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Data are the raw materials ofthis age of information,whether in such structuredform as ATM transactionsand till receipts, or unstruc-

tured such as trends on social mediafeeds and sites.

Business intelligence and data min-ing and warehousing applications ena-ble companies to gain insights frominformation that has mostly been gen-erated internally. Modern analytictechniques, including examinations of“big data” – the mass of informationgenerated by all kinds of commercialand other activities – expand this con-cept by asking questions of both inter-nal and external information almostas soon as, and in some cases evenwhile, it is being generated.

Companies are using these tools toimprove business efficiency, spot

trends and opportunities, providecustomers with more relevant prod-ucts and services and, increasingly, topredict how people, or machines, willbehave in the future.

For example, General Electric’scustomers are using its ProficyMonitoring & Analysis Suite, an inte-grated set of software for industrialdata management and analytics, tomonitor equipment and process datato improve performance.

GE’s Proficy Historian HD, one ofthe six software modules in the suite,lets companies store very large datasets in a Hadoop cluster (manymachines running open-source soft-ware Hadoop that can handle massiveamounts of unstructured data) andthen run advanced analytics on hugeamounts of data to improve perform-ance, troubleshoot problems, and

predict and prevent failures inmachines such as turbines or jetengines.

“We use the software ourselves inour own monitoring and diagnosticscentres to manage trillions of dollarsin asset value,” said Brian Courtney,general manager of GE IntelligentPlatforms’ Industrial Data IntelligenceSoftware group.

The market for business intelli-gence, corporate performance man-agement and analytics applicationsand performance management soft-ware – much of it provided by the “bigfive” of SAP, Oracle, IBM, SAS andMicrosoft – has grown rapidly. Spend-ing totalled $12.3bn in 2011 and grewabout 7 per cent last year, accordingto research company Gartner.

Many companies use businessintelligence software to provide theirsenior executives, sales staff andother managers with access to keyperformance indicators such as costs,sales and margins.

Among the leading trends in themarket for business intelligence soft-ware is the increasing call for screen-based visualisation tools, such as dash-boards, to make financial and otherdata more accessible to executives onthe road via smartphones and tablets.

“We saw a new way to engage withpeople and democratise data,” saysQuinton Alsbury, founder of Roambi,which provides mobile business intel-ligence visualisation software foriPhones and iPads.

Pret A Manger, the sandwichretailer, uses Roambi in the UK toaugment its traditional business intel-ligence software and has provided 70field and regional managers withiPads. Staff can carry out stock takeswhile they are on the move instead ofleafing through a 200-page paper file,or they can monitor kitchen produc-tion while standing on the shop floor.

Similarly, SiSense’s Prism 10X soft-ware is designed for companies thathave outgrown Microsoft Excel andneed an integrated analytics suitecapable of handling huge volumes ofdata without having to rely on the ITdepartment for assistance.

Perhaps the most dramatic trendhas been the move from data mining

Continued on Page 2

Big data putunder thespotlight asnever beforeAnalytics can remove the guesswork fromdecisionmaking but companiesmust knowwhat information they need, writesPaul Taylor

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and warehousing – the useof powerful software tointerrogate stored informa-tion – towards big data.“The origins of data ware-housing lay in data setswhich, at that time, wereimmediately relevant tobusiness problems,” saysDuncan Ross, director ofdata science at analyticsprovider Teradata.

“Specifically, this com-prised data that could beput into tables of rows andcolumns and linked in arelational form.” By itsnature, this limited thetypes of data being storedmostly to highly structuredforms.

While they are still a partof big data analytics, muchof the information beingtapped is unstructured.This may include data fromsocial media, aboutweather, geography, mobil-ity, from sensors and manyother data sets that canenhance understanding.

Using Facebook data, Jap-anese online and catalogueretailer Nissen was able toglean detailed insights intocustomer likes, dislikes andbuying motivations. Tera-data’s Mr Ross says: “Bylinking this external datawith its established internaldata, [companies] are effec-tively broadening their win-dow on the wider world.

“Each time more data areadded, this window growslarger, affording the busi-ness a clearer view of themarket.

“This allows them to testideas and make betterdecisions and predictions.Crucially, it can also enablethem to break away fromsmall, incremental improve-ments towards innovationsthat will transform theirbusiness.”

