Data science skills for your IoT programme success

Over the past 10 weeks, our experts have been in conversation with Internet of Things (IoT) deployment leads to understand critical success factors and challenges. One major finding stands out. Over and over again, we heard the same message: projects are at risk because of a shortage of data science skills.

Organisations simply cannot find the data management and analytics skills. They need to take advantage of their IoT deployments. Analytics is a key part of exploiting their new resource, and there is a worldwide shortage of data scientists. But it doesn’t have to be this way.

In our view, there are three ways that organisations can acquire the skills that they need to seize the moment: they can build, borrow or buy.

Data Science

Building competence

This is perhaps the most obvious: customers can develop their own staff, to ensure that they have the skills that the company needs. But while most of those interviewed could articulate the skills that they needed, very few were able to suggest how they could support their staff to develop those skills. Data science is not something that is widely taught as yet.

It is precisely to address this need that back in April this year, we launched the Academy for Data Science. It provides certified training for data scientists. Our customers and others can use this academy to create an in-house development programme for their staff, to provide skills tailored to the company’s need. The six-week training modules include theory plus case studies or team projects, coaching and an exam to achieve certification. Although the course focuses on SAS packages, trainees emerge with a general certificate in data science.

Borrowing skills

The second option is to borrow the skills from elsewhere. We found that a number of companies surveyed had gone down this route, forming partnerships with firms that had the necessary skills in developing and handling IoT technology. Professional services firms like SAS have access to experts in analytics and data handling. What’s more, these firms ensure that their experts’ knowledge is kept up-to-date by regular training and professional development. It is a time-effective way of ensuring access to the latest skills and technology.

Of course the big drawback of ‘borrowing’ skills is that eventually you have to pay back the loan, as it were. The borrowed experts have to leave and move on to somewhere else. But a combination of borrowing and building can pay off in the longer term. Borrowing fills the immediate skills gap, and building then starts to take over. What’s more, ‘home-grown’ staff developing their skills through training and certification programmes can work alongside borrowed consultants for a while, shadowing them and learn ‘on-the-job’ as well as during their training sessions.

Buying into capabilities

The final option is to buy. This could be in the form of recruiting skilled data scientists who will be ready immediately. The problem with that, though, is that they are few of them. There are not enough to go round, and anyone wanting to recruit has to consider what they have to offer to attract and retain this rare breed.

Fortunately, there are other options: to buy pre-configured solutions that reduce the need for manual intervention by skilled professionals.  There are several ways to do this:

  • a plug and play module
  • a more dynamic data lab
  • an online ‘cloud’ analytics-as-a-service capability.

For example, the Analytics Fast Track™ for SAS® (AFT) is a‘plug-and-play’ analytics module designed to enable businesses to get value out of it fast. The idea is that business simply turn on, add data, and start to benefit immediately. Built in partnership with Intel, this suitcase styled configuration comes pre-configured and ready to go.

For teams who need to support many and as yet unknown projects, a big data lab might be a better option.  This is an environment designed for experimentation and ‘fast failure’, and to generate value from a very early stage. It comes with requisite data science support elements so teams are not stuck at any point.

The ultimate in the ‘buy’ spectrum is a fully functional cloud capability. SAS Viya™ for example provides high-performance cloud-based visualization package designed to be accessible and scalable for individual business users. It is suitable for any analytic challenge, large or small, and also helps with technology integration.

The hybrid model will be the most sustainable for Data Science

Immediate skills shortages do not need to hold anyone back from exploiting IoT opportunities. Whether you decide to build, buy or borrow, or some combination, there are options out there. What will you choose? We can help you in that: join us on Friday 5th August for a discussion on analytics skills evolution. This is an open discussion on Twitter, and no registration is requires. Just follow the #saschat hashtag which will be most active between 15 and 16 hrs CEST.

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Better Analytics Today, Better AI Tomorrow, Starts With Summer Reading

‘We are entering a third era of automation, in which machines encroach on decision-making. But there is still a role for wetware.’ - Tom Davenport, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines (2016)

As we work day in and day out using analytics to drive innovation in our organizations and in society, I think it’s essential that we realize our data science today is very much shaping the way we will live and work with machines in the future. That’s why I was very happy to see how Only Humans Need Apply: Winners and Losers in the Age of Smart Machines emphasizes how we need to be conscious of the current artificial intelligence revolution and really work to make sure human intelligence remains complementary.

“Oh fantastic,” I hear you sigh, “Another ‘must-read’ to add to the list. Because I’ve just got so much free time to read these days.” Well, that being the case, I still recommend you make some time for this one during whatever summer holiday you manage to carve out and….watch out…I’m going to add a few more essential whitepapers to your list a bit further on.

