digital financial transaction. But profiling can also be used to further automate decisionmaking about customers, and target and process them more accurately – with the potential to significantly affect individuals.

The new Data Protection Regulation should introduce further protection in this area, but strong pragmatic guidance will be required from regulators to ensure that this richer data is only used in a transparent manner, and any profiling that has the potential to significantly affect consumers is subject to stringent controls.

Ian Stevens is a partner at international law firm CMS ian.stevens@cms-cmck.com www.cmslegal.com

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Creating new opportunities in healthcare

B

y 2020, all care records will be digital, real-time and interoperable” – that is the government’s goal stated in Personalised Health and Care 2020 (Nov 2014). To some, being able to access their own healthcare records electronically, adding comments and checking who has accessed those records, is appealing.

Integrating healthcare data so it is available in one place will be beneficial for healthcare professionals.

The research benefits of aggregating this amount of healthcare data are also compelling. Concerns over

privacy, in particular data sharing and anonymity (an issue for care.data), are likely to be paramount.

It is reassuring to learn from the Article 29 Working Party (Statement on the impact of big data, Sept 2014) that healthcare big data information services in many EU member states have already been addressed within the framework of existing data protection rules. The Caldicott Principles and the HSCIC Code of Practice (Dec 2014) both acknowledge that adherence to the Data Protection Act 1998, in particular maintaining

the accuracy of sensitive data and transparency over data sharing, are vital to big data success in healthcare.

New opportunities will be created for providers if individuals are able to add data from the new wave of lifestyle applications and wearable devices to their records, optimising big data in healthcare.

Emma Burnett is a partner at international law firm CMS emma.burnett@cms-cmck.com www.cmslegal.com

Get the basics right before you jump in at the deep end

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Busting the top five myths around cloud security

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here is little doubt that cloud computing has had a profound impact on our lives. It goes beyond consumer-focused cloud services, such as Dropbox and iCloud.

Companies are moving part, or their entire IT infrastructure to the cloud, changing the game on how products and services are delivered, purchased and consumed. It’s also opened up the debate around how to secure the applications and services that run on it – generating some common myths that need busting.

offering. However, security in the cloud is a shared responsibility between you and your cloud provider. The security of the servers and applications you put in the cloud are your responsibility and unfortunately for you, these are the areas that are most attacked.

Web application firewalls, network intrusion detection, log management and continuous monitoring tools are essential. You wouldn’t not have these in your on-premise environment, so why would it be fine to not have them protecting your cloud environment?

Myth 1 The cloud isn’t secure The reality is that most cloud platforms are more secure than on-premise environments. Cloud providers take security seriously: they patch regularly and secure their infrastructure and services with market-leading security technologies to continuously monitor and protect their offering. They receive threat intelligence feeds to keep a step ahead of hackers, and make sure vulnerabilities are remediated quickly as opposed to the weeks or even months it takes most on-premise environments.

Myth 3 I need more people to manage our cloud securitys Wrong. Headcount, budgets, skills and staff retention all impact a company’s ability to stay one step ahead of threats. But that is why many companies are choosing security delivered as fully managed services. This way they can rely on security analysts to continually monitor their security posture, make intelligent decisions on any vulnerabilities, and provide remediation plans to the customer.

Myth 2 Security is my cloud provider’s job Your cloud service provider is responsible for managing and securing the underlying infrastructure of their

Myth 4 The cloud makes me an easy target for hackers A hacker doesn’t discriminate whether your website is in the cloud or onpremise: you have something they want, and they will use all the tools

and techniques they can to exploit any vulnerabilities regardless. It isn’t about where your applications are located, but how you secure them.

Make sure you have a comprehensive security strategy that covers all your data centre environments, combining technology, big data security analytics, threat intelligence and security analysts. The ability to see, and respond to, vulnerabilities in real time is key: you can’t fix what you can’t see.

Myth 5 Securing the cloud is difficult Managing cloud security isn’t easy and some security vendors make it harder. Traditional “cloud washed” security solutions are not built in the cloud and don’t have the native functionality to be able to cope with cloud environments. The right cloudsecurity solutions need to work in multi-tenant environments, scale up and down as you launch and terminate cloud instances, integrate with cloud threat intelligence feeds, and provide continuous monitoring of your whole cloud environment to keep you secure.

If done properly, the cloud can be more secure that you can achieve on premise.

James Brown is director, cloud solutions architecture, AlertLogic www.alertlogic.com

ith all the hype about big data, many organisations have started investing in this area before exploring what options are available. While big data can clearly bring many benefits to some organisations, it is not essential for every company to invest in such high-end data analytics. Indeed, a study by Harvard Business Review entitled “You may not need big data after all” argues that some firms may actually be better off making use of information that is already readily available.

Most firms already know that they need to look beyond their own internal data – socalled small data – to gain the greatest business insights.

In fact, half of business executives now say that they spend more than 10 hours a week sourcing external business insights, according to a new survey released by InsightBee. However, despite this large amount of time spent on research, fewer than half of those surveyed (44 per cent) felt they could depend on the information they were able to find.