For companies and otherorganisations at the cuttingedge of big data analytics,the main goal is to be ableto use the intelligencegleaned from analysinglarge volumes of informa-tion to predict and antici-pate future trends.

Leading US banks such as

Continued from Page 1Wells Fargo and Bank ofAmerica, consumer goodscompanies such as Coca-Cola and 3M, and retailersincluding Walmart are allusing big data analytics toimprove the running oftheir business models andto anticipate changes indemand before they actu-ally occur.

Scott Schlesinger, seniorvice-president and head ofbusiness information man-agement for the technologyconsultancy Capgemini inNorth America, says: “Pre-dictive analytics can turnpoor business decisions,made using haphazardguesswork, into wellthought out and successfulbusiness decisions thatimprove performance.”

He also warns that to usepredictive analytics toolswell, an organisation mustfirst know what informa-tion it needs, and devise “aproper information andbusiness process strategythat drives and [delivers]efficiencies across theorganisation”.

Eddie Short, head of dataand analytics at manage-ment consultancy KPMG,sounds a similar cautionarynote. “Three years ago,some commentators sug-gested that data wouldbecome the new currency ofbusiness, almost on a parwith capital and labour,” hesays.

“Since then, informationhas clearly moved to thecore of most organisations’operations, but questionsremain about how toextract real value becausethe journey from traditionalbusiness analytics to [databecoming a] business ena-bler requires organisationsto fundamentally rethinkhow they collect, analyse,distribute and monitordata,” Mr Short adds.

“In my view, three yearsfrom now it will be thebusinesses that haveanswered these questionsby combining their hungerfor data with an appetite tomatch it with the needs oftheir businesses that willwin the day and becomemasters of their own data.”

Big data put underthe spotlight

On FT.com »TransformingindustryMobile technologyis changing theface of healthcareft.com/mobilehealth

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Asignificant shift has beentaking place in the audiencefor business intelligencetools. Traditionally, highlytechnical users in informa-

tion technology departments haveused these tools to produce descrip-tive reports and queries for otheremployees. Now, the trend is towardsa mixture of software and devices thatallow less technically skilled staff tomake diagnostic analyses based ontheir own explorations of data.

Such thinking is changing the waycompanies invest in business intelli-gence tools, according to DanSommer, an analyst with IT marketresearch company Gartner.

The latest “data-discovery” toolswere pioneered by business intelli-gence specialists such as Tableau Soft-ware and Tibco Spotfire but their suc-cess has prompted others to enter themarket. Large providers such asMicroStrategy, Microsoft and SAShave built or acquired their own data-discovery tools.

These make exploring data a moreintuitive process for non-technicalusers. In particular, most offer visuali-sation features that allow data to bepresented in formats such as graphs,maps and dashboards, says PeterLumley, a business intelligence expertat PA Consulting.

His team has mixed supply chaindata with a map of a client’s ware-house to create visual displays thatshow staff how well stock and deliv-ery processes are working and whereproblems occur.

“Data discovery is all about turningdata into actionable information, atthe point of need, by presenting it tousers in way that is more appealing,more engaging and generates moreinsight,” Mr Lumley says.

According to Mr Sommer, such sys-tems are rapidly becoming a main-stream part of corporate businessintelligence and now play a centralrole in companies’ plans to refresh,upgrade or overhaul their data analy-sis processes and systems.

Last year, Aggregate Industries, theconstruction materials company,decided to retire its elderly businessintelligence platform and replace itwith data-discovery tools from anexternal provider. Mike Gibbons,Aggregate’s chief information officer,says the aim was to make businessintelligence a “self-service function”.

“We wanted to give users in thebusiness more power. We wantedthem to be able to go off and get theanswers they needed without a help-ing hand from IT or a call to theservice desk when they got stuck,” he

says. “But above all, we wanted anapproach that would allow users toexplore more data, more frequently,and dig down into it more effectively.”

The tools were provided for execu-tives in the form of an application thatenabled them to explore the monthlyfinancial performance of their divi-sions and compare their costs andprofits with other business units.

Another application allows salesmanagers to measure customer loy-alty, not just on the basis of howmuch individual customers spend, butalso how quickly they pay invoices.