From Stephen Hawking to Bill Gates through to Elon Musk, big brains have highlighted both the potential, as well as the risk of Artificial Intelligence. Logical then that Tom Davenport contributes a ruthlessly pragmatic, but still fun to read, account of what we as knowledge workers can do now, not only to keep up (and keep our jobs), but also to ensure that ‘augmentation’ (the idea that human intelligence plus artificial intelligence needs to be more than the sum of the individual parts) actually occurs.

This isn’t the first time Davenport has treated a hot tech topic to make it digestible. Davenport’s milestone book, Competing on Analytics is now ten years old! When the book came out in 2006, data mining was still very much happening in dusty corners of the organization, sometimes leading to strategic insights to influence strategic decisions, but mostly becoming watered down when it came to influencing actual operational decisions. With a mission to bring analytics into the corporate mainstream and help make data science a boardroom concern, SAS even organized some very successful events with Tom here in Belgium.

The new book made me reflect on where things stand today. While analytics HAVE become an essential part of doing business, there is still a need to continually innovate as a competitive weapon. Today, there is more of everything (data, computing power, business questions, risks and most importantly, analytics consumers). The ability to scale your organizational analytical power is more essential than ever for staying ahead of your competition. And at the same time, in order to balance both the potential and risks of artificial intelligence, we all need to step up our game. Computers can and will do more intelligent work, but we also need long-term thinking about what and how we teach intelligent machines.

So with equal attention for what’s good for organizations today, as well as for planning the artificial intelligence augmentation of tomorrow, I wanted to bring attention to a few recent SAS whitepapers which address some key topics for meeting the growing demand for analytics.

Reading these whitepapers will give concrete suggestions about making your analytics scalable to drive more efficient decision making. While reading them though, I suggest trying to also think about how these analytic process lifecycles need to be enriched with human insights.

  • How do we develop models not only in line with organizational strategy, but with the organizational conscience?
  • When establishing data labs for building predictive models, how do we think in terms of correct model behaviors, instead of correct model outcomes?
  • When engaging machine learning, how do we ensure that such learning is holistic, not just maximizing expected utility from a logical perspective, but fully humanist?

Heady topics, but I’m convinced they are essential considerations if we as data scientists are to make positive contributions to artificial intelligence evolution. I’d be interested in hearing anyone’s views on this.

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Analytics in action – the world (domination) is not enough

I’m sure you’ve heard of Blofeld, Goldfinger and Dr No, right? Well these evil villains and adversaries of Her Majesty’s most famous secret agent had one thing in common: their devious plans for world domination, complete with all the facts and figures, always featured on oversized screens.

Analytics in action - image

Even if world domination doesn’t feature in your business model, visualising your plans can still be helpful when on the hunt for new ideas. In fact, this approach works equally well in meetings with colleagues and management alike.

Visualisation is the common language that unites the different roles within a company. Aside from the silver screen, data visualisation is no longer restricted to just the big global players; it requires a strong level of analysis, which even medium-sized companies can use to find trends in their data. In doing so, they are able to uncover new revenue potential, improve their services, anticipate issues and thereby gain a competitive edge.

The advantages of having an edge afforded by digitisation and globalisation include close customer relationships and loyalty. But needless to say, having information available so quickly and readily has made customers more demanding than ever.

Speed and quality are of paramount importance to customer satisfaction, which has been demonstrated in a number of studies. This means that 80% of unsatisfied customers will permanently walk away from a company that doesn’t respond quickly enough.

Information is key to improving customer relationships. It can be provided through a variety of different sources and sectors, including emails, phone calls, social networks and even surveys.

Structured and unstructured text data offers valuable insights if it is focused on a particular outlook or existing activity (such as resignation) in the right context.

Companies are often lacking not only in the analytical tools required to evaluate the available data, but also in the employees capable of using them. Data scientists are expensive and hard to find. With this in mind, an alternative option of providing end users within specialist departments with the necessary power requires an analytical approach. In most cases, they quickly come to the relevant conclusions on their own, and can then work side by side with the existing data scientists.

This is where SAS offers a smart introduction to analysing text data (without any prior changes being made), which can be performed securely and directly in the office environment without the need for statisticians or data scientists.

Not everyone can rely on Q for technical and analytical support, but plenty of people have the intelligence and strong power of deduction to handle this.

Here’s an example of how text data in Excel can be transformed into a word cloud at the click of a button, highlighting initial trends across the files.

Highlight the text data in Excel …

excel sheet - blogpost

… and generate an initial overview of the content at the touch of a button.