Cloud-based start-ups such as InsightBee are now aiming to close this

insight gap. These startups use a combination of research consultants and technology engines to help businesses gather information on companies, industries or on a specific business question. This vital business intelligence can then help companies serve their existing clients more effectively, win more business and react to market opportunities much more quickly.

The lesson here is clear: obtaining high-quality insights into customers and prospects is vital for firms of any size, but big data may not always be the answer. Many firms – and small-to-medium enterprises in particular – may be better off using tools that provide incredible research power, but with much lower overheads. Before diving into the deep end with big data, these businesses should consider maximising the potential of the information that is available to them right now.

Manoj Madhusudanan is managing director of InsightBee 020 3695 5555 support@insightbee.com

Business Zone

14 · Business Technology · March 2015

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COOL IT! How climate control is central to the LD6 smart data centre

The future

Big data’s ‘elephant in the room’…

N Video special

Neil Murray, managing director, corporate services, Sodexo UK&I, talks about the importance of a people-centred approach for successful facilities management. http://business-reporter. co.uk/videos/2015/01/ sodexo-deliveringquality-of-life-services/

ot many people understand the many and varied aspects that comprise Hadoop, and even fewer know that Hadoop the technology was actually named after the favourite toy elephant belonging to its founder’s son.

To the majority of the tech-savvy population, Hadoop has come to represent a by-word, synonymous with big data, but few truly understand its origin story, or indeed the many and varied benefits of it.

Apache Hadoop (to give its full name), was initially inspired by a series of papers published by Google outlining its approach to handling its own avalanche of data. Since its initial market release it has become the de facto platform for enterprises and public agencies looking to store, process, and analyse hundreds of petabytes (or even zettabytes) of complex data.

As 100 per cent open-source software, Hadoop enables storage, management, processing, and analysis of huge amounts of data. Being based on the Google model, it uses standard industry computer servers that can be configured to scale without limits.

Although Hadoop was a relatively early entrant to the big data space, its foundations in the open-source school of tech theory has been an instrumental part of its current success.

Hadoop’s continued success seems assured, with more and more opensource projects, software, and standards eroding the traditional position of proprietary and hardware-based products and no end in sight to the exponential growth of data flows.

The digitalisation of everyday consumer and professional life has created a data tsunami. Just to give this some context, it is reckoned that in 2015 the average UK citizen will consume more information in one day than someone from the middle ages did in an entire lifetime.

This has, unsurprisingly, impacted a number of industries, and there are few that have been affected so much over the last decade (especially since the advent of the iPhone) by these developments than the telco space. It stands to reason, therefore, that for mobile network operators (MNOs) looking to engage new customer bases, reduce customer churn, improve customer experience, and

monetise new offerings, that the effective understanding and use of big data is proving invaluable.

A number of the biggest global operators already use Hadoop to manage their big data streams: monitoring, assessing, and analysing sentiment on call logs and social media; real-time analysis of call data records; customer experience and churn management; cellular resource optimisation modelling; network usage analysis and routing; fraud detection; mobile passive data collection; and analysis for predictive modelling.

In a space that is being shaped as much by its customers as the actual technological advances themselves, the requirement for MNOs to remain ahead of the curve has never been more pertinent. Operating in such a crowded and competitive arena, the use of big data and Hadoop is providing MNOs with the competitive edge that they need to succeed in the digital business environment they now inhabit. Long may it continue! +44 (0) 20 3178 4857 www.cloudera.com

Equinix, one of the world’s largest data centre operators and internet exchanges, is set to open its sixth London data centre, LD6, in Slough.

The company will use Munters Oasis Indirect Evaporative Coolers at both sites to achieve world leading sustainable server climate control, meeting the demand from Equinix’s customers in financial services, cloud and enterprise segments.

LD6 aims to be accredited in leadership in energy and environmental design (LEED) to platinum level.

Some 40 Oasis IEC 200 systems including four MUA units for LD6 Slough are at the heart of Equinix’s air treatment design, and will contribute towards lower energy consumption and carbon footprints. Munters Oasis IEC 200’s will supply more than 8MW of cooling for the IT Load for the first phase of LD6. The new LD6 data centre will provide a capacity of 8,000 square metres equivalent to housing 2,770 server cabinets.

Equinix’s investment in the LD6 data centre uses Oasis’s award winning innovative patented indirect evaporative heat exchanger and 100 per cent natural ventilation.

Russell Poole, managing director of Equinix UK, said: “LD6 is a hugely exciting project. The facility will be the most advanced data centre in the UK. We are committed to providing continuous improvement for our customers and set new standards in efficiency and sustainability.”

• High efficiency cooling • Annualised cooling pPUE of 1.06 • Fully separated air • Use of any fresh water type • Annualised project PUE of 1.2 Read the full case at www.munters.com/equinix +44 (0) 1480 410223 airtreatment@munters.com

Business Technology · March 2015 · 15

AN INDEPENDENT REPORT FROM LYONSDOWN, DISTRIBUTED WITH THE SUNDAY TELEGRAPH

Safeguarding an ethical supply chain

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ohn Lewis has implemented a web-based software product called “Lighthouse Ethical Trade” from ediTRACK to manage its ethical compliance programme and to provide real-time business reporting.