The introduction of high-perform-ance analytics at Frankfurt airport inGermany is helping to increase thefrequency of passenger flow analysisfrom just once a day towards two tothree times an hour, says Dieter Stein-mann, senior manager of informationand communications services at air-port authority Fraport. An estimated57m passengers a year move throughthe airport’s terminals. The companyis working with its analyticsprovider to add a data-discovery layerthat will enable Mr Steinmann andhis colleagues to apply relevant ana-lytic apps more widely – to groundstaff and baggage-handling teams,for example.

If data discovery is about shiftingbusiness intelligence from a descrip-tive to a diagnostic process, as someanalysts say, the next step is to makethis predictive, so that users cananticipate changes in business condi-tions in advance and make the neces-sary preparations.

This is the path that fleet-leasingand management company ARI FleetUK has taken, using tools from SAP.

The products are used by ARI togather data from the units on vehiclesthat it leases to clients such as logis-tics company FedEx and builders’merchant Travis Perkins, along withinformation about fuel card usage,accidents and maintenance work. Theinformation is then presented to cli-ents in the form of individual, self-service dashboards (multiple screenscontaining information and data).

This approach keeps clientsinformed about issues such as thehours drivers spend at the wheel andincidents of harsh braking.

In future, predictive analytics willenable businesses to anticipate theeffects on fleet management costs ofvehicle downtime, adverse weather orchanges to delivery routes caused byroadworks. “Predictive analytics willenable us to help clients run theirfleets even more efficiently, by keep-ing them one step ahead of potentialproblems,” says Keith Allen, ARI’smanaging director. “The cost of down-time with medium or heavy-dutytrucks can be considerable,” he says.

“So there is tremendous power inbeing able to tell a client that, forinstance, there is an 85 per centchance that a particular part is goingto fail in the next 2,000 miles, basedon data gathered from other trucks ofthe same make and model, runningsimilar routes in similar conditions.”

All aboard for journeys of discovery

Fast track:Frankfurt airportanalyses flows ofpassengers withgreater frequencythan before

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Management

User-friendly formats allowless technical staff to exploreinformation more easily,writes Jessica Twentyman

FINANCIAL TIMES WEDNESDAY JUNE 26 2013 ★ 3

The Connected Business

As with the industrialrevolutions of the past, thehuge technological changestaking place around us canseem threatening and

confusing, especially when they comecouched in language that isseemingly incomprehensible to manypeople. Here is a short guide to what“big data” and business analyticsmean for businesses.

DefinitionsBig data is a term used to describeinformation of an order of magnitudefar greater than has beenencountered before. Typically, thedata come from social media such asFacebook or Twitter, or vastnumbers of connected devices,including satellites, closed-circuittelevision cameras, audio and videorecording equipment, paymentterminals, mobile phones andsensors.

There are an estimated 5bnconnected devices in the world, atotal that is expected to rise to 20bnby 2020, all of them gathering andcreating data.

Analytics exploits the storagecapacity and power of technology toprocess information at high speed,

and deploys mathematical algorithmsto spot valuable data.

“What previously might havetaken days or weeks can now bedone in hours or even minutes,” saysMark Wilkinson, managing directorof SAS UK and Ireland, a businessanalytics software company.

Anthony Deighton, chieftechnology officer at QlikTech, a USbusiness intelligence softwarecompany, compares analytics tolooking at a cell under a microscope.“Before it is under the lens, it issimply . . . tissue or blood cells,” hesays. “But with a microscope, onecan make sense of the smallestrelevant parts of the DNA to createmiraculous insights.

“That’s the way it is with big data.When you can isolate and compareparts of the data, it becomes useful.”

HistoryThe term big data was coined byGoogle, according to Eddie Short,head of the business intelligencepractice at KPMG, the consultancy.“But in reality, it started with thefirst satellites and space exploration.”Physicists alone are collecting moredata in a few days than previousgenerations together accumulated

throughout history. The sheervolume of data and the way it isprocessed mean it is about lookingfor probabilities rather thancertainties, says Mr Short. “We arenow having to eliminate what isunlikely and improbable, as opposedto identifying exact answers.”

The commercial exploitation of bigdata is in its infancy. According to areport by Vanson Bourne, a UK-based technology research company,and Interxion, a European providerof data centre services, only aquarter of European organisationshave built a business case for bigdata. But more than 90 per cent of

companies that have an informationtechnology strategy aligned withtheir business plan have explored it.