VA report - blogpost

More wonderful and inspiring insights and best practices of data visualization can be found here

I’d love to hear from you on this blog, so please feel free to leave comments.

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Long live the IoT hype!

Long live the IoT hype!

Why Gartner is "wrong" and the Internet of things hype won’t drop.

Internet of things, IoT, connected cars, Industry 4.0, Insurance 4.0, smart factories, smart homes, smart cities, smart police, smart banking, smart grid, smart … where will it end? If there’s one thing the Internet of things isn’t short of, it’s names. A sure-fire way to tell that marketing bods the world over have most definitely jumped on the bandwagon of this hot topic. Expectations have reached epic proportions. Technologies and infrastructures are still in their early phases of development. Processes and companies are not yet ready. And if dreams and reality get too far apart, this kind of disillusionment can only set us up for a fall. This is what Gartner describes in its Emerging Technology Hype Cycles, and exactly what the 2015 Hype Cycle predicts for the Internet of things.

This is where Gartner is wrong – and yet right on the money.

Read More »

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Cyberangrep, hvor skal vi se etter fienden?

“Cybersecurity is the greatest threat the world has faced since the atom bomb” uttalte Apple gründer Steve Wozniak i intervju på australsk TV for litt siden. Bak denne overraskende uttalelsen ligger erkjennelsen om at det, slik som for atombomben, ikke finnes sikre gjemmesteder eller trygge havner for cyberkriminalitet.

Gjennom nyhetskanalene har vi hørt om at elektroniske anslag både kan slukke strømnettet og slå av internett. Internasjonalt har politiske rivaler bilateralt slått ut den andre parts støttesystemer eller massive propagandakampanjer. Eksperter innen kommunikasjonsteknologi frykter at terrorister i teorien både kan ta over kontroll av rutefly, jernbanenett og atomkraftverk.

For å kartlegge økonomisk kriminalitet og elektroniske angrep rettet mot deler av norsk næringsliv, gjennomførte SAS Institute en spørreundersøkelse rettet mot helse- og omsorgssektoren og annen kommunal virksomhet. Undersøkelsen var anonym og henvendte seg direkte til ledere. Resultatene fra undersøkelsen plasserer frykten for å bli utsatt for elektroniske angrep øverst på trussellisten samtidig som det uttrykkes bekymring for å skape tilstrekkelig forståelse og erkjennelse blant egne ansatte for at angrep også vil ramme offentlig sektor.

Har vi gjennomført de viktigste og de riktige tiltakene mot cyberangrep? Hvilken pris versus kostnader er knyttet til å rydde opp i slike hendelser hvor inntrengeren allerede har kommet seg innenfor forsvarsverket?

Har vi gjennomført de viktigste og de riktige tiltakene mot cyberangrep? Hvilken pris versus kostnader er knyttet til å rydde opp i slike hendelser hvor inntrengeren allerede har kommet seg innenfor forsvarsverket?

Det gjelder alle andre
For mange oppleves imidlertid trusselen om elektroniske anslag som fjern. Det er bare noe vi hører om i media, som ikke rammer egen virksomhet. Derfor har vi kanskje ikke et tilstrekkelig bevisst forhold til selve kjernen i problematikken.

Flere internasjonale undersøkelser har sett nærmere på dette og det viste seg dessverre at mange virksomheter som er rammet, ikke vet hvem inntrengeren er. I gjennomsnitt hadde inntrengeren vært innenfor forsvarsverket i 205 dager og i 60% av tilfelle brukte virksomheter mer enn tre måneder før de oppdaget inntrengeren. I de fleste tilfellene gjennom at kundene eller myndighetene hadde fattet mistanke.

Nærmere analyser av disse angrepene viser at i de fleste av tilfellene ble disse karakterisert som sofistikerte og målrettede angrep hvor angriperne systematisk og bevisst gikk etter de mest sensitive eller kritiske data. Analysene konkluderer med at sikkerhetsstrategiene vi har brukt inntil nå blir stadig mindre effektive mot denne typen angrep.

Etablere en sikkerhetsstrategi
Intrusion Detection System (IDS) og Security Information and Event Management (SIEM) er regelbaserte systemer som for bl.a. nettverksdata kalkulerer mistanke om uautoriserte forsøk på tilgang og inntrenging med påfølgende blokkering og varsling. Prosessen kan delvis automatiseres.

En av utfordringen med å implementere disse typer system, er at det produsere betydelige mengder med nye data i form av logger og alarmer. Slik genereres det nye oppgaver og et behov for et omfattende apparat som i ettertid må følge opp resultatene. En slik reaktiv strategi foregår ofte primært ved bruk av manuelle rutiner som medfører tapt tid og sent iverksatte tiltak.

