1、INDEPENDEN T P U B L I C AT I O N BYRACONTEUR.NET16/10/2022#0837into the video gaming sector moves markets.Why?Because eco-system players have such disruptive potential.Back in 2011,Nokias then CEO,Stephen Elop,said:“Our competitors are not taking our mar-ket share with devices;they are taking our m

2、arket share with an entire ecosystem.”His comments still resonate more than a decade later.Data on customers and partners is the lifeblood of such strategies.But the business ecosystem model has extended far beyond online shopping malls such as Walmart Marketplace.It is also being deployed along val

3、ue chains.John Deere is doing this with its smart farming ecosystem as it combines tech-enabled tractors using cloud computing,field mapping and data analytics.Maersk,meanwhile,is focused on integrating container logistics to help optimise cus-tomers supply chains by joining the dots in transport,fi

4、nance and port services.Those firms that have succeeded with an ecosystem model started by rolling out a common data and digital platform.This is the backbone,enabling other players to connect and work together using a single source for customers and supply chains.This also enables synergies between

5、 busi-nesses to develop.So-called data flywheels Only connect:the rise of the data ecosystemA wide range of companies are benefiting from the power of multi-partner collaborations based on data-sharinghe natural world is a great inspi-ration for business.Ecosystems,where many species combine to prod

6、uce a thriving entity,are imitated in the corporate world.The whole range of goods and services on which humans depend is delivered by dynamic groups of businesses working in harmony.The DNA that underpins all this activity is data.Data-led business ecosystems,in which a single source of digital inf

7、ormation empowers independent economic players to offer services that customers value,are thriving.Data-sharing collaborations of this type have become a source of com-petitive advantage and its not only online marketplaces that are flourishing asa result of them.More than half of the worlds biggest

8、 companies engaged seriously in ecosystem business models,according to research by the Boston Consulting Groups think-tank,the BCG Henderson Institute.Brands ran-ging from Walmart and Maersk to John Deere and Grab are rolling out ecosystem models that involve a network,linked by flows of information

9、,services and money,where the whole functions better than the sum of its parts.Advances in“digital platforms,connec-tivity and data have fuelled the dramatic rise of such ecosystems that we have seen over the past few years”,reports Martin Reeves,chairman of the BCG Henderson Institute.“Successful e

10、cosystems can pro-vide access to new capabilities,scale up rapidly,be very adaptive,enjoy high asset productivity and transform entire indus-tries.They also exploit the network effect,whereby the value to users and suppliers increases with the size of the ecosystem.”Thats because data-fuelled digita

11、l plat-forms can offer more to the customer,such as personalised recommendations across abroader product range and at a lower cost.This has hugely expanded whats on offer,breaking the trade-off between com-plexity and reach.When Chubb offers embedded insurance via the Grab“superapp”,the big traditio

12、nal players shudder,while Netflixs venture Nick EasenAn award-winning writer and broadcaster specialising in science,technology,economics and business.He has produced content for Time,CNN and BBC World News.Sean HargraveA former Sunday Times innovation editor who works as a freelance business and te

13、chnology journalist covering topics such as digital marketing and financial services.Christine HortonA long-term contributor to IT titles who specialises in writing about technologys impact on business.She is also tech editor at B2B agency alan.Natasha Khullar RelphA freelance journalist who has bee

14、n writing about technology and the environment for more than 20 years.Oliver PickupA multi-award-winning journalist specialising in business,technology,sport and culture.Finbarr ToeslandA freelance journalist who has contributed to outlets including TheTimes,The Telegraph,the BBC and NBCNews.Alex Wr

15、ightA business and financial journalist with more than 20 years experience,having worked on publications ranging from national newspapers to trade and consumer magazines.also begin to gain mom-entum as more information is gath-ered across the ecosystem,informing what,how and when products and servic

16、es should be offered to customers.Christian Pedersen,chief product officer at enterprise software specialist IFS,stresses that firms must“first evaluate how data can drive business strategy.Data lakes are becoming more prevalent as a means of storage,largely because its easy to run analytics on thes

17、e lakes and then use the output to feed an ecosystem of business tools that take advantage of it.”And thats where data-led business eco-systems are different from mere digital platforms.Ecosystems depend on shared data to inform stakeholders strategic and tactical decision-making.Their success also

18、largely depends on how humans inter-pret the material and act on it.The easier itis to digest,the better.“A key area of focus for business eco-systems is explainability,”Pedersen says.“There is a perceived difficulty in taking complex problems concerning data and explaining these to stakeholders.But

19、 we are seeing the emergence of techniques such as explainable AI,which is providing more information to decision-makers far more quickly.”But becoming a business ecosystem player empowered by data is far from straightforward.The BCG Henderson Institute believes that only 15%of the eco-systems it ha

20、s studied can be sustained in the long run.Its a jungle out there,with a huge rate of attrition.Dominant market incumbents are proving less successful at it than large tech or startup players.Reeves says that one of the most common mistakes a firm can make is to“automati-cally assume that it has the

21、 right to be the orchestrator of an ecosystem when most do not.Building one incurs costs and risks.Industries with significant customer friction,such as high intermediary costs,delays and mismatches,and those markets that havent yet been dis-rupted by digital and data-led plat-forms provide many suc

22、h opportunities.Lots of these have already played out in the B2C space,but the potential of B2B and the public sector remains largely untapped.”Yet overly complex data infrastructures,siloed data,legacy systems and a lack of real-time information plague many sec-tors,making ecosystem models less via

23、ble.Newer technologies,such as smart data fabrics,can help to overcome this.These enable organisations to capitalise on data lakes,building a layer of command and control on top as well as stitching together distributed information.Bringing in the right talent can also help in this respect.“Against

24、a backdrop of uncertainty,busi-nesses across all sectors are looking to their data to gain a competitive edge,”notes Chris Norton,managing director at IT consultancy InterSystems in the UK and Ireland.“Organisations are also often unaware of just how much value can be added to their innovation initi

25、atives through the inclusion of data specialists.”The ecosystem business model presents new opportunities in numerous sectors,particularly specialist niche markets.Yet finding such opportunities,as Reeves notes,may require imagination and coun-terfactual thinking a process that data can also inform.

26、The concept of business ecosystems is not new.What has changed is the data empowerment element and the understanding that,with the right systems in place,ecosystems can be scaled up quickly and efficiently.Its whats making them such an exciting growth prospect.Distributed inPublished in association

27、withAlthough this publication is funded through advertising and sponsorship,all editorial is without bias and sponsored features are clearly labelled.For an upcoming schedule,partnership inquiries or feedback,please call+44(0)20 8616 7400 or e-mail .Raconteur is a leading publisher of special-intere

28、st content and research.Its pub-lications and articles cover a wide range of topics,including business,finance,sustainability,healthcare,lifestyle and technology.Raconteur special reports are published exclu-sively in The Times and The Sunday Times as well as online at .The information contained in

29、this publication has been obtained from sources the Proprietors believe to be correct.However,no legal liability can be accepted for any errors.No part of this publication may be reproduced with-out the prior consent of the Publisher.Raconteur Media/future-data-2022-octFUTURE OF DATAS M A S H I N G

30、S I L O SS K I L L SCY B E RS E C U R I T YR E S I L I E N C EConsolidation tends to be hard,costly work,but the long-term benefits will justify the effortWhy employers must become more creative to solve their shortage of data scientistsWith attacks on the rise,businesses look to advanced analytics

31、for protectionGreener ways to make data centres more robust against extreme weather Nick EasenTContributors A key area of focus for business ecosystems isexplainability.There is aperceived difficulty intaking complex problems concerning dataand explaining these to other stakeholdersD ATA C U LT U R

32、ELead publisher Jamie OglesbySub-editorChristina RyderChief sub-editorNeil ColeDeputy reports editorJames SuttonReports editorIan DeeringHead of productionJustyna OConnellDesign and production assistantLouis NassDesignHarry Lewis-Irlam Celina LuceyColm McDermottSean Wyatt-LivesleyEditorSarah VizardD

33、esign directorTim WhitlockIllustrationKellie JerrardSamuele MottaCommercial content editorsLaura BithellBrittany GolobAssociate commercial editorPhoebe Borwellraconteurraconteur.storiesTOP INITIATIVES TO FOSTER A DATA CULTURE AMONG LARGE COMPANIES IN NORTHERN EUROPE AND THE US Percentage of senior e

34、xecutives in the data analytics function citing the following as measures their firms were usingManaging data governance at the point of data use49%Improving collaboration between the data analytics team and the wider business42%Establishing an internal data community44%Creating metrics and key perf

35、ormance indicators focused on data curation40%Embedding data scientists in departments36%Training/retraining people in the use of data45%Emphasising the importance of data skills when recruiting42%Designating data stewards in business units43%Raising awareness in the organisation about the value of

36、using data37%Wakefield Research,Alation,2021raconteur-mediaF U T U R E O F D ATA02Amalgamate to accumulateThe task of breaking down data silos may seem time-consuming,complex and costly,but letting disparate legacy systems atrophy in isolation is likely to prove more expensive in the longer termhe w

37、idespread adoption of power-ful analytical tools and AI-based systems that can offer insights into everything from operational efficiency to consumer behaviour has had a clear positive impact on businesses worldwide.Yet,despite such advances,even the most forward-thinking companies are still likely

38、to have data silos that are preventing them from performing to their full potential.“It doesnt matter whether youre a start-up or a large corporation silos will exist if different departments inside your business store their data in separate locations,”says Mihai Cernei,CTO at Amdaris,a specialist i

39、n digital transformation.“As these dispa-rate assets grow,so do your silos.”The existence of silos makes data analysis a far more time-consuming process than itneeds to be.And,if similar material is being stored in numerous places,inconsist-encies can easily creep in,jeopardising the quality of the

40、information extracted.IT specialists faced with a lack of joined-up platforms tend to devote more effort to data management than they might wish to.A 2020 Gartner survey of data professionals found that on average they were spending 56%of their working time on routine data management work.That meant

41、 they were spending only 22%of their time on more value-adding tasks such as data monetisa-tion and the extraction of valuable insights.Every company will have its own unique set of data consolidation problems to over-come.In Cerneis experience,nearly every obstacle a business will face in its effor