BenefitsBusinesses can find out whatcustomers, suppliers and competitorsare saying and doing, often in realtime. They can predict moreaccurately what is likely to happen.

This presents opportunities tocustomise products and services andbetter integrate with suppliers overdevelopment and delivery, says MrShort. “An organisation workingeffectively in a big data culturebecomes dynamic and innovative,

ultimately selling more, moreprofitably, or delivering moreeffective services.”

The benefits are so significant theyshould be taken into account byeconomists measuring gross domesticproduct and by government policymakers, according to a report by theCentre for Economics and BusinessResearch, which says recognising thevalue of data goes beyond companyinterests – it is vital in valuingnational economies.

RisksBig data and analytics do not offercertainty. Because you are dealing

with eliminating the most unlikelyelements and examining probabilitiesand correlations, there is always adanger of missing somethingessential, says Mr Short.

Another risk is that data are socomplex that they can only be usedby data scientists. Analytical toolsneed to be easy to handle, with theirfindings clearly visible, so that non-technical users can gain insights.

If this becomes mainstream, thepotential is limitless, says MrDeighton. “You can give staff theirown ‘microscope’ to make the nextbig discovery that . . . transforms acompany, an industry or the world.”

Treasure can befound hidden ineveryday detailsGuide Jane Bird helps to define terms in thenew era of business intelligence and analysis

Customer selectsand scans product

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Data captured byscanner and sentfor analysis

Checkout instantly prints customised offers intended to encourage customer to return within five days

Collecting Big Data How it works

Research: Jane Bird FT Graphic/Dreamstime

Adds information about product sales to other sales data to monitor stock levels

Customer walking past supermarket enticed in by special offers sent to mobile phone

Supermarket sends messages to other retailers suggesting they send offers

Loyalty card data linked to personal information sent for analysis

Data collected and analysed by the supermarket

Santander is an elegantcity on Spain’s northerncoast whose surroundingmountains are said to glowat sunset. But it is whenthe sun goes down that thetrue magic happens.

Street lampsautomatically dim whenthere is a full moon orwhen the road is empty,bins send an alert to beemptied when they are fulland drivers are directed tothe nearest free parkingspaces. It is all due to anexperiment involving 12,000sensors installed across thecity, measuring everythingfrom light, pressure, CO2levels and humidity, to themovement of people, publictransport and cars.

Santander is a connectedcity, one that is smart.

A living picture of thecity is created throughconnecting these separatebut interconnected pools ofdata and analysing themcan transform howSantander operates and itsinhabitants live. This“smart city” is just oneexample of how big dataare going to transform ourworld.

An expanding amount ofdata are being created asmore people, devices andthings become connected –we have entered the age ofthe “internet ofeverything”, also called“the internet of things”, aworld where there arealmost twice as manybytes of digital data asthere are litres of water inall the world’s oceans.

It is not the amount ofdata that is important; it iswhat is done with it.

Using analytics, artificialintelligence and machinelearning technologies tocollect, connect and crunchenormous, disparate datasets is what will underpinnew waves of economicgrowth, innovation andhuman endeavour.

Big data offer three hugeopportunities: they willbring new insight, helpingus understand the worldand ourselves in a waythat we never could before;they will enable an era ofinnovation; and they willlead to the creation oftransformative services,changing the way we dothings. Fundamentally,they will change societyand what it means to behuman. Analysing big datasets can provide incrediblypowerful results. Take anexample about how it cantransform the way wetackle bullying. Universityof Wisconsin researcherscreated a machine learningalgorithm – a system thatcan learn from data – to

spot bullying among the250m daily posts onTwitter.

It found 15,000 bullying-related tweets a day andwas able to identify thebullies, their victims,accusers and defenders.This type of big datainitiative could be used toidentify children in need ofhelp and intervention.

Another project,involving the mobile phonedata of 50,000 peopleshowed that it was possibleto be able to predict thefuture locations ofindividuals with 93 percent accuracy – a showcaseof how big data bringgreater understanding ofhuman behaviour.

The pace of technologicalinnovation is at timesscary as it challenges ourunderstanding of what itmeans to be human.

When automobiles were

first invented, someonewas legally obliged to walkin front of cars carrying ared flag. It is ridiculousthat you would want torestrict a vehicle to thewalking pace of a man. Weface a similar inflectionpoint now with therevolutions possible withbig data.