Nå har vi lært at beskyttelse mot elektroniske anslag krever en mer proaktiv tilnærming. Vi må legge om gamle rutiner som var rettet mot virusangrep, brannmurbeskyttelse og nettverkslogger. De fleste eksperter er i dag enige om at en offensiv forsvarsstrategi må ta utgangspunkt i at:

  • Angriperen vil i det lange løp lykkes pga. deres overlegne styrkeforhold
  • Virksomhetsstrategien bør ha som utgangspunkt at inntrengere allerede har kommet seg på innsiden

En proaktiv forsvarsstrategi og best mulig beskyttelse handler med andre ord om å innføre en realtidbasert risikoanalyse. En analyse der man oppdager nye avvikende bruksmønstre som gir muligheter for raskt å kunne identifisere og isolere områder i virksomheten med høy risiko. Slike områder kan f.eks. være fysiske områder, avdelinger/organisatoriske enheter eller fagnettverk.

Så hvordan kommer vi oss fra en reaktiv handlemåte bygget rundt rapportering på allerede innsamlede nettverksdata og logger til en proaktiv løpende overvåkning og deteksjon av risikobildet?

Informasjonssikkerhet basert på en risikobasert tilnærming
Å gjennomføre denne type kontinuerlig sikkerhetsanalyse, A Risked Based Approach, stiller ekstrem krav til systemets skalerbarhet og evne til å takle raske skifter, store volumer og høy hastighet i datautbud. Virksomhetene må tenke moderniseringsstrategi og implementasjon som evner å fange store og skiftende datamengder gjennom utallige kanaler og med teknologier som muliggjør rask og nøyaktig analyse. En typisk Big Data problematikk.

Vi i SAS Institute arbeider internasjonalt sammen med et bredt spekter av virksomheter for å få på plass forretningssentrerte og kostnadseffektive løsninger for disse utfordringene. En av komponentene i vår løsningssuite er den hybride analysemotoren som scorer risiko, finner mistenkelige korrelasjoner, identifisere hendelser og visualiserer mønstre av interesse som kan tyde på ondsinnet atferd på innsiden av virksomhetens forsvarsverk.

Med bakgrunn i våre erfaringer mener vi derfor at en risikobasert tilnærming som gir øyeblikksbildet og en hybrid analysemotor der indikasjoner på anslag kan sjekkes mot hverandre, gir virksomhetene en holistisk risikobasert oversikt gjennom å:

  • Identifisere timing knyttet til hendelser. Finne mønstre eller sekvenser av forekomster knyttet opp mot tid
  • Få innsikt i forskjeller i resultater basert på data fra ulike kilder. Fores virksomheten med falske data?
  • Kunne rangere trusselbildet og forutsi videre utvikling
  • Identifisere muligheter for å iverksette automatisering av tiltak
  • Skape plattform for dypere årsaksanalyser og nye strategier

Vår brukerundersøkelse innen offentlig sektor og helse viste helt tydelig at virksomhetene ønsket å møte trusselen for å bli utsatt for elektroniske anslag med forbedrede rutiner knyttet til informasjonssikkerhet. Men samtididig ble det uttalt at dagens tiltak mot cyberkriminalitet og elektroniske angrep mest handlet om kompetansebygging for dedikerte IT-roller og var i liten grad rettet mot proaktiv prosessforbedring og innføring av systemstøtte. Videre i liten grad med innretning mot å identifisere mulig kriminalitet som allerede har kommet seg på innsiden av forsvarsverket.

Diskusjonen i ledelsen i virksomhetene bør nå være; Har vi gjennomført de viktigste og de riktige tiltakene mot cyberangrep? Hvilken pris versus kostnader er knyttet til å rydde opp i slike hendelser hvor inntrengeren allerede har kommet seg innenfor forsvarsverket?

Å besvare dette er en krevende prosess siden et angrep vil kunne skape store bevegelser både på inntekt- og kostnadssiden. Der investeringer i system og forbedrede prosesser kanskje er beskjedene kostnader sammenlignet med potensiell tap.

Det er publisert forholdsvis lite informasjon internasjonalt om reelle kostnader knytet til cyberangrep, men det halvstatlige Get Safe Online i Storbritannia anslår at britiske virksomheter tapte omlag 13 milliarder NOK på Cyberangrep i 2015. Det foreligger lite materiale for kostnader for risikobildet knyttet til cyberangrep i Norge. I «De norske resultatene, PWC’s Global Economic Crime Survey 2014» fremkommer det bl.a. at over halvparten av virksomhetene har fått økt erkjennelse av cyberrisiko og er mest bekymret for omdømme og tap av intellektuell kapital.