John Lewis sells more than 350,000 product lines across 50 different product categories sourced from more than 50 countries and the subject of working conditions is one that it takes very seriously. The John Lewis Code of Practice on Responsible Sourcing sets out in detail the standards that it expects its suppliers to meet on labour standards, the environment and animal welfare. It requires suppliers not only to obey the law, but also to respect the rights, interests and wellbeing of their employees, their communities and the environment.

With the complexities of managing a global supply chain, John Lewis needed a system that could easily interrogate and trend data as well as provide enhanced reporting functionality to track progress.

Lighthouse Ethical Trade was a perfect fit. It could be implemented

quickly and, due to its intuitive design, John Lewis could be up and running quickly with minimal training. Being web-based, it’s accessible for sourcing offices and partners via logons which are managed by the central team at John Lewis. It holds a database of all suppliers and factories, along with the often complex relationships between them.

It provides alerts when audits are due and complete visibility of suppliers and their factories audit results.

John Lewis can see the status of its supply chain in a few mouse clicks. Dashboards show a workflow of tasks required within a given time-frame, and dynamic reporting tools enable management to see the status of all its factories. The reporting wizard enables reports to be set up quickly and run instantly, significantly reducing the time required to collate reports for internal meetings and external assessments.

Using Lighthouse Ethical Trade has had a positive impact on productivity and assists John Lewis in safeguarding its supply chain.

About ediTRACK ediTRACK is a global supply chain solutions provider with

more than 20 years’ experience in developing, implementing and hosting web-based software for companies wanting to gain superior control and visibility of their business processes.

Its software links the systems of organisations and their partners within industries such as retail and insurance, helping them to drive efficiency, quality and compliance in complex and global supply chains.

Insurance solutions are provided to insurers and their suppliers to help them gain visibility of their claims supply chains to reduce bottlenecks and improve customer service. Today, its solutions are used by two of the top 10 global insurers as well as Lloyd’s of London insurance syndicates.

Retailers including Mint Velvet and John Lewis use ediTRACK’s “out of the box” subscription-based software Lighthouse to enable the efficient management of supply chain processes such as sourcing, production and delivery. As a result retailers benefit from shorter lead times without compromising their commitments to product quality and ethical working standards.

01753 485100 www.editrack.com

Get ready to feast: the world is eating software

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uperstar investor Marc Andreesen was famously quoted as saying that software is eating the world. But he may have had that exactly backwards: the world is eating software. The smartphone in your pocket is the start of a prosthetic brain – today helping you remember important dates, navigate, and take notes.

Now, we’re imbuing everything around us with that kind of intelligence.

Consider the lowly beacon – a small, inconspicuous device with a battery life of three years, it can measure and transmit information about its surroundings. Or Affectiva, software that measures human emotions in video by capturing microexpressions. Or Shazam, a popular mobile app that can name a song from just a few seconds of audio.

Each of these is a sensor. A beacon can track people nearby, market to them, and record their actions. Affectiva can tell who on a conference call is unhappy. And Shazam can predict within hours of a song’s release whether it will be a breakaway hit.

Here’s the thing about all

the intelligence we’re putting into the world: when we use it, we leave a digital breadcrumb trail. And when software analyses those breadcrumbs, it can do amazing things.

The so-called internet of things is the other half of the big data movement; the marriage of the two will transform us as individuals, organisations, and even as a species.

That might sound like mere hyperbole but when you consider the challenges humanity is facing – climate collapse, population growth, newly resistant and emergent diseases, conflict, ailing medical systems, and so on – the pairing of ubiquitous sensors with big data might just save us.

That’s one reason big data is such a hotbed of commercial activity. Business has always been about striking a balance between risk and reward, and if data can predict the future, even slightly, then it can reduce the risk and increase the reward.

Here’s an example: Next Big Sound, a data startup that analyses music data from airplay, social networks, streaming platforms, and more, has tried to predict which songs will be on the Billboard top 200 in the following year. It does so surprisingly well, predicting 108 out of 200 chart-toppers,

compared with radio (78 predictions), online plays (66) or social networks (55).

If you’re an industry insider, better data analysis means less risk and more profit.

There’s also no doubt that big data has gone mainstream. Once the domain of finance and advertising, now every industry is transforming itself with data. I run the Data-Driven Business Day at O’Reilly Media’s Strata+Hadoop World conference (strataconf. com/uk), and in the last four years we’ve seen speakers from entertainment, energy, education, healthcare, manufacturing, environmental analysis, humanitarian aid, library sciences, gaming – virtually every commercial vertical – talk about

how they’re putting data to work.

In the coming decade, the world will eat software – and businesses that don’t join the meal will be left to starve, unable to navigate an increasingly connected, data-driven marketplace.

Alistair Croll (left) is an entrepreneur, author, and speaker working on big data, cloud computing, and startups; his books include the best-selling Lean Analytics.

He chairs O’Reilly Media’s Strata + Hadoop World conferences, coming to London May 5-7, 2015 @strataconf www.strataconf.com/uk