Take learning a foreignlanguage. It is acornerstone of mostchildren’s educationaround the world but wehave to ask whether this isnow redundant.

Many would balk at thissuggestion. But big data,coupled with machinelearning, power instantlanguage translationservices, accessible on ourmobile devices, that up tonow have worked prettywell with text. These willsoon be able to translatelive speech almostperfectly in real time.

So should we bother toteach children a foreignlanguage when bigdata-powered technologycould soon do it better andmuch more efficiently?

As a society we have toaddress these types ofquestions just as we haveaddressed them at similarmoments in our evolutionto date – notably theintroduction of cheappocket calculators andtheir disruptive role inmaths education in the1980s.

Big data provides theopportunity to change theway we live and the worldthat we live in. It can helpsolve some of society’sgreatest challenges butmoral, cultural andconsumer concerns need tobe properly understood andaddressed before the fulltransformative potential ofbig data can truly berealised. Big data willchange humanity ifhumans allow it to.

The writer is chiefenvisioning officer atMicrosoft UK

Paul TaylorEditor, the ConnectedBusiness

Bede McCarthyTechnology correspondent

Jane BirdJournalist specialising intechnology and business

Michael DempseyJournalist specialising in ITand defence

Jessica TwentymanFreelance journalist

Emma JacobsBusiness Life reporter

Adam JezardCommissioning editor

Andy MearsPicture editor

Steven BirdDesigner

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Information deluge haspower to change us allOpinionDAVE COPLIN

An algorithm found15,000 bullyingtweets a day andidentified victimsand their accusers

4 ★ † FINANCIAL TIMES WEDNESDAY JUNE 26 2013

The Connected Business

Lausanne­based nVisoemerged from a Swissresearch project intomodelling humanperceptions of emotion asshown by the smallest facialexpression. Now it hasturned to IBM’s cloud­basedservices to analyse its digitaldiscoveries to predictbehaviour.

By filming people in focusgroups to capture eachmuscle movement, astatistical model is built up,with the human facemapped via hundreds ofreference points. Theexpressions are scrutinisedby nViso’s algorithms tointerpret people’s feelingsafter being streamed from awebcam into the cloud. Theirprimary emotions are whatmarketing agencies the worldover pay nViso to uncover.

Tim Llewellynn, co­founderand chief executive, says hehas “built a system thatdetects emotions in real

time, and emotions predictbehaviour”. Cloud­poweredanalysis means buyingintentions emerge frompeople’s emotionalengagement. Reactions to aplanned marketing push canbe measured and used torevise the campaign.

What IBM’s cloud servicebrings to the research is anability to increase and

decrease the amount ofanalysis without capitalspending or waste. Theeconomics of the cloudmake nViso viable. “We’dnot have been able to deploythis without the cloud. Now,we can do this work on aproject basis and offer totest a product’s prospectsfor as little as $10,000,”says Mr Llewellynn.

Data analysis is of littleuse if you cannot act onwhat it reveals. The instantconnection to IBM’s cloudallows nViso to break downbarriers to understandingwhat it defines as our sixprimary emotions: happiness,surprise, fear, anger, disgustand sadness.

“It’s about much morethan detecting a smile,” saysMr Llewellynn. “Humansaren’t binary; we have toperceive subtle reactions tominor changes.”

Michael Dempsey

Case study Face mapping gets to heart of consumer emotions

Visage aware: nViso at work

Technologies such as bigdata have transformed busi-ness intelligence from thestuff of stodgy analystreports to an instant streamof information that helpseverybody from sales repsto chief executives.

Such data are often mostuseful in the field, which iswhy many companies areequipping employees withbusiness intelligence appli-cations for mobile use.

Companies have alwaysused data in live situations– in mining and geology forexample – but it was oftentied to laptops and requiredspecialist skills to interpret.

But the rise of affordablecloud solutions for analyt-ics, coupled with the arrivalof smartphones and tablets,made it possible to usemobile intelligence withouta large investment in serv-ers or staff training.

“The barriers to entryhave changed,” says IanCohen, group chief informa-tion officer at Jardine LloydThompson, the risk, insur-ance and employee benefitsspecialist. Mr Cohen saysJLT equips its consultantswith mobile analytics sothey can work with clientsto deal with issues on thespot, rather than gatheringinformation and taking itback for analysis. The keydifference is presentation.