Avslutningsvis går jeg tilbake til Apple gründer Steve Wozniak og intervju med han på australsk TV der han sier: "We used to fear the atomic bomb when I was young, and you used to come home from school and sirens would go off for a test on every corner. Those were incredible days of fear from something. And now we fear all the cyberattacks and hacking».

Ønsker du å se hva SAS kan tilby innen Cybersikkerhet, se våre løsningssider.

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Recap of SAS Global Forum 2016 - from a partner perspective

Dan Jacobsson, Business Developer at Knowit Decision Stockholm

Dan Jacobsson, Business Developer at Knowit Decision Stockholm

By guest-author Dan Jacobsson, Business Developer at Knowit Decision Stockholm

Whatever role you have working with SAS products and solutions, SAS® Global Forum is the highlight of the year. This year´s event was my second one and I looked forward to experience it again, this time in Las Vegas, a city I have never been to before and potentially the strangest place I have ever been.

Apart from experiencing Las Vegas, I was looking forward to the introduction of new SAS products and releases combined with social interaction with people: customers, other partners and SAS representatives. We were all there to experience the atmosphere and learn from each other and from SAS.

In my role working at Knowit Decision, attending this conference is essential to me. During the days we were gathered, we had the opportunity to ask questions and discuss with SAS Product Managers, R&D and other experts. This year the focus was on SAS® Viya, SAS® Cloud Analytics, SAS® Analytics for IoT, Advanced Analytics and the latest release of SAS® Visual Analytics (which by the way looked really great).

In addition, the different demonstrations given at The Quad was of superior quality and gave me so much inspiration for future customer cases.

To listen, learn and socialize with the “cream” of SAS people worldwide was a useful experience. At SAS Global Forum, it is up to each one to make a tailor-made agenda out of the approximate 800 sessions during the conference. Personally, I was looking forward to the launch of the new platform SAS® Viya and the celebration of SAS turning 40 this year.

Referring to Las Vegas, I experienced Las Vegas Boulevard´s constant pulse at all hours, the many huge hotel complexes, the Bellagio´s fountain, the many casinos with their card tables and slot machines and the strangest people. Amongst these, the man who made a ball out of himself by getting down on his stomach, pull his legs behind his head and arms in the opposite direction, for later to start rolling down the sidewalk.

Our guide Nancy, who brought us to and from Hoover dam, had worked as guide in Las Vegas the last 47 years. She had experienced the mafia era when Las Vegas where in its start-up period, and she offers every now and again anecdotes from that era.

What happens in Vegas stays in Vegas is an old cliché that no longer goes. What happens in Vegas WILL NOT stay in Vegas it the new one. The world needs to know that we can count on SAS for the next 40 years.

And while at it, you also have the possibility to join SAS global events. First up is the Analytical Experience in Rome (November 2016) and secondly SAS Global Forum 2016 in Orlando, Florida (April 2017). Hope to see you then!

 

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What exactly can IoT do for hospitals?

As with all early-stage markets, customers interested in monetising IoT are hungry for examples of compelling use cases. Over the past six weeks, my colleagues and I have been exchanging views with IoT deployment leads across EMEA, and from the healthcare respondents, found the following real-life examples. These are hospital-centric examples, in addition to the patient centric examples discussed by Petri Roine in this blog post.

  

No1: Improved tracking of resources

  • Better management of hospital processes, such as laundry. Processes that are not directly connected to patient care are not exactly the sexy side of healthcare. Nevertheless, they are important—no hospital can continue to function without a laundry service, or one to sterilize equipment—and can also consume an astonishing amount of resources. Improving the handling of equipment by using IoT and automated systems can hugely improve the service to staff, and therefore to patients, and cost less.
  • Better use of hospital assets such as expensive equipment. Portable equipment gets moved about, from patient to patient, but it’s not always returned after use. An IoT-based system that can track expensive assets and locate them immediately can save huge amounts of staff time having to search for lost equipment. It can also improve patient care, because patients no longer have to wait for the equipment to be found.
  • Reducing time for maintenance of equipment such as diagnostics. IoT-based tracking systems for hospital equipment and machinery have another use: they can also save time required for maintenance. If a machine or piece of equipment can be located immediately, technicians have more time to spend on maintenance, and machinery is therefore likely to be absent for less time. This improves both productivity and patient care.
  • Ability to locate particular pieces of equipment instantly in the event of problems. It may not happen often, but sometimes one or two particular pieces of equipment need to be withdrawn from service immediately because of problems, such as a manufacturer’s recall. Being able to locate those precise pieces of equipment without having to check every last item in the hospital can save huge amounts of staff time.