42、ts to bring together fragmented data falls into one of three categories.First,its becoming increasingly difficult to find high-quality technical experts who can do this work.Second,the task of even accessing many legacy systems requires either bespoke soft-ware or new data connectors to be built.Thi

43、rd,and perhaps the most significant fac-tor for firms looking to eliminate data silos,is that the process tends to be expensive.Finbarr Toesland“Some integration is costly and requires a lot of computer power,”says Cernei,although he adds that its“important to note that this isnt true of every solut

44、ion.Some can save you money.”Chris Gorton is a senior vice-president at Syniti,a specialist in enterprise data man-agement.He recommends that the first step any organisation should take when attempting to break down silos is to obtain a comprehensive understanding of exactly what data it wants to ga

45、in control over.“Companies need to develop a plan to consolidate information,harmonise dupli-cated material and ensure that its of a high quality,so that it can be trusted and used throughout the business,”Gorton says.As data-synchronisation work can affect all parts of an enterprise,its vital that

46、this plan factors in how all operations can keep running seamlessly as the process gets under way.Many business leaders are facing budget constraints that will require them to make hard choices about which projects need to be prioritised and which ones can be shelved until more funds are available.I

47、f they are to approve a data integration pro-ject,members of the C-suite will therefore need to see a strong business case for it.“Are there any quick wins that would in-crease overall acceptance for making the change?If so,this could be an opportunity to save money,reduce risk and create effi-cienc

48、ies that will drive greater acceptance from the whole business on why this should be done,”Gorton suggests.Replacing outdated software and hard-ware is a key element of any plan to remove silos.The longer that legacy systems are left unmodernised,the more work will be required further down the line

49、when they cause compliance and security problems,hinder innovation and restrict growth.The emergence of cloud-based integra-tion solutions has made it easier than its ever been to eliminate silos caused by the continued use of obsolescent systems.Data lakes,in which all forms of data can be held and

50、 made accessible,can be a particularly effective tool.Mike Haresnape,director at business intel ligence consultancy Dufrain,explains that consolidating the material into such platforms enables a firm to“model differ-ent data sets and join them together.It can then meet any number of reporting,ana-ly

51、tical or machine-learning use cases.”He adds:“Organisations can cut costs and time spent on data extraction by ensuring that,whenever an application is enhanced,its data is moved to another platform.Tak-ing advantage of relatively low storage costs and landing large data sets in the cloud or on the

52、premises can also help with this.”But its no secret that data consolidation programmes of this type are notoriously difficult to get right.Gartner estimates that about 85%of big data projects will fail to meet all their objectives,illustrating the scale of the challenge that businesses face when try

53、ing to get a handle on complex and disparate data from across the enterprise.Using a mix of integration solutions is unlikely to succeed unless a comprehen-sive data governance system is embedded throughout the organisation.In practice,this will necessitate a range of standards,processes,policies an

54、d metrics that define clearly how data is used to best meet the goals of the business.“One practical step towards making pro-gress on data,while also keeping an eye oncost,is to align data towards business strategies,”Haresnape says.“A data gov-ernance strategy needs to add extra value,be tailored t

55、o the organisation and focus on data thats relevant to its activities.”A well-implemented data governance strategy can result in both data quality im-provements and the ability to create a map indicating the location of business-critical material.With businesses continuing to generate huge volumes o

56、f data on custom-ers,suppliers,employees and more,data governance will become an increasingly important part of any method of dealing with silos.Theres no question that the initial outlay required to break down data silos can seemexcessive.But the potential benefits of establishing a single source o

57、f truth,enabling all decisions to be based on the same information,mean that its less of a cost and more of an investment in the future of the business.One practical step towards making progress on data,while also keeping an eye on cost,is to align data towards business strategiesCommercial featurea

58、ta can be key to solving busi-ness problems,but only if decision-makers have the ability to access it while its still rele-vant.Finding out what action should be taken now is more important than determining what should have been taken yesterday.CDOs are under pres-sure to manage vast amounts of data

59、 at an unprecedented pace:delivering data and insights in real-time is impor-tant across every type of business and in every aspect of those businesses.Product teams that get usage insights in seconds instead of days can increase user adoption and reduce churn.Stock and cryptocurrency analysts who c

60、an stream and analyse trading data instan-taneously have an advantage over their market peers in identifying the most profitable trades.Ecommerce stores that run analytics with millisecond latency can instantly personalise the shopping experience delivered through a seamless UX,boosting conversion r

61、ates and reve-nues.Regardless of industry or product,real-time analytics improves the KPIs that data leaders-and their stakehold-ers-care about.But getting to the stage where prod-uct development teams can make use of data at scale is easier said than done.Businesses process huge volumes of data eac

62、h day from numerous sources,stored in multiple ways by multiple people across the organisation.Data ware-houses are well equipped to store uni-fied data that supports specific analytics needs,but handoffs and delays are often hard to avoid while data is being batched and processed.Even minute delays

63、 may have ripple effects that impact user experience,and acting on analytical que-ries in real-time is not tenable,with the value of the insights they provide drop-ping as the minutes tick by.Data leaders must rise to the challenge of building or rebuilding data infrastruc-ture that ensures everyone

64、 can get the data they need when they need it.In theory,closing the gap between ana-lytics and action can be achieved inter-nally.The instinct may be to throw data engineers,time,and money at the prob-lem in the hopes of improving latency or concurrency metrics.But this also means diverting substant

65、ial resources away from the actual business of the business-and away from improving the product.Jorge Gomez Sancha,co-founder and CEO of Tinybird,knows that engineers are often used to managing their own data infrastructure,which brings with it a score of things to think about,from basic server conf

66、iguration to the intrica-cies of developing secure,low-latency,high-concurrency endpoints.“Whats the right CPU level,the right number of CPU cores,or amount of memory?Should I use replication or sharding?How do I keep track of whether everything is up and running?Theyre thinking we need a database t

67、hat we then build things on top versus we need tools to solve our problems with data,”says Sancha.“Your devel-opers shouldnt even need to think about any of that,they should be think-ing Whats the next business problem I can solve and provide value?”Sancha believes that data leaders should focus on

68、enabling developers to apply analyt-ics within the products they build in as close to real-time as possible.In many cases,the problems data lead-ers need to solve in order to give devel-opers access to real-time analytics are not unique.Almost every CDO or head of data is confronting or has confront

69、ed the challenge of building real-time data architecture.But why is it so challeng-ing to solve?Data warehouses werent built for real-time,but data teams have spent the last decade investing in infra-structure and tooling that surrounds and supports the data warehouse.To solve for real-time use case

70、s,data leaders will need to branch out.But why start from scratch when tools like Tinybird are already solving the prob-lem?Increased performance and pre-cision are core goals for any CDO,and streamlining these processes requires the right set-up.Data teams that use a serverless approach with best-o

71、f-breed software can integrate with existing streams,databases,and warehouses,process them through an optimised and simplified data stack,and then provide near-instantaneous access on the other side-often in a way that complements the traditional data warehouse.These serverless tools can plug into d

72、ash-boards,trigger alerts,power automa-tion,or feed into whatever other data products the business uses.Sancha points to Keyrock,a Tinybird customer operating in the cryptocur-rency market,as a prime example:“they ingest data from markets all across the world,in crypto but also in other assets,and t

73、hen they are constantly making bets as to where things are going and creating transactions.”Inevitably this involves a massive amount of data,and Keyrock was battling a host of latency,freshness and concurrency issues.Data took many seconds or even minutes to process and hand off,and even went missi

74、ng entirely,making it challeng-ing to analyse and act on that data in real-time.In such cases,attempting to fix the issue internally was costly and time-consuming:using Tinybird proved a far more efficient solution.Data teams that add real-time archi-tecture to their stack often discover opportuniti

75、es to apply the tech to new,tangential use cases that have sat unre-solved.Sancha remarks on a client who had initially transitioned to a real-time architecture to reduce the lag time in their analytics platform.This shed light on a new solution to an old prob-lem-could real-time analytics be the ke

76、y to identifying and preventing deni-al-of-service attacks on their services?Implementing instant logging and analyt-ics enabled them to turn hours of work into an automated process that could effectively intercept and respond to attacks within minutes.Once the value of real-time data becomes eviden

77、t in one area,different teams across the business will find that they rapidly develop new ways to apply real-time across everything they do.Data leaders need to give developers the tools to make actionable use of the data thats pouring into their databases at a moments notice,and waiting min-utes to

78、 understand whats happening while their competitors wait seconds or milliseconds is not a sustainable option.They need real-time data architectures with an emphasis on simplicity and per-formance.Having the data to make crit-ical business decisions isnt enough;developers and data teams need to be ab

79、le to build data products that can have a real-time impact at any scale.CDOs and heads of data need to act now to realise this,as the size of their data is only accelerating.For more information,visit tinybird.coSimplifying the data stack:why businesses need a real-time upgradeData leaders are under

80、 pressure to deliver on real-time use cases over data thats growing exponentially,but how can they get there with a traditional data stack not suited for real-time?Commercial featureD Developers should be thinking:Whats the next business problem I can solve and provide value?DATA LEADERS ARE STREAML

81、INING PROCESSES AND STRIVING FOR GROWTHCDOs top data governance priorities CDOs top data governance obstacles But meeting these goals is not without its challenges55%53%54%40%52%40%41%32%59%55%Process improvement and increasing efficienciesDelivering and determining valueRisk mitigationData-enabled

82、decision makingBoosting business outcomesResource deficitsSkills gapsSiloed operating modelsAdoption barriers Company cultureEvanta,2022C O N S O L I D AT I O NTSILOS ARE AMONG THE BIGGEST BARRIERS TO THE USE OF DATA TO FUEL GROWTH AMONG LARGE COMPANIES IN NORTHERN EUROPE AND THE US Percentage of se

83、nior executives in the data analytics function citing the following as limiting factors in their firmsWakefield Research,Alation,2021A lack of analytical skills among employeesPoor-quality dataThe burden of managing complianceA lack of data democratisation not everyone can gain access on their ownOr

