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Fans soak up the sun on Murray Mount during day twelve of the Wimbledon Championships at the All England Lawn Tennis and Croquet Club, Wimbledon.

Behind the scenes of IBM's Wimbledon data bunker

IBM's near real-time Wimbledon data is powered by county tennis players from across the UK, patiently recording the dynamics of every serve, slice and volley

Beyond the grass courts, tennis whites and jugs of Pimms, there’s a whole flurry of activity going on in a dimly lit underground bunker. The series of whirring machines in IBM's data bunker are fed through to every commentary, post-match analysis and TV graphic on screens across the country. Welcome to the IBM bunker in the heart of the championships.

In the bowels of broadcasting centre sits the data operations alongside the web and content room for IBM, its 25th year as the official technology supplier of Wimbledon and the All England Lawn Tennis Club.

Technology is great, but there's still a huge reliance on humans

IBM shows off updated technology every year ahead of the championships, driven by a team of data entry experts, photographers, graphic operators and a systems and operation team.

Two members of the IBM team keep an eye on the data coming in from live entry courtside

IBM deploys 48 data entry people – 46 are dotted around the venue and sit court side capturing data such as the speed of the serve, the direction of the serve, the number of shots in a rally (forehand and backhand by player) and how a rally is won or lost.

“We employ county national tennis players, because it’s easier to train them on how to enter the data into the system than it is a technical person,” explains Chris Nott, chief technology officer for big data and analytics at IBM UK and Ireland.

Both centre court and court 1 have three data entry people sitting courtside; one calling the game, one who tracks the speed and direction of serves and another who inputs the data into the Wimbledon information system. Nott describes how it is the task of the remaining two data entry people within the bunker to shadow the action on court through the TV coverage and to communicate with the relevant team via radio comms, flagging up any discrepancies.

"Dimitrov, he's one to watch," says one of the data entry team as he watches the Bulgarian compete against Britain's Andy Murray in the mens quarter-final of the Wimbledon championships

“It makes it more accurate having two people’s opinions,” says one of the team, turning his head briefly to explain how his communication with the team courtside needs to be fast and the decision instantaneous.

For Henry Moore, 21 from Hampshire it is the first time he has worked in the data entry team for the IBM bunker. A collegiate tennis player in the US, he’s enjoying the opportunity to watch a grand slam from a new perspective. He expresses how focused he has to be in this role: no more drifting in and out of a game when you're scrutinising every single action.

Who has he enjoyed seeing play? He glances back at the screen. “Dimitrov,” he says. “He’s one to watch.” Indeed he is; shortly after we speak he beats Murray, forcing the defending champion out of the tournament.

From mountains of data to bite-sized chunks

Very detailed data is available from the Wimbledon information system for commentators, players and the media. With data on past matches throughout the year also on the system, commentators can make comparisons on the way a player is performing against past match stats, explains Nott.

Members of the IBM digital team working on game statistics in the digital operations room during day Four of the Wimbledon championships. Photograph: Philip Toscano/PA

A search for Sharapova brings up all her grand slam history, annual ranking, career earnings and tournaments played in this year with corresponding results. Another click and the system pulls up Spencer Gore - the first ever winner of Wimbledo who walked away triumphant with winnings of 12 guineas.

A recording of the match, blended with statistics – meaning players analysing their play can instantaneously match up a stat with the moment in the video – is handed on a USB stick to the players 30 minutes after the match has finished.

From the bunker to your screen

“In the same way we’ve used tennis players to capture [the data], we also put someone alongside the BBC producers… they will then advise them on the appropriate graphic to use at a particular time in the match that is relevant and timely,” says Nott..

One tap of the 'graphic on' button and a range of lines spread across the screen showing the direction of Nadal’s shots from the points at which he hit the ball to where the ball landed.

New for 2014 is analysis of aggressive play on centre court, Nott explains, based on an algorithm using four input points: the speed that the ball is hit, the closeness to the line at which it lands next to, the amount of movement of the player goes through to get to hit the ball and from where they hit the ball.

#thehill vs #theworld

Twitter are asked who will win? Dimitrov or Murray? The IBM social media command centre track the hash tagged responses

Another room is dedicated to social media, and features a large display of live Twitter data, and what people are tweeting about today at Wimbledon. With the arrival of the Duke and Duchess of Cambridge in the Dimitrov vs Murray match, Royal Box is one of the top trending topic displayed.

Which players are the most engaged, where in the world people are tweeting and what pictures people are uploading with the Wimbledon hashtags are also tracked.