No2: Improved identification, tracking and monitoring of patients

  • Reducing mistakes in theatre by improving checking processes. It’s not a great thought, but mistakes do happen in operating theatres. Sometimes the wrong patient, sometimes the wrong procedure, and with patients anaesthetized, they can’t alert anyone before the mistake happens. Smart wristbands and digital photo identification have been successfully used to automate patient recognition, and reduce this type of error.
  • Improved information for families and friends waiting for news. Sometimes it is easy to forget the importance of passing information to family and friends. However, an automated system using smart wristbands can provide immediate feedback on the patient’s location to relatives waiting anxiously for news in the emergency unit. Even if that news is as simple as that, the patient is now out of theatre and in recovery, or on their way to the intensive care ward, automatically relaying it can be very reassuring, and allow nurses to focus on patients, not passing on news to relatives.
  • Improved patient safety through medication tracking and matching. Mistakes in drug administration are one of the most common errors in healthcare. IoT-based systems can be used to identify, track and match medication from pharmacy to patient, and remove the potential for at least some errors.
  • Patients with dementia and other mental illnesses can be kept safer. Dementia and other mental illnesses provide a particular challenge for healthcare: how to keep safe people who do not necessarily co-operate with treatment. IoT-based systems offer potential for non-invasive tracking systems that can be used in real-time.

 No3: Improved administration processes

  • Data gathering and transfer can be automated and improved. Data gathering and transfer are not the primary function of most IoT-based applications so far, but they are a key side-benefit of many. Automatic transfer of information to back-office functions can improve logistics and supply-chain management in hospitals just as they can elsewhere. For example, medicines can be reordered automatically when they reach certain critically low levels.
  • Improved staff monitoring and compliance. IoT can be used to improve security, by ensuring that only authorised staff can enter certain areas, or that staff engage in particular behaviours required to improve patient safety, such as regular hand-washing. This does, of course, require staff to co-operate by wearing wristbands. One pilot found that staff frequently forgot to wear tags, so the potential for this may be more limited.

Do you have other examples of IoT use cases within the hospital environment? We’d love to hear from you. You can have a deeper understanding of how to accelerate the growth of your company by reading the white paper The Internet of Things: Opportunities and Applications across Industries

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Three lessons from health IoT testbeds

There has been plenty of discussion about how the Internet of Things (IoT) will change healthcare. Most of it, though, has either been in the realms of fantasy, or based on wearables and their potential to improve health, rather than healthcare. The conversation has not really been helpful in terms of managing today's big and challenging issues of healthcare, like how to manage chronic diseases, and prevent costs from rising exponentially.

This trend is changing now. We are seeing ‘testbeds’ emerge that are targeting a key benefit of IoT: self-service. In the UK for example, the projects will focus on diabetes and dementia, two of the ‘ticking time bombs’ of healthcare, meaning that they could be a very big deal indeed for healthcare around the world.

Recognizing the potential for self-care

The number of people with diabetes is rising. More than 1 in 20 people are estimated to have diabetes, many undiagnosed. Managing diabetes effectively requires lifestyle changes, as well as therapy, and poor management has potential for huge costs, because it can result in loss of sight or of limbs. This means that patient education and self-management are important elements of diabetes care.

Diabetes Digital Coach, run by the West of England Academic Health Science Network, in partnership with Diabetes UK will allow providers and patients to experiment with different diabetes self-management products already on the market. The idea is to find suitable products that will enable people with diabetes to self-care in their own way.

The project is wide-ranging. The products involved include wearables and supporting software, and monitoring devices and sensors, together with kit to connect them.  The idea is to help people with diabetes find the products that work for them, and enable them to self-care effectively, with more timely and effective contributions from healthcare professionals and other people in their lives, including family and friends. The benefits will be seen at patient level, as self-care improves, and in better planning and provision of healthcare to individual patients. However, the project will also provide important insights into diabetes at a population level, so that they can change behavior.

petri_iot

The challenges of self-care

Self-care for dementia patients, by the very nature of the condition, is a completely different ball game. The second test-bed project is Technology Integrated Health Management (TIHM), run by Surrey and Borders NHS Foundation Trust with several local universities and the Alzheimer’s Society, plus local commissioning groups. The group estimates that over 16,000 people in Surrey alone probably have dementia, although only around 6,000 of them have a diagnosis.