84、ganisational silos an unwillingness among teams to share dataLimited awareness of what data exists and where its being stored41%39%39%36%35%34%R A C O N T E U R.N E T03THE RISE OF HYPER-SCALE DATA CENTRESNumber of large centres housing thousands(or millions)of servers in existence between 2015 and 2

85、021Synergy Research Group,2021BIG DATA STORAGEBig data analytics is an advanced technology thats helping businesses in many sectors to achieve their commercial goals.But where is all of the material it uses being stockpiled?Whilesome companies invest in storage and processing centres on their own pr

86、emises,thesheer volume of data will often demand the use of off-site,hyper-scale repositoriesMAIN LOCATIONS OF HYPER-SCALE DATA CENTRESGlobal distribution of large centres housing thousands(or millions)of servers between 2017 and 2020USChinaJapanOtherSynergy Research Group,20220201939%46%

87、45%45%7%6%7%6%7%8%10%10%47%40%38%39%DEMAND FOR STORAGE SPACE IN COLOCATION DATA CENTRES IS SET TO RISEThe markets projected revenue growth from 2021 to 2028DATA CENTRE POWER CAPACITY Total power supply provided by data centres in selected European cities in 2021Dublin125MWParis210MWAmsterdam390MWFra

88、nkfurt425MW$136.65bn2028$50.58bn2021Vertiv,2022Dgtl Infra,2021THE MOST POPULAR LOCATIONS FOR DATA CENTRESNumber of centres known to exist in selected countriesCloudscene,20222,758032MexicoCanadaUSBrazilNetherlands UKFranceAustraliaJapanChinaIndiaRussia Poland Germany

89、 Italy 2074582000248504597700London710MWF U T U R E O F D ATA04There is a fear among data scientists that automation will eventually put them out of a job.AI-based systems are already being put to work on several simple tasks producing basic data models,for instance.

90、A research report published by Gartner in 2017 predicted that about 40%of data science work would be automated by 2020.While the accuracy of that forecast is moot,its widely expected that the technology will take on more challenging and complex tasks as advances in AI continue to be made.Since data

91、scientists are required to maintain the technology,AI can never fully replace them.Humans are neededto guide the first iterations of machine-learning models and initial inputs,as well as to identify new opportunities for the business,which AI will still often miss.“While it is true that some technol

92、ogies can dramatically improve the performance of data scientists,weare further away from AI replacing them than ever,”argues Kjell Carlsson.“The ongoing struggles of vendors in the machine-learning space that have promoted the myth of the citizen data scientist can be seen as evidence of this.Inste

93、ad,the opposite is happening:AI is making data scientists much more productive and impactful.Demand for them is therefore increasing rather than decreasing.”Instead of viewing machine learning as a competitor,data scientists need toembrace the technology,using it as a tool that enables them tofocus

94、on more valuable work.Thatsaid,they will need to update their skills constantly to ensure that they stay abreast of developments in the field.AI enables data scientists to generate hundreds or even thousands of variations of models with different prediction features and to create more complex iterat

95、ive data simulations to choose the best variation.By working together,data scientists can use AI as a digital assistant that can automatically test,iterate and monitor data quality;incorporate data points as soon as they become available;and ensure that they can react quickly to new developments.“In

96、 the world of data science,the main task is not to train a new model.First,you have to do a feature engineering process,which sometimes requires a lot of imagination,”observes Andrew Lane,founder and CEO of Acuity Trading.“As long as we never teach AI how to imagine,data professionals jobs will be s

97、afe.”As demand for data scientists looks set to outstrip the supply for several years,employers would be well advised tobroaden their search and make longer-term investments in training and developmenthe volume of data that businesses handle has increased exponen-tially in recent years and so has th

98、eir need for the skilled professionals who can analyse and interpret all this material.The problem is that there is a huge dispar-ity between the supply of data scientists and the demand for them.To give an idea of the scale of the talent shortage,there are about 210,000 job ad-verts for data scient

99、ists on LinkedIn alone,according to research by the International Data Corporation.Among the most highly sought-after skills are information man-agement,statistical analysis and program-ming.Recruiters are especially keen on candidates specialising in fast-evolving fields machine learning and custom

100、er analytics,for instance who can interpret the data these systems generate and rec-ommend appropriate plans based on it.Zo Morris,president of Frank Recruit-ment Group,believes that companies need to adopt a“people-first mindset”to bridge the skills gap.That requires them to adopt a multi-pronged s

101、trategy that looks bey-ond the limited pool of immediately ready candidates and makes longer-term invest-ments in people.“Providing learning,development and training opportunities that enable profes-sionals to upskill is the first step in doing this.This is likely to improve attraction and retention

102、 in the process,”Morris says.“Businesses also need to diversify their talent pipelines,expanding their reach to become more inclusive.”To this end,firms must put a robust di-versity and inclusion strategy in place to attract and retain a wider range of people.Candidates brought in from varied back-g

103、rounds and industries can bring valuable new perspectives and experiences to the team.Employers also need to offer recruits the option of flexible working,so that they can be at their most productive and en-gaged at work,while maintaining a healthy and fulfilling lifestyle.Some companies have alread

104、y adopted such an enlightened approach.They are looking for candidates with foundational Alex WrightCommercial featureHow operational resilience keeps data availableAccess to data after a breach is essential to operational resilience,says James Hughes,vice-president and enterprise CTO,EMEA,at Rubrik

105、Why has there been such a rise in ransomware attacks?Ransomware has had its perfect storm.The pandemic brought on this holy trin-ity amplification of vulnerable people work-ing from home,the rise of data absolutely everywhere and the growing prevalence of anonymous currencies like Bitcoin.Together,t

106、hese trends have seen a huge acceleration in ransomware over the last couple of years and we dont see it stopping.Its not kiddies in a bedroom anymore.Malicious actors run proper businesses which operate P&Ls,offer ransomware-as-a-service products and even have systems to leave reviews because they

107、compete for custom.State-sponsored hack-ing is also more prevalent.What is the ultimate cost of a ransomware attack?When people think about ransom-ware,many think about the cost of the ransom,but thats the cheapest part.The cost of the outage is the biggest expense.Attackers are not targeting your i

108、nfrastruc-ture;they know you can recover that pretty quickly.Theyre targeting your data,which is a one-of-a-kind asset and the absolute life-blood of any organisation.If theyre deter-mined,whether you like it or not,they will get it,and it will halt your business from being able to operate.Staff twi

109、ddling their thumbs and customers not getting what theyve paid for is the real cost,and its why operational resilience is so important.When resilience is embedded in your busi-ness,you may not be able to operate at full capacity immediately after a ransomware attack,but youll at least still be opera

110、ting.What are the key challenges to ensuring that breached data can be recovered?You can only know what to do after an attack if youve rehearsed it.Youve got to rehearse in peacetime so you know what to do in wartime.And its not just a technol-ogy exercise but people too.We run events called Save th

111、e Data,which show the sorts of things youve got to get involved in right away from your technology teams to how to communicate to the markets and your cus-tomers.But without data,theres nothing to rehearse.Its vital to ensure data is absolutely protected,completely secure and access to it is locked

112、down.Most importantly,data must be available when you need it,which means combining the ability of an offline data backup with the speed of an online platform.Is a zero-trust approach to security required to achieve operational resilience?Yes,its paramount.Zero trust is simply the idea that one shou

113、ld assume a breach.If youre operating your entire envi-ronment with the mindset that somebody with malicious intent is already in,that puts a really different lens on your architectural decision-making and also creates a com-pletely different mindset,much more con-ducive to achieving operational res

114、ilience.Its also important that organisations close the many silos that exist between tools and teams.If your IT and security teams are look-ing at the same data and the same recovery position,and they know what each other are doing,they are in a better position to keep your business operating.How i

115、s Rubrik supporting companies on their journey to operational resilience?Our mission is to secure the worlds data and we take that extremely seri-ously.Were not looking at your infrastruc-ture,as thats all fungible in a cloud-cen-tred world.Were laser focused on data.Data secured by Rubrik cant be a

116、ffected by malicious outsiders and when you need your data back we make it immedi-ately available,in some cases up to the second,so that your applications can continue functioning.Theres a huge dif-ference between recovery and resilience.With recovery,youre rebuilding from the rubble.Resilience mean

117、s you can weather the storm and continue servicing your business with all the right data in the right place.Thats what we do all day,every day at Rubrik.To learn more from James Hughes on the importance of operational resilience,register for Rubriks upcoming Data Security Talks event at Q&AS K I L L

118、 STHow to expand the data science talent puddle capabilities,such as an aptitude for logical and quantitative reasoning,and then training them in the principles and prac-tices of data science.Others are hiring not only from different sectors,but also from different regions.Philip Linardos is co-foun

119、der and CEO of ShelfNow,a London-based online trading platform.He says that his firm has some-times“looked to hire overseas talent,as we are a Europe-wide company that works with several EU countries.In addition,while we have waited to find the perfect person for data science roles on occasion,we ha

120、ve redeployed skills accordingly.”Tertiary education providers clearly have a big role to play in equipping tomor-rows data scientists with the requisite know ledge and skills.Indeed,several uni-versities and colleges are establishing new bach elors and masters degree courses or updating their exist

121、ing programmes in data science.Employers can collaborate with these providers by,for instance,helping them to fine-tune their curriculums.They can Artificial intelligence:friend or foe?DevSkiller,2021Laurence Dutton via iStocktiero via iStockGrowth in the number of data science-related tasks set by

122、recruiters during interviews last year295%R A C O N T E U R.N E T05Commercial featureuccessful businesses are reli-ant upon resilient supply chains that can withstand short-and long-term disruptions,respond to problems at speed and con-tinue to deliver a reliable service ahead of competitors.But how

123、 do companies bolster supply chain resilience?Partnering with a cloud ERP provider is an essential first step for modern businesses of all sizes.Mid-market businesses typically have on-premises ERP systems or IT solutions but have not yet made the switch to the cloud.Doing so will help them better m

124、anage their supply chains,procurement,manufac-turing and other daily activities.But Covid-19 and variables such as supply chain and distribution chal-lenges,heightened demand and labour shortages,as well as the soaring cost of energy and raw materials,have accelerated the demand and need for real-ti