The official Wimbledon Twitter account @Wimbledon regularly throws out questions to the Twittersphere. At the moment the question that is raging is "who will win this match? #Murray or #Dimitrov?' Not only are answers divided by location, #thehill vs #theworld but so it seems is sentiment. Viewers away from the grassy slope don't fancy Murray's chances as much with 59% tweeting that Murray will win, while 91% of those tweeting with #thehill think Murray can win.

Andy Burns, digital producer at the IBM digital agency showing an image of the hill at Wimbledon.

Andy Burns, digital producer at the IBM digital agency, zooms into an image of the enthusiastic crowd on Henman Hill using the via Slam tracker tool - the centrepiece of IBM's offerings to the public - a sense of the real atmosphere on the hill is spread. For global fans of the event who are not just interested in the tennis but for all else that comes with it, the 360 degree images provide an intimate look at world famous event that they may be hundreds of miles from.

"We want to create the beauty of being in Wimbledon” explains Nott. There were almost 20 million unique users on mobile channels and wimbledon.com in 2013 and it is expected to grow this year. Ultimately, Nott sums up, the aim is to bring the Wimbledon experience in the otherwise rather quiet area of SW19 to an audience spanning the globe.

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  • Wimbledon 2014

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How IBM Watson is Powering Big Data & Analytics

How IBM Watson is Powering Big Data & Analytics

Darryl Worsham | January 18, 2018

We’ve covered   big data and analytics  in some of our previous posts, and in this post, we focus solely on   IBM Watson big data. Where it started, its evolution and growth, and how IBM Watson is powering big data and analytics today. We also explore some industry use cases. You’ll have a greater understanding and appreciation for IBM Watson and big data.

Download our summary sheet to learn more about the future of IBM Watson.

Cognitive Computing & IBM Watson

Before IBM Watson, an IBM Research team worked on a project called Deep Blue. Deep Blue was programmed to sift and sort through up to 200 million possible chess positions per second. In 1997, Deep Blue made international headlines by using high-powered computing to win a chess match. Later, the architecture behind Deep Blue gave developers insight into ways they could use this type of processing for predictive modeling in the world of finance, healthcare, and business practices.

Deep Blue placed IBM at the forefront of the cognitive computing technology era, leading to IBM Watson.

Watson, The First Iteration

In early 2011, IBM caught international attention again as IBM Watson beat two of the all-time most successful human players on Jeopardy! without an internet connection. It only knew what it had amassed through years of persistent interaction and learning from a large set of unstructured knowledge. Using machine learning, statistical analysis, and natural language processing to find and understand the clues in the questions, IBM Watson then compared possible answers, by ranking its confidence in their accuracy, and responded – all in about three seconds.

Source:   IBM

Applications of IBM Big Data Analytics

Advancements in the Watson ecosystem have evolved at a rapid pace since this first iteration. What follows are some examples and case studies of how IBM Watson is powering big data and predictive analytics with long-term value.

The healthcare sector generates petabytes of data, information from Electronic Patient Healthcare Records (EPHR), research, trials and medical journals is often unstructured and due to the sheer volume of it, can’t be processed manually by humans.

Because of this, potentially valuable insights are being lost which could have lifesaving implications such as helping to diagnose medical conditions or identify patients that will respond better to some treatments more than others.

Cancer patients

According to IBM, Watson is adding value to Oncology and is being used to suggest tailored treatment plans for patients based on their unique medical records.  Not everyone benefits or responds to treatment in the same way, but with Watson, healthcare professionals can crunch large volumes of data to identify treatments that have the highest probability of success.

387 million people in the world live with diabetes, and according to Hooman Hakami, Executive Vice President and Group President of Medtronic Diabetes:

“The number of people isn’t slowing down, the cost isn’t slowing down. We need to do something different.”

To address this, IBM, in conjunction with   Medtronic , worked together to produce a Cognitive Application that can help with the prevention, identification, and management of diabetes.

The Medtronic and Watson application dubbed Watson Health was designed to help patients manage their condition daily. One of the ways in which it’s able to do this is be performing a retrospective analysis of a patient’s insulin levels, continuous glucose monitors, and nutritional data.

The application can help patients understand how their everyday behavior is affecting fluctuations in glucose levels in real-time. The hope is that patients will be able to pinpoint lifestyle choices and their effects and adjust or make healthier decisions.

In 2012, Citi partnered with IBM to explore the use of Watson technology with consumer banking solutions. After developing cognitive technologies for customer insight, IBM went on to develop technology to help finance firms manage regulatory and compliance controls. Today,   IBM Watson Financial Services  powers services in the wealth management industry, insurance, and financial risk management solutions.