The project will provide technology to help people with dementia live at home for longer. It includes wearables, sensors, and monitors, which together will support patients to take control of their own health. At the same time, because of the nature of the condition, local health and social care staff will be provided with access to insights and, potentially, alerts about problems emerging from the data. The ‘double whammy’ of the project will therefore be improved self-care coupled with better provision of more responsive care from health services.

The project will help reduce the long-term care in nursing homes, that is now expensive, and not reflecting the real needs. It will also reduce demand on emergency services, by alerting staff to problems sooner, and preventing the need for unplanned hospital admissions.

Beyond the ‘holy grail’

Both these projects are designed with a dual purpose:

  • To save costs.
  • To improve quality of life.

Data from the patients’ sensors are analyzed and presented to give views that makes immediate sense, regardless of whether you are the patient, family member or member of the clinical team.

It is early days to be getting excited. The test beds have just been announced, and have a lot of work yet to do. But one early finding is that in addition to self-care, doctors have been able to intervene even when the patient has been shy about ‘bothering the doctor’ with what may have seemed like a small anomaly. Clinicians will recognize the huge impact of this apparently simple consequence of transparency. Analysis and trends need the additional context that only an experienced practitioner can bring to bear.

Are you involved in an IoT-enabled health digitization program? I’d be interested in more concrete examples as these test-beds as we use technology to improve outcomes for patients.

If you want to explore the many business opportunities IoT presents, read this report from the International Institute for Analytics, The Internet of Things: Opportunities and Applications across Industries.

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From “Jurassic Park” to “Hyperloop” in a single step?

I read somewhere that you should not be afraid to take a leap when necessary – because you cannot cross a gulch in two small steps. A former British Prime minister named David Lloyd George said this and I believe the same about how organizations often think of change.

What drives change for most people or organizations? Very simple, somebody needs to have a strategy and plan for the change process and to speak up about it. This person must have a vision and a plan for implementation and push the change forward. Organizations do not change without a need for it or if somebody suggests a business proposition that will demand change. Who is this person in your organization or do you want to be this person?

Presenting SAS® Viya – next generation of analytics

Presenting SAS® Viya – next generation of analytics

Did you attend this year’s SAS Global Forum in Las Vegas? Did you see the new SAS® Viya software? Did these new software possibilities inspire you? Thinking: “If I only had better tools and newer versions of my favorite software – then I really would be a beacon at work!” Did you wonder why your organization rarely upgrades your everyday SAS® Intelligence Platform and does your daily work and tools suddenly feel out of date?

Before I joined SAS Institute, I worked in a Nordic Insurance company. This was in the old days before we used regular client-server systems. We handled the ordinary SAS jobs running on the company’s BIG mainframe (MVS) – a machine so big in its nature - it was like a mid-size house inside the data center (at least it felt like that).

One thing we knew, all too well, was that the cost of running daily SAS jobs was high. The cost perspective was a constant buzz in the organization. - “It costs too much to run our SAS data warehouse environment for the actuaries”. I think they forgot one major thing. The work the actuaries did to generate the right models for pricing and scoring customers, meaning that the company made money, but at a high cost. Anyhow, the green 3270 terminal and MVS SAS was outdated a long time ago.

What did we do to help our company to modernize the old “Jurassic Park” of a SAS platform? We started to modernize two things:

  • Where the SAS software run: we moved the SAS jobs from the monolithic MVS to a smoother and much cheaper AIX decentralized server. Saving a lot of CPU Cycles and money not running it on the MVS
  • Convincing the people in the organization to work differently. Is it enough to prove that we save money? Is it enough to prove that new tools and a platform modernization will give them new opportunities to develop better models and work smarter?

This task seemed challenging at first and the resistance was huge from some of the SAS users. However, after training them and showing them the new flexible platform they gradually saw the potential in the modernization. By giving the SAS users in the organization better tools and new opportunities, they managed to look at the content of the business data and the SAS System in a clearer way.

Simultaneously, we worked with the business side to transform the organization to a new Governance model and. they were introduced to the modern world of SAS. After a while, they gained what we call “The Power to Know” and the inside out of their business data and SAS processes. This was a great driver to the business; to work continuously improving the system and the data quality, structure and to operate data better and cross these with other sources of data. This resulted in a more robust and agile organization along with a new governance model. Now, the business could measure how much the change of platform actually did to a positive ROI.