125、me data and remote access to enable businesses to make swift and accurate decisions.This is enabled by cloud technology.“When implemented correctly,cloud ERP software enables ecommerce at the speed of light,”says Andy Coussins,SVP&head of international at ERP software provider Epicor.“Businesses can

126、 keep track of supply and demand,ensure accurate forecasting and enable strategic planning while staying compli-ant in todays challenging and complex global economy.”But the decision to move to the cloud or change ERP provider isnt taken lightly.Most businesses use a range of different software to r

127、un differ-ent business functions,whether its for sales,customer service,payroll or other operations.Epicors ability to integrate with these other platforms allows businesses to seamlessly control their operations and ensure their data is secure in the cloud.Epicors Industry ERP Cloud solutions are i

128、ndustry-specific and tailored to seamlessly integrate with existing tech-nology.Key to this is Epicor Automation Studio,a pioneering low code inte-gration platform-as-a-service(iPaaS)which allows companies to integrate and automate activities and processes between previously siloed applications data

129、 and platforms.Automation Studio empowers work-ers to easily integrate and automate scheduled or event triggered work-flows,offering access to a market-place of over 1,000 popular applica-tion connectors where businesses can modify and implement the workflow integrations that they need.It can also c

130、all any API or read from a database meaning its simple to connect systems.But,while the integrative qualities and functionality of the cloud ERP software are essential,the relationship between the business and pro-vider is equally important.The Epicor Industry Insights Report 2022,which surveyed 1,3

131、50 tech-nology decision makers,revealed that most leaders consider changing pro-viders every one to three years.A common reason for switching pro-viders is poorly managed implementa-tions as a result of poor communica-tion with key stakeholders.“The key to a successful long-term partnership with an

132、ERP provider is to ensure the rela-tionship is aligned at the right level,”says Coussins.“ERP solutions run the business and hence should be aligned with the people that run the business,not just IT.“Previously,software was seen as an IT concern and some soft-ware is,such as collaboration tools and

133、productivity applications but ERP software is very different and failure to recognise and align is destined to cause operational turbulence.”If businesses can partner with a cloud ERP provider that offers smooth inte-gration and robust communication,then the foundations are in place for digital tran

134、sformation to occur.Epicors cloud ERP acts as the digi-tal foundation of the business forming the basis from which more and more parts of a business can be digitised and integrated.A key part of this transfor-mation is enhanced security.Epicors global team of experts are on hand at any time of day t

135、o take care of main-taining security updates,backups,and upgrades,enabling businesses to con-centrate on running their company without worrying about data breaches.“Having the latest security solutions available in an elastic cloud far out-weigh the server under someones desk or in a data centre tha

136、t isnt pro-tected against natural or malicious dis-asters,”says Coussins.Similarly,data management is improved through cloud solutions.Businesses are better able to migrate legacy data onto the cloud,and clean and maintain their data when using Epicors solutions.This enables that data to become a cr

137、ucial business intelligence and insight asset.Interoperability is another key feature of digital transformation facilitated by cloud ERP.Different departments can collaborate on one interface and have access to a single data source.For businesses expanding into new markets,it can also provide easy d

138、ata sharing between different operations and business units in different coun-tries.Configurability is another advan-tage,enabling modifications to match the needs of individual businesses,for example bespoke processes,collabo-ration techniques and documentation.With supply chains set to face more v

139、olatility in the months and years ahead,partnering with a cloud ERP software provider is imperative for businesses that want to build resil-ience,undergo digital transformation and gain a competitive advantage over their rivals.For more,please visit E the cloud facilitates improved data management C

140、loud ERP software is giving businesses the power to respond to disruption remotely at speed,forecast problems before they occur,boost data security and provide a central hub to facilitate digital transformationCommercial featureS The key to a successful long-term partnership with an ERP provider is

141、to ensure the relationship is aligned at the right level When implemented correctly,cloud ERP software enables ecommerce at the speed of lightCLOUD ERP CAN SUPPORT CRUCIAL BUSINESS FUNCTIONSTop three areas of business that companies would use cloud ERP to addressCLOUD PROVIDER SUPPORT CAN BOOST CONF

142、IDENCE IN ERP SOLUTIONSTypes of data support that help in-house teams when migrating to the cloudAnalytics and business intelligence31%28%Supply chain management31%29%Manufacturing and Operations29%34%31%30%29%33%Support in data migrationEducation on data hygieneDistributionManufacturingDistribution

143、Manufacturingof distribution and manufacturing professionals agree that they are comfortable with cloud based solutions90%Epicor,2022Epicor,2022Epicor,2022Nearlyith data flowing into them from all corners of the cloud,organ isations are seeking to squeeze out every drop of value from it,capitalise o

144、n AI technologies such as machine learning and become truly data-driven businesses.As the head of IT innovation at a large manufacturer recently told us:“Our whole business model is now based on predictive technologies.”We at CIO WaterCooler have observed the CIO role spawning all kinds of specialis

145、ed mutations a process that has accelerated in recent years.In par-ticular,we have witnessed the rise of the chief data officer(CDO),especially in the financial services sector,as the senior IT leader to deli ver on the promise of data.In the decade after the emergence of Web 2.0 and cloud computing

146、,many CDOs joined senior management teams.Yet most organisations in the UK still dont have a CDO yet and would freely admit to being in the early stages of the so-called data maturity curve.The CTO of a London-based security services firm told us that his organisation has a lot of data,“but it is al

147、l over the placeinsilos”.The com panys big pro-ject this year is to bring all that material together,cleanse it and consider its use for AI solutions.But the centrality of data in modern organisations is ultimately forcing fur-ther evolution in the role of the CIO.Companies are hiring data scientist

148、s because everybody else is doing it,yet few have the right mindset to be truly data-first organisations.Where will data scientists sit in the organisation?Not under IT,according to the UK-based CIOs in our communi-ty.Most are embedded in the business,but some organisations have been building out th

149、eir data science capabil-ity with external partners such as IBM and Infosys,or creating a new internal data organisation.A veteran CIO working at a charity told us that she has observed“a range of healthy to unhealthy tensions”bet ween the IT and data science functions.IT understands data management

150、 and the value of data,but data science needs to be out in the business.Although IT should provide“an architecture with the right systems and data-capture pro-cesses”,sheis“not convinced that the data scientists then sit best within an informatics organisation”.The data function is moving into the b

151、usiness and forming interdisciplinary teams.Its following the general trend of IT,which no longer works in a silo.A global CTO of an information ser-vice told us:“Our teams are genuinely hybrid and I work very closely with our COO,CPO and CDO to ensure that we have an integrated strategy.”Where will

152、 that leave the CIO?The CIO role was already morphing into a more general strategic position a chief innovation or transformation officer.We have seen CIOs become COOs when they reach board level.In the ideal scenario,the CDO would be an equal partner of the CIO.The CDO wouldnt be able to succeed wi

153、thout the CIOs support.But the trend is that the CDO reports to the business,the CEO,COO or CFO,not to the CIO.The role of CDO is generally poorly defined.It is characterised by high expectations and too little power,which sets the incumbent up for failure.But that situation is likely to change.The

154、role could evolve,taking responsi-bilities and influence from the tradi-tional CIO.Data science and a CDO position would then become the main path to a board-level IT or innovation leadership role.Data is moving into the business and forming interdisciplinary teamsAndrew Pryor Co-founder,CIO WaterCo

155、olerI N S I G H TW Passion for data science starts young and it needs to be encouraged.Apprenticeships and work-experience placements are therefore vitalHARD-TO-FILL VACANCIESPercentages of UK businesses that were recruiting and struggling to recruit for selected data jobs in 2020 and 2021Recruiting

156、Struggling to recruitData analystHead of dataChief data officerData protection officerData managerData engineerAI strategy managerIntelligence analyst12%9%10%8%7%7%8%7%9%6%7%5%4%4%6%3%Gov.uk,2021work with universities,colleges and even secondary schools to generate awareness among students using eve

157、nts such as careers fairs.They can provide internships and work-experience placements giving direct exposure to the role.They can also offer scholarships and other funded routes into the profession.“Passion for data science starts young and it needs to be encouraged,”argues Mark Mamone,group CIO at

158、GB Group,aspecialist in digital identity verification.“Apprenticeships and work-experience placements,as well as graduate training programmes,are therefore vital.Working with communities that support inclusion,diversity and equality in this field the Women in Tech Forum,for instance is also key to a

159、ttracting diverse talent and building a successful team.”Microsoft has partnered with the Univer-sity of London and US institutions Purdue University Global and Bellevue College to provide blended and flexible learning opportunities based on its own technical courses in fields such as data science.S

160、imilarly,Infosys has enrolled 150 new workers in a six-week full-time programme at North Carolina University to improve their knowledge in foundational areas such as statistics,data visualisation,machine learning and Python programming.Stephanie White is a director at EC1 Part-ners,a recruitment age

161、ncy specialising in fintech.She reports that several universi-ties are helping students by offering them sandwich-year industry placements.“This means that,when graduates enter the jobs market,they already have some relevant business experience rather than just knowing the theory,”White says.“This e

162、quips them better for the work,which makes them more valuable to employers.”Once a company has assembled the right team of data scientists,the hard work doesnt stop there.The members need regu-lar training,delivered through deep learn-ing models,to keep their skills up to date in a particularly fast

163、-moving discipline.“To solve their data science gaps,compa-nies need to adopt a people,process and technology perspective,”advises Dr Kjell Carlsson,head of data science strategy at Domino Data Lab.“They must be far more diverse in their recruitment,training and evaluation processes.And they need te

164、ch-nology that supports such diversity and makes people more productive,more col-laborative,more impactful and,ultimate-ly,more fulfilled.”No one can know for certain how jobs in data science will evolve in the medium to long term.But having a well-planned and resourced recruitment process in place

165、is key to maintaining a supply of talent that can keep pace with advances in the field.“The technology is moving fast,but the skills required from a data science pers-pective are falling behind,”warns Andrew Scotts,EMEA head of front-office technolo-gies at EC1 Partners.“Companies need to stay on to

166、p of the changes and ensure that their employees are equipped with the right skills at all times.”The rise of data is not only transforming organisations;its also changing the role of the CIO.As the spotlight turns from the chief digital officer to the chief data officer,Andrew Pryor,co-founder at C