“It’s a visualisation ofdata in a way that people

can see, touch and move.The days of analysts sittingbehind screens in big officescrunching data have gone,”Mr Cohen says.

The technology can bene-fit almost any business.Retailers can see sales fig-ures from the shop floor. InColchester in the UK, anNHS hospital is trackingthe efficiency of its accidentand emergency service.

Vendors say such toolsare popular with execu-tives, who want updateswhile travelling or to accessdata in meetings withouthaving to request it.

So it is no surprise thatmobile business intelligenceis now a $13.1bn market.According to Gartner, the

IT research company,spending on business intel-ligence, information man-agement and analytics soft-ware rose 6.8 per cent lastyear, and 17 per cent theprevious year.

This coincides with a risein demand for staff who caninterpret business data inthe field – a skill, Mr Cohensays, is in short supply.

He says: “The person youhave at headquarterscrunching data might notbe the same one you wantto put in front of a client attheir office. You need tohave people who are moreadept at data, who knowwhat they’re looking for

and ask the right ques-tions.”

The sector is dominatedby traditional vendors suchas SAP, Oracle and IBM.But the shift to mobile hasprovided an opportunity forsmall cloud-based compa-nies such as Salesforce inthe US and Sweden’s Qlik-Tech to gain a foothold.

“The new companies havegained huge traction by vir-tue of their simplicity, visu-alisations and dashboards[multiple screens], so thatother more traditional anal-ysis-driven companies arebeing challenged to keepup,” says Mr Cohen.

Sean Farrington, manag-ing director of UK and Ire-land for QlikTech says: “Wealways demo on a mobiledevice, because we haveseen that is an expectationof senior executives – theydon’t want to access infor-mation any other way.”

Mr Farrington says Qlik-Tech has 28,000 customersbecause of good data visual-isation and allowing usersto inspect it with simplequestions. “It’s that ques-tion-based method ratherthan delivering informationin a standard formattedreport. When you’re a busychief executive, you don’twant to spend the time orhaven’t the patience tolearn a tool.”

Carrying sensitive dataon mobile devices can leavecompanies vulnerable ifdevices are stolen or lost.

However, Mr Farringtonsays the web-based natureof products means suchdata need not necessarilybe stored on phones or tab-lets. “That’s why we delivervia a browser, so if you loseyour mobile device thereare no data on it.”

Answers are just a call awayMobile devices

Analysis is nowavailable to anyone,anywhere, reportsBede McCarthy

‘You need to havepeople who aremore adept at data,who know whatthey’re looking for’

The jacket for Eric Siegel’sPredictive Analytics: thePower to Predict Who WillClick, Buy, Lie, or Die,contains a description ofthe “omnipresent science”of predictive analytics asaffecting “everyone, everyday. Although largelyunseen, it drives millionsof decisions, determiningwhom to call, mail,investigate, incarcerate”.

It is an ominous phrase,coming at the same timeas Edward Snowden’sclaims that the NationalSecurity Agency hadaccess to information fromthe servers of internetcompanies such asFacebook, Google,Microsoft and Yahoo.

The data, the USwhistleblower has said, areused to track foreignnationals suspected ofterrorism or spying.

The claims have cast ashadow on the use of databy companies. The book’sauthor, a former ColumbiaUniversity professor, israther more gung-ho aboutthe potency of using data,possibly unsurprising as hehas also founded thePredictive Analytics Worldseries of conferences.

The book shows suchtechniques have beenapplied by organisations toforecast, for example, yourbuying decisions, or thelikelihood of your leaving ajob, your health and dateof death. The modellingmethods vary but all usedata, from commercial

transactions, socialnetwork postings or humanresources records. Theseare harnessed to anticipatebehaviour, in order todrive and automatedecisions by retailers,employers or healthcareproviders.

Prof Siegel revealsinsights into consumers’habits, such as a pharmacychain’s findings that if youbuy nappies you are likelyto buy beer, or an insurer’sdiscovery that a low creditrating means more caraccidents.

He looks at the FlightRisk program, run by thePC maker HP, whichpredicted which staff weremost likely to leave. In apilot group, HP was able to

reduce turnover from 20 to15 per cent.