Explore the “Hyperloop” of the next generation of Analytics

Figures of business value from a modernization should not be very hard to find, I believe. SAS Institute has released the new SAS® Viya Platform. SAS Viya and our current SAS® 9.4 Platform will work together – hand in hand. SAS Viya is an all-new platform making SAS more open and cloud ready. We have created a new, modern, open environment for analytics. SAS Viya answers customers need for multi-cloud deployment, it is open for innovative disruption and an extremely fast, in-memory massively parallel analytics environment. Both SAS Viya and SAS 9.4 can coexist and work together – however if you like to move to the SAS Viya platform you need to modernize – moving from current outdated software versions to the SAS 9.4 Platform. Only then, you will be able to reuse all that know how you have invested throughout the years with SAS in your organization.

If your organization still are using an older version of SAS – then you should ask us, at least the following two questions:

  • When can SAS help you do the modernization?
  • How can SAS transform the way your organization works to become more effective, faster and smarter?

The answer we will give you is to upgrade to the latest version of SAS and do the modernization project together with SAS experts. We will work with you to find flexible solutions and make you a happier SAS customer. Exploring into the “Hyperloop” of the next generation of Analytics with SAS Viya certainly will make you the Beacon at the office – if this is your driver – make that call.

Read more about SAS® Viya

Be inspired on your way to modernization by reading this white paper on SAS® High-Performance Analytics Products, or have a look at this webcast where we try to demystify In-Memory Analytics.

Good luck!

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Fem vanliga missuppfattningar om Big Data

Big Data är ofta ett missledande ord för att beskriva det skifte som pågår inom teknologi, affär och kultur. För tillfället har big data blivit ett vedertaget ord för allt inom dataanalys och om du inte förstår begreppet så är du inte ensam.

Här är några vanliga missuppfattningar om vad Big Data är för något:

1. Du tror att du kan ignorera Big Data?

Dåligt förslag. Möjligheten att omvandla data till affärsnytta kommer fortsatt att vara oerhört viktigt för alla industrier de närmaste åren. I affärer är information makt. Big data ger oss tillgång till information som vi för bara några år sedan endast kunde drömma om att analysera på. I stort sett alla yrkeskategorier kommer att påverkas inom en väldigt snar framtid - från lågutbildade och tillfälliga anställningar till högutbildade professionals. Att ignorera big data är att sticka huvudet i sanden; trenden är här för att stanna.

2. Du tror att Big Data handlar om data?

Intressant nog så handlar det inte om data i sig utan snarare vad du gör med den. Att enbart samla in och analysera på data skapar inget värde. Det är först när du omvandlar data till affärskritisk information för att utveckla och styra din verksamhet och dina strategiska beslut som det blir intressant. Utan värdefull tillämpning som förändrar/förbättrar dina processer, skapar nya affärsmodeller eller erbjudanden så är big data bara ett kostsamt och tidskrävande projekt.

3. Du tror att Big Data handlar om mycket data?

Big data fick sitt namn därför att teknologin plötsligt gjorde det möjligt för oss att samla in och analysera betydligt större datamängder än tidigare. Till detta kan vi även analysera på helt nya typer av data – så kallad ostrukturerad data. Tidigare var det endast möjligt att bearbeta data i strukturerad form som finns i rader, kolumner och databaser. Idag kan vi analysera texter, media, journaler, e-mail, video, chatt, bilder, ljud, nätverk, sensorer, mobiler, sociala medier etc. Big data handlar inte om mängden data utan snarare om den mångfald av data som vi nu kan kombinera och analysera för att skapa mer precisa affärsvärden.

4. Du tror att ju mer data vi har tillgång till desto bättre?

Många företag har börjat hamstra och samla in så mycket data de kommer åt bara utifall de i en framtid eventuellt kommer få ut ett värde av det. Men detta är en dyrbar strategi. Datalagring är inte gratis och när mängden data växer lavinartat så växer även kostnaderna. Dessutom så kommer sökning och analys bli alltmer utmanande, komplext och resurskrävande. Istället för att hamstra data så är det bättre att endast spara det som du verkligen behöver ur ett affärsperspektiv. Här är det viktigt att först formulera de frågor som din verksamhet behöver svar på innan du kör igång ett big data projekt så att fokus hamnar på kvalitet snarare än kvantitet.

5. Du tror att Big Data handlar om att samla in och lagra din egen data?

Faktiskt inte. När företag och organisationer börjar se sin data som den affärstillgång den är så skapas en marknad där organisationer kan köpa, sälja och byta data med varandra. I tillägg till detta finns en stor mängd öppen data från myndigheter, forskning- och vetenskap eller non-profit organisationer. Många företag kommer upptäcka att mycket av den data som behövs redan finns därute - vilket avsevärt minskar mödan och tiden av att realisera värde i verksamheten.

Förhoppningsvis har du fått en klarare bild över big data som begrepp och hur det kan hjälpa dig navigera rätt i den digitala förändring som vi står inför.

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