167、IO WaterCooler,considers whether the latter could emerge as the key IT leader at board level F U T U R E O F D ATA06Fighting the good fight one exabyte at a timeAs the migration of business to the cloud gathers pace,security specialists are becoming increasingly dependent on data analytics to detect

168、 suspicious activity across their networksata analytics has always been used in the war against cyber-crime,but its becoming firmly established in the front line of corporate defen ces as more and more businesses move their systems to the cloud and the criminals adopt increasingly sophistica-ted inf

169、iltration methods.The simplest explanation for why data analytics has become so important is to consider the fundamental change that accompanies the move to remote hosting,according to Ryan Sheldrake,CTO for US cybersecurity company Laceworks in EMEA.When they host their own servers businesses have

170、physical oversight,but that level of direct control is lost once a third party takes over their management.“In the past,you could find a server affected by an attack on your premises and even pull the plug on it,”he says.“With cloud providers,you may not even know where your servers are and you cert

171、ainly cant touch them.Instead,the providers trade that direct,physical control for mountains upon mountains of data,which is why analysing that data has come to the forefront of tackling cybercrime.”The rise of analytics in countering cyber-crime is not only down to the mass of data thats become ava

172、ilable to cloud users.The latest tactics adopted by highly sophis-ticated hackers have made threats harder to spot using traditional virus-detection meth ods,according to Adrian Nish,head of cyber at BAE Systems Digital Intelligence.“Viruses used to have the same signature code in them,so you could

173、scan for these,”he says.“But that is no longer the case attacks have become more advanced and one-off,meaning that you cant look for signatures.Instead,you have to use data analytics to monitor network traffic in par-ticular.There will be millions of pieces of data to look at.But,with the right anal

174、yt-ics,you can see what doesnt look normal,such as something on your systems a bot perhaps regularly calling out or beacon-ing to a third party for instructions.It might not be anything to worry about,but you can narrow the field with analytics.”That functionality is hugely important to organ isatio

175、ns operating on the front line of the war against cybercrime.Argua-bly,there is no industry where this is more pressing than financial services.A secur-ity breach at a bank,say,could cause a system outage at the moment a customer is expecting their mortgage funds to come through for their dream home

176、.It could even deprive people of their life savings.James Fellows,CTO of the Coventry Building Society,reveals that data analy-tics has become the only way for it to keep track of network traffic.Thats because the threats have altered,while what normal looks like has also changed dramatically.“Our c

177、ustomers have made a huge shift to ecommerce during the pandemic,which Sean HargraveCommercial featureDesigning a data strategy that delivers valueThe first step in any data initiative is developing a strategy.What are the key considerations?of companies worldwide do not have a well-defined data str

178、ategy70%any across the private,public and third sector believe that leveraging data is the domain of ecommerce giants,retail businesses with deep pockets,or tech firms with Silicon Valley muscle.Yet in an age when inno-vation is fast being commoditised,data science can now offer incredible and achie

179、vable benefits to any organisation.The first step involves unlocking the value of data.“Top executives in every sector real-ise that they sit on lots of data,however,utilising it can seem daunting.Creating a data strategy is the first decision.This is about laying the foundations for data empowermen

180、t.Its the beginning of a journey and the most important call to make,”explains Giles Horwood,man-aging director of Simpson Associates,a leading UK data analytics consultancy,with over 30 years experience.However,many organisations expe-rience inertia in any push to become data-driven.Concerns around

181、 skills,developing processes,technology deliv-ery,budgets and uncertain outcomes stymy investment,but these roadblocks can be overcome.“The big issue is how to get going.With a short,sharp assessment,you can understand where you are when it comes to data maturity.It doesnt need to be a long-drawn-ou

182、t process.But any data audit needs to be methodical,working out whats valuable and whats not.What this starts to do is generate an organi-sation-wide conversation about data,which is a crucial step,”details Horwood from Simpson Associates,which works with a vast range of organisations includ-ing the

183、 Natural History Museum,Barratt Developments,UK police forces and the Royal British Legion.There are misperceptions that unlock-ing the value of data is eye-wateringly expensive and all encompassing.In many cases,today,a data science,proof-of-concept can be easily rolled out within weeks,not months.

184、This can also work on discrete data silos and use cases.Results can be achieved quickly,demonstrating a return on investment.“If you get your data strategy right from the start,you can deliver value rapidly and efficiently.Eighty percent of data science involves preparing the data.Having a foundatio

185、n and methodology in place,knowing where you are,what you need and how you get there,is vital.This then unlocks the potential for any use case whether its machine learning,artificial intelligence or data analytics,”states the managing director of Simpson Associates,which is a Microsoft Gold partner,

186、holding four gold competencies in data and business intelligence.Demonstrating initial gains with a data strategy is important.It draws people,processes and culture into the equation after all,valuing data is a change-man-agement issue,but it requires a strong framework to drive it forward.The right

187、 questions need to be asked,while knowl-edge and experience is needed to artic-ulate what good looks like.“It is crucial to understand how to get the best out of your data otherwise any strategy will fail.That is why we deploy a robust data-maturity assessment.Understanding what the best use cases a

188、re in that industry,the market environ-ment and how that sector values data is also crucial,”says Horwood from Simpson Associates,which has recently earned the Great Place to Work Certification.“Starting small and then scaling mat-ters.Every organisation must show early wins and ROI when it comes to

189、 data-sci-ence projects,which can then be championed internally for further digi-tal-transformation projects.It also opens up the potential for valuing data in new ways from boosting productivity to mon-etising data-led services.In the current economic climate,there are efficiency gains to be made u

190、sing data to do more with less.”“Theres so much potential.Were only just getting started,”states Horwood.Think about your data strategy today with simpson-associates.co.ukMHarvard Business Review,2021 Starting small and then scaling matters.Every organisation must show early wins and ROI when it com

191、es to data-science projectsCommercial featureHow has the role of data evolved in organisations over recent years?In this digital-first world,increas-ing amounts of data are being pro-duced,shared and destroyed every second.Technologies to analyse vast volumes of data have also evolved with the resul

192、t that many organisations rely on data for meaningful insights and to take the right decisions.While some organisations still have a cen-tralised approach to data where employees work in the office and access data through secure servers more and more businesses are adopting a decentralised approach.

193、Now,employees are working remotely,accessing data from their own unsecured devices.What has been the impact of decentralisation and remote working?The pandemic created an era of forced,rapid digital transformation insti-gating a necessary rise in remote working.According to Buffers 2022 State of Rem

194、ote Work study,more than 95%of workers still want to work remotely at least for some time.But decentralising means businesses must democratise their data.This requires easy access to data analyt-ics which is driving decision-making,leading to increased data storage and management requirements.The ke

195、y to success for modern businesses is unifying data access and data sharing across business functions.Using data to automate and integrate workflows is one of the core benefits of a digital-first world.But the great challenge for modern busi-nesses is how they democratise their data without compromi

196、sing its security.What are the data security challenges in such an environment?IT teams became the front runners in the world of business through digital transformation,overseeing cloud adoption,artificial intelligence,machine learning,remote collaboration,and a host of other dig-ital services.Some

197、51%of IT decision-makers in the UK say that use of cloud solutions has increased for data-related purposes.However,democratisation removes the mid-dleman the IT team-and simplifies access to data by employees.We call it Shadow IT.This also increases the potential for cyberattacks as the secure syste

198、ms put in place by IT are bypassed by decentralised employees.The“attack surface”increases as grow-ing numbers of unsecured devices have access to the companys data.This leads to a spike in data breaches,phishing attacks and Distributed Denial of Service attacks.By improving the ease of access,busin

199、esses make the data accessible to everyone-including the attackers.IT teams must also comply with standards and regulations such as ISO,GDPR and CCPA without affecting the ease of work.What technologies and processes should organisations put in place to achieve secure data democratisation,and how do

200、es this impact company culture?In such an environment,implementing data protection policies is essential.That means the cybersecurity department must have visibility over the network,the infrastructure,the employee devices and event logs and be able to monitor the traf-fic in and out of these endpoi

201、nts.This allows the organisation to pick up on anomalies and unusual behaviour that indicate insider attacks and external cyberattacks.Typical processes include controlling access to data by both managed and unmanaged devices,securing endpoints and implementing mul-ti-factor authentication.However,a

202、 new ManageEngine study shows that while about 44%of deci-sion-makers in the UK believe that security is the responsibility of IT and cybersecurity teams,23%believe that its the employees responsibility too.Training IT teams and the wider workforce to recognise suspicious activity starts with creati

203、ng a culture of security which prioritises employee confi-dence,consistency and performance.How can organisations prepare for the future?Businesses will be driven by data that is self-operating,transformational,and decentralised.56%of decision-makers in the UK already believe that democrati-sation o

204、pens up more room for innovation.Companies will look for ways to create fric-tionless and secure data access.They will also need to develop a deep understanding of their data security challenges and invest in the right solutions.Ultimately,companies should look for accreditation from the Cyber Essen

205、tials scheme,a Government-backed and indus-try-supported programme to help busi-nesses protect themselves from cyberat-tacks and security breaches.With steps such as these in place,busi-nesses can face the data-driven future with confidence.For more information,visit manageengine.co.ukQ&AData securi

206、ty and decentralisationSridhar Iyengar,managing director at Zoho and ManageEngine Europe,offers a reassuring outlook on how to create modern workspaces that are adapted for modern risksC Y B E R S E C U R I T YDGlenn Carstens-Peters via UnsplashDATA STORAGE IS A PRIORITY IN CYBERSECURITY POLICIES Pr

207、oportion of UK firms citing the following as matters covered by their policiesHow data is meant to be stored76%Use of cloud computing56%Remote and mobile working61%Use of personal devices for business purposes51%How staff are permitted to use their organisations devices72%Use of network-connected de

208、vices56%What data can be stored on removable devices USB sticks,for instance56%Use of software as a service34%Statista,2022means we are adapting to new payments leaving their accounts at all times,”he says.“And many of our employees are working from home and at different times of the day,so we have

209、to get accustomed to a lot more unusual behaviour,such as someone logging on in the evening bec-ause they are working flexibly.We need to learn whats normal by feeding data into analytics packages that will flag up where we might need to investigate further,per-haps by calling the person concerned t