He also shows thelimitations of predictiveanalytics – for example, byassuming too much. Hecites the case of theBerkeley professor DavidLeinweber, who discoveredthat the annual closingprice of the S&P 500 stockmarket index could havebeen predicted from 1983 to1993 by the rate of butterproduction in Bangladesh.

“His analysis wasdesigned to highlight acommon misstep byexaggerating it,” writesProf Siegel. “It’s easy tofind correlations bysearching through a largenumber of financialindicators across manycountries, just by chance.”

The book is littered withlively examples, althoughthe short chapters andsubheadings lack focus.

Prof Siegel only brieflyraises the privacyimplications of data use,citing a rather flipreference to the comiccharacter Spider-Man’suncle: “With great powercomes great responsibility.”

More seriously, he statesthat: “[This] is animportant, blossomingscience. Foretelling yourfuture behaviour andrevealing your intentions,it’s an extremely powerfultool – and one withsignificant potential formisuse.”

Emma Jacobs

Gung-ho approach tendsto ignore dark overtones

PREDICTIVE ANALYTICS

The Power to Predict WhoWill Click, Buy, Lie, or Dieby Eric Siegel

Published byJohn Wiley & Sons£18.99/$28

The promise of businessintelligence is that it canspot unforeseen correlationsand allow companies to drawsurprising insights from

masses of data such as quarterly salestransactions.

But this work requires a lot of com-puting power, which previouslymeant paying in advance for dedi-cated processing equipment and soft-ware before the inquisition of datacould begin.

However, providers hosting analyti-cal services on remote servers in thecloud can undercut what was previ-ously a costly exercise even for bigcompanies.

Using the cloud means not havingto buy dedicated equipment or allo-cate substantial space on existinghardware.

Established data analysis software –designed for the corporate domain –was not easily adapted to be accessedonline, and newer entrants in thismarket have leapt into the cloud, withthe result that their clients havelower data analysis bills.

James Mucklow, an IT expert withPA Consulting, says: “The idea ofbusiness intelligence is to have a con-versation with the data. In the past, ittook time to formulate each ques-

tion.” He says the surprise for manybusinesses accustomed to using busi-ness intelligence software is just howquickly projects can now be set upusing cloud-based services.

PA uses publicly availableanonymised prescription data formillions of patients of the UK’sNational Health Service to demon-strate how to initiate a project.

To analyse such a mountain of datausing conventional software wouldtake months and cost £100,000 ormore, including hardware purchases.However, a project to analyse thesame data could be up and running inthree days using cloud-based services.

In IT terms, the drugs data are nodifferent from sales transactions in alarge organisation, and Mr Mucklowsays they can be interrogated quickly.

He adds that venturing into a dataanalysis project via the cloud is a low-risk option. “You can do this, decide ithas no value for you, and switch itoff,” he says.

As a result, business intelligencehas entered a new era of agility; forexample, one-off intelligence projectsare now likely to become a muchmore attractive proposition to smallbusinesses.

Both Amazon and Google areoffering data analysis via the cloud.

Jaspersoft was founded in San Fran-cisco to bring data analysis to abroader audience.

The company now operates via theAmazon Web Services Marketplaceand 250 users signed up for the serv-ice in the first three months of itsgoing live.

Jaspersoft’s software manipulatescustomer data, hosted on Amazonhardware.

Brian Gentile, Jaspersoft’s chiefexecutive says: “Once your databaseis inside Amazon’s cloud we can con-nect to it and do analysis,”

He says that previous businessintelligence applications were “tooexpensive, didn’t reach the audiencethey could have because of the cost”.

Jaspersoft reckons that it can scru-tinise data through Amazon for just52 cents an hour, although most com-panies offer a fee structure that varieswith how much you use their serv-ices.

Despite its new availability, MrGentile thinks that it would be amistake to confuse a business intelli-gence project with every other cloud-based service.

“This is still a different category ofsoftware, you have to know whatyou’re doing, although there is noth-ing magical about it,” he says.

Remote hostingoffers moreagile responsesThe cloud Online access cuts fees and deliversprojectsmore quickly, writesMichael Dempsey

New prescription:NHS data demonstratethe potential of theinternet Daniel Lynch

‘This is a differentcategory ofsoftware, you haveto know whatyou’re doing’