210、o verify that it was them logging on.You simply cannot do that type of safeguard-ing without using analytics to target where you need to be double-checking.”It is here that data analytics requires powerful machine-learning tech to start building up a picture of what everyday traffic looks like,given

211、 the millions of inter actions that flash across the average companys networks each day.David Hoelzer,director of research at Enclave Forensics,thinks that this is the key reason why approximately 50%of the people who attend his cybersecurity lec-tures for the industrys Sans Institute have a backgro

212、und in data.“About half of my students are data sci-entists who want to learn more about how to apply data to cybersecurity at their org-anisations,”Hoelzer says.“The industry ismoving to a point where data analytics is like a triage system that flags areas of concern,because humans cannot wade thro

213、ugh millions of data points hoping to get lucky and find unknown malware.”He continues:“The trouble is that many industry vendors have been overpromising for years,claiming that they can spot un-known issues before they become a threat.Many people may be forgiven for thinking that they already have

214、this cover or not believing what theyre being promised.”For Hoelzer,the risk is that,just as data analytics and machine learning are mat-uring to a point where they can accurately guide users to areas of unusual activity on networks,investment in them might be cut short.Given the power of analytics

215、to narrow down the search for bad actors,this would be a mistake.In particular,it would be a step back-wards in cybersecurity because,according to Sheldrake,the next wave of innovation will take company defences to the next level,where anomalies are not only spot-ted but fixed automatically.“Were mo

216、ving to the point where AI will not only be able to use data analytics to guide security teams to where unusual activities are taking place,”he says.“The next stage will be about using the data to find a problem and then solve it.These self-healing systems will be able to spot issues and then fix sy

217、stems on the fly.”That is the ultimate promise of data analytics in defending against cyber-crime.While the technology can already be used to cut down the noise of network traffic to highlight where threats may belurking,in the future it will be able to investigate anomalies and then report back to

218、the security team to confirm that its detected a problem and dealt with it.There will be millions of pieces of data to look at.But,with the right analytics,you can see what doesnt look normal It might not be anything to worry about,but you can narrow the field with analyticsR A C O N T E U R.N E T07

219、Cheesewright argues,adding that,in any case,“techniques for bypassing surveil-lance are widely understood”.Nonetheless,Vishal Marria,founder and CEO of enterprise intelligence company Quantexa,notes that the private sector,particularly the financial services industry,is making great use of AI in nip

220、ping crimes such as money-laundering in the bud.“HSBC has pioneered a new approach to countering financial crime on a global scale across billions of records,”he says.“Only by implementing contextual analytics tech-nology could it identify the risk more accu-rately,remove it and enable a future-proo

221、f mitigation strategy.”Alex Case,senior director in EMEA for US software company Pegasystems,believes that governments and their agencies can take much from the private sectors advan-ces.Case,who worked as a deputy director in the civil service from 2018 to 2021,says:“The levels of service being rou

222、tinely pro-vided by the best parts of the private sector can be replicated in government.In con-trast with the dystopian future depicted inMinority Report,the increasing use of AI by governments may lead to a golden age of citizen-centric public service.”Which other operations or business func-tions

223、 have the most to gain from advances in predictive analytics?Cheeswright bel-ieves that“the upstream supply chain is an obvious one in the current climate.If you can foresee shortages owing to pandemics,wars,economic failures and natural disas-ters,you could gain an enormous competi-tive advantage.”

224、The biggest barriers to wielding such fore-casting power are a lack of high-quality data and a shortage of experts who can analyse the material and draw actionable insights from it.“Bad data can turn even a smooth deploy-ment on the technology side into a disaster for a business,”notes Danny Sandwel

225、l,data strategist at Quest Software.“Data govern-ance underpinned by visibility into,and insights about,your data landscape is the best way to ensure that youre using theright material to inform your decisions.Effective governance helps organisations to understand what data they have,its fitness for

226、 use and how it should be applied.”Sandwell adds that a well-managed data governance programme will create a“sin-gle version of the truth”,eliminating du-plicate data and the confusion it can cause.Moreover,the most advanced organisations can build self-service platforms by establishing stand-ards a

227、nd investing in data literacy.“Data governance enables a sys-tem of best practice,expertise and collaboration the hallmarks of an analytics-driven business,”he says.Gilbert offers business leaders one final piece of advice in this area:recruit carefully.She argues that“a great data analyst is worth,

228、at a con-servative estimate,20 average ones.They can often do things that any number of average analysts working together still cant achieve.Whats more,a bad analyst will cost you both money and time.”And,as Minority Reports would-be crimi-nals in discover to their cost,time is the one resource that

229、s impossible to claw back.inority Report,Steven Spielbergs 2002 sci-fi thriller based on a short story by Philip K Dick,explores the concept of extremely proactive policing.The film,starring Tom Cruise,is set in 2054 Washington DC.The citys pre-crime dep-artment,using visions provided by three clair

230、voyants,can accurately forecast where a premeditated homicide is about to hap-pen.The team is then able to dash to the scene and collar the would-be murderer justbefore they strike.While police forces are never likely to havecrack teams of incredibly useful psy-chics at their disposal,artificial int

231、elligence has advanced to such an extent in recent years that its powerful algorithms can crunch huge volumes of data to make star-tlingly accurate forecasts.Could a Minority Report style of super-predictive governance ever become feasible in the public sector or,indeed,in business?If so,what would

232、the ethical implications of adopting such an approach be?There is a growing list of narrow-scope cases in which predictive analytics has been used to fight crime and save lives.In Durham,North Carolina,for instance,the police reported a 39%fall in thenumber of violent offences recorded between 2007

233、and 2014 after using AI-based systems over that period to observe trends in criminal activities and identify hotspots where they could make more timely interventions.To recreate a precognitive world,you would need an incredibly advanced,highly deterministic model of human behaviourThe appliance of p

234、rescienceAI has also been used to tackle human trafficking in the US,where it has helped the authorities to locate and rescue thou-sands of victims.Knowing that about 75%ofchild trafficking cases involve grooming on the internet,the governments Defense Advanced Research Projects Agency moni-tors sus

235、picious online ads,detects coded messages and finds connections between these and criminal gangs.In Indonesia,the government has part-nered with Qlue,a specialist in smart city technology,to predict when and where natural disasters are most likely to strike.Its systems analyse flood data collected f

236、rom sensors and information reported by citizens.This enables it to identify the localities most at risk,which informs dis-aster management planning and enables swifter,more targeted responses.While all these cases are positive exam-ples of the power of predictive AI,it would be nigh-on impossible t

237、o roll out a Minority Report style of governance on a larger scale.Thats the view of Dr Laura Gilbert,chief analyst and director of data science at the Cabinet Office.“To recreate a precognitive world,you would need an incredibly advanced,highly deterministic model of human behaviour using an AI dig

238、ital-twin model,perhaps with low levels of uncertainty being tolerable,”she says.“Its not certain that this is even possible.”An abundance of information is required to understand a persons likely behaviour,such as their genetic make-up,upbringing,current circumstances and more.Moreover,achieving er

239、rorless results would require everyone to be continuously scrutinised.“Doing this on a grand scale by closely monitoring every facet of every life;accu-rately analysing and storing(or judiciously discarding)all the data collected;and cre-ating all the technology enhancements to enable such a program

240、me would be a huge investment and also cost us opportunities to develop other types of positive interven-tion,”Gilbert says.“This is unlikely to be even close to acceptable,socially or politi-cally,in the foreseeable future.”Tom Cheesewright,a futurist,author and consultant,agrees.He doubts that suc

241、h an undertaking would ever be considered worthwhile,even in 2054.“The cost to the wider public in terms of the loss of privacy would be too great,”Advances in artificial intelligence are giving organisations in both the public and private sectors increasingly powerful forecasting capabilities.How m

242、uch further down this predictive path is it possible for them to go?AN EXPANSION FORESEENThe projected revenue growth of the global market for predictive analytics from 2020 to 2028Oliver PickupCommercial featurehe right insights are funda-mental to building watertight marketing strategies.More than

243、 ever,organisations are operating with a data-down approach to develop long-term loyalty,advocacy and engagement.To secure their seat at the top table,CMOs need to acquire new tools and market insights both strate-gically and organically.However,marketers are at risk of becoming inundated with infor

244、mation.As the volume and complexity of the data that they must respond to snow-balls,CMOs are struggling to identify reliable insights and translate them into decisions.A 2022 report by GfK and CMO Council revealed that 91%of mar-keters acknowledge the importance of responding to insights at speed i

245、n their role,but 55%only have slight or mod-erate confidence in their data analytics and insights.In the current economic climate,com-panies should be harnessing high-veloc-ity data marketing,not shying away from it and making sure their companies support the effort.“Marketing budgets are going to b

246、e scrutinised in the year ahead,so being able to demonstrate the value of marketing data and the decisions it informs is essential,”says Jutta Langer,vice president of consulting at GfK.The accelerated pace of modern business leaves little room for second-guessing,and CMOs need to show their strengt

247、h as data-driven lead-ers.To exceed consumer expectations,brands need to be sure that their data is highly relevant and optimised for quick decision-making.Langer continues:“If you dont have the right data insights,you will find it hard to deliver a consist-ent customer experience and youre more lik

248、ely to miss out on opportunities because you dont see the signals.”So how can CMOs ensure that they have the right timely data and solutions?The first step is making data legible and available.Storing data for easy access can also be incredibly complicated,and companies are falling into the trap of

249、pulling this information into silos that cant talk to each other-a strategy that may be working now,but will not be fit for purpose in future as the load continues to increase.With many CMOs at a loss,GfK is seeing rising demand for its gfk-consult service.“We plough through the data and insights 24

250、/7 and have a huge team of analytics experts who can give clients the confidence to build sound strategic plans and support their execu-tion,”says Langer.Actionable data lays the foundation for future-proof marketing strategies that can cope with the demands of modern consumers.First,businesses need

251、 to be more selective about their insight sources to make high-veloc-ity data marketing sustainable.“What organisations need is just a handful of relevant data sources,plus tech to help democratise and visualise it,and then skilled people who can interpret it and convert it to real-world actions,”ob

252、serves Gonzalo Garcia Villanueva,GfKs chief marketing officer.According to Garcia Villanueva,opti-mising the speed at which data can be analysed and insights shared should be a top priority for CMOs.“When Im look-ing at customer and market data and planning strategy,I want to know which campaigns an

253、d promotions are perform-ing best and should be replicated-and where we need to stop investments right away,”he says.“If you want to really cap-italise on timely opportunities or hedge risks,this exercise needs to happen every week.Otherwise,youre leaving money on the table.”Nearly a quarter of top

254、data marketing performers claimed to have real-time access to customer insights,compared to just 2%of the lowest performers.Garcia Villanueva believes that always on data analytics are key to driving the best value from marketing insights and achieving sustain-able brand growth essential for CMOs se

255、eking a stronger voice in the C-suite.Capturing up-to-the-minute intelli-gence from the business,its consumers,and its competitors is achievable through external tools such as gfknewron.Garcia Villanueva explains:“When you have data that shows the true sales uplift of your promotions for Black Frida

256、y and other peak seasons,you can optimise marketing strategy and future promotions to drive sustainable growth and brand premium.”To respond to insights at scale and pace,ease of use needs to be a priority.Organisations should be putting accessi-ble structures in place that enable mar-keting teams t

257、o make tactical decisions quickly.But many cant afford the luxury of waiting to build those systems internally.Time is of the essence,and Garcia Villanueva urges other CMOs to be bolder in data strategy.“If you spot the right opportunity using data from a platform like gfknewron,youve paid for your

258、tech-nology costs for the next three years,”he says.CMOs who let their data do the work are better prepared to manage future disruptions,minimise losses,and tap into consumer purchasing habits to level up their strategies and hold that seat at the executive table.For more information,visit CMOs guid

259、e to building data-driven consumer connectionsHigh-velocity data marketing promises real-time answers to consumer demands,but to keep those promises,marketers need essential trust in their dataCommercial featureT What organisations need is just a handful of relevant data sources,plus tech to help de

260、mocratise and visualise itThree data mistakes CMOs should avoidTo help put chief marketers on the right path with data,Garcia Villanueva cited several critical mistakes that can prevent CMOs from climbing the high-velocity data marketing curve.Frequency is keyOne pitfall that CMOs can fall into is n

261、ot looking at data often enough.Garcia Villanueva cites the example of washing machines and fridges.“We dont buy them very often but if your fridge breaks and you need a new one,youll have a new one within 48 hours,”he says.“As a brand,if your messaging was off that week,then youve missed that oppor

262、tunity and left money on the table.”When it comes to data,curate aggressivelyThe second concern is that CMOs are trying to process too much data.“You might have 100 or 200 potential data sources,but in reality,perhaps four of them matter,”Garcia Villanueva continues.Rather than trying to pull in mor

263、e data,companies should redirect their focus to identifying the most important market insights and establish systems that will make that data easy to visualise and understand.Democratising data breaks down barriersA major roadblock for many CMOs is that data is not being democratised.“If you have th

264、e right people and the right partners,you can democratise that data more quickly,”CMOs should look to remove barriers to data sharing and decision-making in some areas,Garcia Villanueva adds:“I dont wait for the market research team to show me data when Im making decisions.Im going to look at leads,

265、see which campaigns are working best,and then make choices on what I need to replicate,or change.”With these watch-outs in mind,CMOs can leverage carefully selected data and tools to keep securing loyal customers and confirm their own roles as future-focused leaders and collaborators.of marketers ac

266、knowledge the importance of responding to insights at speed91%only have slight or moderate confidence in their data analytics and insights55%CMO Council,2022A R T I F I C I A L I N T E L L I G E N C EM$41.52bn$5.29bn20282020Chris Liverani via UnsplashVerified Market Research,2021F U T U R E O F D AT

267、A08With the demand for data rising expo-nentially,data centres need a lot of energy to stay running and cool.Specialised computing equipment can emit large amounts of heat.Its impor-tant to regulate this to keep the system functioning.Traditionally,that was achieved by creating almost sub-zero,freez

268、er-like conditions,but in recent years the sector has learnt that data centres operate most efficiently at ambient temperatures of between 18C and 27C.As recently as five years ago,40%of the total energy consumed by data centres was used in the cooling of equipment.That proportion has since fallen t

269、o about 10%.Although this is the era of air-based cooling,experts agree that liquid cool-ing in which heat from equipment is transferred to a liquid and siphoned away is relatively energy-efficient.As Lawrence points out:“Air-based cooling pushes the hot air out of the system you exhaust it.And that

270、 is wasted energy.”As opportunities to use waste heat from data centres as an energy source proliferate,liquid cooling is set to become an increasingly important technology.Even in heavily insulated pipes,hot air cant travel very far before cooling too much.Hot liquid,on the other hand,is far more t

271、ransportable.“The other thing about direct liquid cooling is it requires very little water,”Lawrence says.“It will be easy to use.”Five ways to build resilient data centresC O N T I N U I T Y P L A N N I N GNatasha Khullar RelphWaste heat utilisationLiquid coolingn 19 July,as the UK faced rec-ord hi

272、gh temperatures,Google Clouds data centres in London were experiencing cooling failures,resulting in connectivity problems and outages.Oracles data centre was also forced into a protective shutdown,owingto what the company called the “unseasonably high temperatures”.As global temperatures continue t

273、o rise,the changing climate threatens the uninterrupted services of data centres.In a recent survey of operators by the Uptime Institute,45%of respondents reported that they had experienced an extreme weather event that had threat-ened the continuous operation of their facilities.Moreover,9%confirme

274、d that they had suffered an outage or signifi-cant disruption as a result,which made Across Europe,tech companies are ex-perimenting with waste heat recovery from their data centres.Meta has been reusing heat from its centres to warm 6,900 homes in Denmark,for instance.Microsoft,meanwhile,has powere

275、d a data centre in Finland with carbon-free energy and recycled the waste heat to nearby homes and businesses.Energy-efficiency agency Codema has part-nered with an Amazon data centre in Ireland to capture waste heat for use in homes and council buildings.And inSweden a project called Stockholm extr

276、eme weather one of the biggest causes of service failures.The number of data centre outages around the globe is increasing year on year,although this is because more centres are being built than ever before.According to the International Data Corporation,about 500,000 centres were handling the world

277、s data traffic in 2012.The total in existence today is close to 8 million.“The industry is getting much bigger and certain companies in it are bec-oming more powerful,”observes Andy Lawrence,executive director of research at the Uptime Institute.“When they fail,more fails.”He notes that were all bec

278、oming far more dependent on data centres.This means that,when one does fail,it has a Data Parks has been running in part-nership with the citys government,the local heating and cooling agency,and several data centres.The goal is to heat 10%of the capital by 2035.“In Germany,data centres have evolved

279、 from being enemies of the state to becoming one of the heat sources,”reports Stefan Mink,head of TechOps hosting at Ionos,who has been respon-sible for the planning,construction and management of 20 data centres in Europe and the US.“Its become a cir-cular economy,whereby the data cen-tres are usin

280、g the energy but then also providing energy in terms of heat use.”wider-reaching impact.A quarter of respondents to the Uptime Institutes survey said that their most recent out-age had cost more than$1m(900,000)in direct and indirect costs,with a fur-ther 45%reporting that theirs had cost them betwe

281、en$100,000 and$1m.Data centres are notoriously bad for the environment.They have the same-sized carbon footprint as that of the aviation industry and are set to account for 3.2%of the planets total greenhouse gas emissions by 2025,while consum-ing a fifth of the worlds electricity.Consequently,effor

282、ts are focused on how data centres can meet the demands of digitisation and create infrastructure resilience,while having as little impact as possible on the environment.These are five of the most popular solutions.A 2017 white paper from the Alliance for the Strengthening of Digital Infra-structure

283、s in Germany had noted that the 13 billion kilowatt-hours of electric-ity that was converted into heat in the nations data centres over the year would,if reused,have met the annual energy needs of Berlin.In 2019,investment analysis of waste heat from data centres showed that the process of reuse was

284、 a financially viable option and could provide an attractive return on investment for companies.Moreover,by helping to take pressure off the main grid,the process would eventually come back around and help to make the data centres themselves less prone to outages.But there is still some way to go be

285、fore waste heat utilisation can enter the mainstream.Most data centres still use air-based cooling.Because air isnt an efficient transport medium,consumers of the captured heat need to be located near a centre.Added to this,the infra-structure would need to be upgraded.“Capturing and reusing heat wo

286、uld require a full overhaul of your entire facility,while other options may be less invasive to your hardware set-up,”observes Daan Terpstra,executive chairman of the Sustainable Digital Infrastructure Alliance.“But,with a typical hardware refreshment cycle of data centres being somewhere between fi

287、ve and seven years,I think this is an ideal moment to start plotting the chart and placing this at the top of the list.”ORemote storage facilities are becoming increasingly vulnerable to extreme weather events.Can improving their ability to withstand such threats be achieved in an environmentally su

288、stainable way?12Underwater data centresMicrogridsArtificial intelligenceSeveral of the worlds tech giants have set ambitious renewable-energy targets for their data centres.For instance,Meta,which has more than 20 centres,com-mitted to 100%renewable energy in 2011,followed by Apple,Google and Amazon

289、.Microsoft has pledged to become carbon-negative by 2030.It has also committed to removing all of the carbon the business has ever emitted,either directly or by electrical consumption,since it was founded in 1975,by 2050.A blog post on its website states:“To reach this,data centres must be part of t

290、he solution for broad decarbonisation.”Nonetheless,buying carbon offsets is the method by which many big tech companies are aiming to achieve net In 2018,Microsoft ran Project Natick,dropping a data centre containing 855 servers 35m below the sea just off the Orkney Islands.The aim was to insulate t

291、he facility from extreme temperature fluctuations and test whether under-water data centres could be reliable and practical while using energy sustainably.Two years later,the company retrieved its data centre and found that only eight servers were down.Microsoft said that Most data centres have mult

292、iple sour-ces of power so that,if one source fails or goes down,another can keep them functioning.Resilience has always been a primary concern for data centre operators.While the threats and the solutions might be evolving,the ability of a data centre to withstand failures cost-effectively remains p

293、aramount.Microgrids are increasingly being seen as an excellent back-up solution for data centres.A microgrid is an autonomous local energy grid that ena-bles you to generate your electricity,which means that it isnt dependent on the traditional grid.It can not only keep the data centres power on du

294、ring grid outages;it can also store electricity and sell it back to the grid.“So many outages are happening that any critical facility whether its a hos-pital or a data centre is thinking about how to ensure that its able to run if the grid goes down,not just for an hour or two but potentially for d

295、ays or weeks,”says Jayesh Goyal,chief revenue officer at Enchanted Rock,a company thats been contracted by Microsoft to dev-elop Californias largest microgrid.The facility will use renewable natural gas and provide Microsofts San Jose data centre with auxiliary power.What makes microgrids especially

296、 noteworthy,Goyal says,is that you can choose how you want to power them.Renewable,natural gas or fuel cells the choice is yours,constrained only by cost and space.Natural gas is a popular fuel choice for microgrids because of its accessibility and relatively small zero,which means that they will,in

297、 effect,still be using fossil fuels.That situation may change quickly,experts believe,partly because of societal pres-sure and upcoming legislation.“Based on the current social and eco-nomic climate in continental Europe and the UK,sustainability will become a licence to operate,”Terpstra says.AI is

298、 one of the most cost-effective and scalable tools for improving the energy-efficiency of data centres.In 2018,for instance,Google and DeepMind jointly developed an AI-powered recommend-ation system to control the cooling of data centres,resulting in claimed aver-age energy savings of 30%.The use of

299、 AI can offer more than energy and cost savings.Theres also resilience.Alibaba Cloud,for instance,the equivalent figure on land over the same period would have been 64.Subsea Cloud,which plans to start operating an underwater data centre off the west coast of the US before the end of this year,claim

300、s that constructing underwater data centres is cheaper and could reduce carbon emissions by 40%.In a bid to meet their stated targets,Microsoft and other big companies are experimenting with ways to make data centres more sustainable.While this is to be lauded,many of their experiments environmental

301、 footprint.But whats exciting to many experts is the oppor-tunity to use hydrogen fuel cells.In 2020,Microsoft worked with Power Innovations to power an array of data centre servers for 48 hours using fuel cells with a first-of-its-kind hydrogen generator.Hydrogen is described as a clean fuel becaus

302、e water is its sole by-product.But it occurs naturally only in compound form and the cost and technology required in separating it from other elements have been prohi-bitive.This situation has started to change,though.As it does so,hydrogen-has deployed machine-learning-based temperature alert syste

303、ms in its global data centre.In July 2021,the firms prin-cipal engineer,Wendy Zhao,told indus-try publication Data Centre Dynamics:“We took hundreds of temperature sen-sors monitoring data,using an ensem-ble graph model to quickly and precisely identify a temperature event due to cooling facility fa

304、ults.It generated alerts much further in advance and provided the data centre operation team precious time to respond to the fault.”Microsoft is developing an AI system to analyse data and generate alerts to“prevent or mitigate the impact of safety incidents”,while Meta is investigating ways in whic

305、h AI can anticipate how its data centres are likely to operate under “extreme environmental conditions”.fuelled generators and microgrids start to look like a real possibility.Terpstra believes that hydrogen fuel cells will need to be used in more than microgrids and back-up generators.Building a da

306、ta centre fully powered by hydrogen fuel cells is the only route to cost-effectiveness,he argues.“The calculations Ive seen mean that the costs of setting up hydrogen back-ups versus the number of times youd need them are completely out of bal-ance,”Terpstra says.“The run-time on back-ups is too lit

307、tle when compared with the investments required.”543are impractical in terms of both cost and scalability,according to Terpstra.“It may be super-cool to have under-water data centres,but there are so many other solutions possible that would result in the same effect by looking at the reliability and

308、 climate impact from a holistic design viewpoint,”he says.For Terpstra and several other experts in this field,its all about practical meas-ures that can move the needle now and will continue to create an impact as the infrastructure improves.Keng Po Leung via Alamy Stock PhotoAleksei Mukhanov via A

309、lamy Stock PhotoRstudio via Alamy Stock Photo Cao via Alamy Stock Photo Maurice de Vries via Alamy Stock PhotoR A C O N T E U R.N E T09Commercial featureKohl.But all too often,managers who want to apply data to make smarter decisions are faced with a debilitating lack of technical know-how.Departmen

310、t heads want to analyse data in a way that enables them to detangle functional insights from assumptions and use these insights to report with confi dence to the executive leadership team.To achieve this independently,they need access to nuggets of information that can inform timely,intel-ligent dec

311、isions.However,many analytics and BI tools are still targeted at the needs of technical users rather than the needs of the business itself.They require extensive training and skill to use,which makes them inaccessible to the everyday line-of-business user.If a manager wants to understand why a certa

312、in area of the business is performing in a certain way,they need to call in the BI experts.And the result is slow or even no decision-making.The Pyramid Analytics Decision Intelligence Platform is a prime example of a streamlined,unifi ed and personalised decision intelli-gence platform that allows

313、non-technical employees to access and analyse multiple data sources in an AI-driven no-code envi-ronment.“Everything is drag and drop and point and click,”Kohl explains.“You dont need to know how to write code but you can still do very deep,very sophisti-cated research on your data.”Increasing the a

314、vailability of analytics and creating greater overall visibility means anyone can draw valuable insights from data fl owing into the business quickly,without relying on hypo-thetical assumptions.Going one step further,prescriptive ana-lytics uses AI to offer actionable recom-mendations based on insi

315、ghts and trends,as opposed to speculation.The outcomes can be tangibly fi nancial,organisational,and even environmental.A power plant,for example,could determine what mix of energy sources they should be using to maximise effi ciency and minimise their carbon emissions,with-out bringing in analytics

316、 experts.Personalised experiencesData is integral to almost every business function,so fi nding a more accessible way of interacting with analytics is key to developing a healthy data culture across teams.The onus is on business intelligence and analytics tools to meet organisations where they are.N

317、on-technical users who are uncomfort-able using even basic point-and-click and drag-and-drop BI tools can still intuitively interact with data visualisations using plain English,via a Natural Language Query(NLQ)chatbot.Pyramids NLQ chatbot,for instance,allows users to type or use voice commands to q

318、uery data natively and directly in the data source,regardless of location,size or com-plexity.This means anyone in the business can fully investigate data without needing to know the underlying data structures,hierar-chies and measures,with the platform gen-erating actionable insights that can then

319、be shared in a report or presentation.“If you see an underperforming salesper-sonyou can start asking is it the product that hes selling?Is it his territory?Is it the demand generation engine behind him?Is the cost of the solution that hes selling too expensive based on the competition?You can start

320、 peeling the onion,even as a non-techni-cal user,and go very deep,”Kohl explains.AI and ML can tailor the analytics environ-ment to an individual,ultimately generating more data-driven decision-making.“It could be automated insights that we push to your morning dashboard:here are the fi ve things yo

321、u need to know about your business that happened in the last week,”Kohl explains.Democratisation is a win-win.Reducing one-off requests means freeing up data analysts to focus on more strategic work.Instead of providing reports and dashboards,they are empowered to provide predictive and prescriptive

322、 insights that allow them to identify core business strengths and double down in those areas.For this to work,companies need to develop a lateral approach to analytics,equipped with intelligent tools that bring new voices into the conversation.To learn more about applying augmented analytics,decisio

323、n intelligence and AI in your enterprise,visit many organisations,data is at the centre of fundamental deci-sion-making,providing business leaders with guidance on how and when to act.But this new emphasis on analytics may leave technical teams burdened by a backlog of additional tasks while their n

324、on-technical counterparts struggle to contribute.As companies become more connected and data-driven,the question is no longer if data should be made available to more people in an organization even everyone in an organization-but how.Of the estimated 130 software offerings in the analytics and busin

325、ess intelligence(BI)space,few have evolved to meet the needs of modern,data-driven businesses.Where most BI products have yet to catch up,tech-nical professionals are fi lling in the gaps to support line-of-business staff.A growing number of enterprises are working towards company-wide adoption to t

326、urn data into actionable insights across the board,start-ing with the embrace of augmented analytics tools that incorporate artifi cial intelligence(AI)and machine learning(ML).Calls for continuity The use of different BI and analytics tools by different teams and departments has created a complex I

327、T landscape that often obscures up with lots of siloed implementations that advance a specifi c function but dont provide a view of the entire company.”These siloed implementations have occurred against a backdrop of explosive data growth.A decade ago,businesses had limited access to data and accura

328、te,acces-sible insights that analytics provides.Today,data is abundant,whether structured or unstructured,in small,independent data sets or large infl ows of insights that talk to one another.The value is in how information powers decision-making across the business.This vast wealth of data is const

329、antly in motion.“Data used to be stuck in an enterprise data warehouse,”says Kohl.“Now its moving to data lakes.Its moving from on-prem to the cloud.Its moving from cloud to multi-cloud,and so forth.”Keeping up with this sustained movement is a challenge and business intelligence needs to adapt to s

330、upport new levels of operational fl exibility.Democratising decision-makingNavigating this complex data environment and using insights to drive smarter busi-ness decisions requires clear leadership.“If Im a manager of a group of people and I dont make data-driven decisions,my team wont make data-dri

331、ven decisions,”says AIAIs core mission is to inspire and empower women,underrepresented minorities,and people from lower socio-economic back-grounds to successfully pursue an educa-tion and career in analytics.The Pyramid Decision Intelligence Platform supports Vasseurs Step Into Data workshops,whic

332、h have provided more than 2,000 learners in 30 countries with hands-on experience in data analytics.What has traditionally limited access to AI,analytics and data-driven insights?Its easy to use our gut feelings,to keep going with our own biases.But as soon as you become data-driven,your biases are

333、exposed and thats not some-thing we naturally want.It forces us to change;it forces us to be humble,and thats not always easy.Secondly,good,qualitative data data that is prepared,curated and ready for analysis is much scarcer than you might think.A lot of people say,Id love to have more insight,but then they get their hands on some data and its a mess.Youre not going to get much from data that is