Source   ZDNet

With a history of data analysis and predictive modeling, it’s no surprise that the marketing industry is a growing marketplace for IBM Watson. In 2016,   SugarCRM partnered with IBM to help businesses across the automotive, insurance, hospitality, retail, industrial, government, and banking industry solve CRM problems.  In 2017, Salesforce announced a global strategic partnership to power Salesforce Einstein.

Wimbledon Case Study

Back in 2016, powered by IBM Watson big data, the Wimbledon editorial could monitor social channels and break new stories and mold the narrative to encourage new fans from other sports such as the F1 to visit its tennis-related platforms.

The results were impressive, a 24% increase in social media audience, an increase of 25% in terms of video views from 2015’s event (110 million video views).

View Habits and Attention

Internet user habits have changed dramatically in recent years, attention spans are shorter, and from a marketing perspective, it is often said that we live in an “attention economy.”

Watson allowed the Wimbledon team to capture the audience’s attention by allowing the team to continuously publish the right content in the right places at the right times.

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Twitter Data

Twitter, the global social media platform is the platform of choice if you want to find out what’s happening now .

For the Wimbledon Team to create compelling content for social media audiences, it paid to keep an eye on the hot topics of the day.  A task like this is impossible to achieve manually, but by leveraging Watson’s Natural Language Classifier, the team could “surface” key topics and phrases of the day.

Instead of using simple keyword filtering such as searching for a hashtag such as “#wimbledon,” Watson was trained using historical datasets to highlight messages that were relevant to the tournament.

To further enrich this data and gain additional insights, Watson’s  Alchemy Language  service was used to identify metadata from the text of relevant social media posts. Using this service allowed the team to identify things such as the players and matches being mentioned or the sentiment of the post (the underlying emotion of the message).

Throughout the tournament, over 17 million pieces of social media content were processed and aggregated.  This information was displayed in real-time dashboards in the Cognitive-Social Command Centre interface.

[bctt tweet=”By identifying signals in the “noise,” the editorial team could then make better-informed decisions about how best to connect with the audience. #Wimbledon #CaseStudy #IBMWatson ” username=”GAPapps”]

You might think that 17 million posts sound like far too much content to process, but Watson was able to “surface” the most important topics and messages that were relevant to the Editorial Team. This gave the team insights as to which topics and stories had viewers and fans excited.

We’ve explored AI, machine learning and its effects on employment in detail on another blog post . While a platform like IBM Watson allows healthcare professionals to quickly analyze vast quantities of medical data whether it be in text, video or web format at incredible speeds, we don’t see clinicians and other healthcare professionals being replaced anytime soon. The same can be said for many other industries.

Platforms like IBM Watson will extend existing human capabilities by allowing professionals to derive actionable insights from data that was invisible prior to using AI and machine learning technology.

Here at Growth Acceleration Partners, we have extensive expertise in many verticals.  Our Centers of Engineering Excellence (COEs) in Latin America focus on combining business acumen with top-notch expertise to help your business.

We can provide analytics services for your organization with resources in the following areas:

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If you’d like to find out more, then visit our website  here .  Or if you’d prefer, why not arrange a call with us or send us an email ?



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Case study 2.1: Wimbledon and IBM

Introduction, the business challenge, the transformational approach, winning hearts and minds, the results, case study questions.

The Championships, Wimbledon, held at the AELTC (All England Lawn Tennis Club), is, for two weeks in June, the centrepiece of tennis globally and of sporting tradition in England. Wimbledon and IBM have collaborated successfully to provide innovative digital content and were DADI award winners in 2017 with their ttWhatMakesGreat campaign.

The year 2016 was one of amazing sporting experiences, events, and enterprise with the Olympic and Paralympic Games in Rio, the UEFA European Championships in France, and Leicester City winning the English Premier League. Wimbledon risked losing viewers but saw an opportunity to broaden the Wimbledon experience to a new fan audience whilst enhancing the offer to their existing fan base.

IBM began working very closely with the editorial and social media team at Wimbledon to develop new sporting digital cognitive technologies. Together, IBM and Wimbledon actively monitored social media channels and new platforms with key objectives to broadcast new stories and shape the conversation to entice fans from other sports to visit its innovative new digital platforms.

From a scheduling perspective, 2016 was a challenging year for the organisers of the Championships, Wimbledon. During Wimbledon fortnight, sports fans would be spoilt for choice: in addition to the tennis, they could watch three international cricket matches, two Formula 1 Grand Prix races, nine stages of the Tour de France, and nine matches in the Euro 2016 football championships.

Alexandra Willis, Head of Communications, Content & Digital at AELTC, explained the philosophy behind the use of the technology. "The cognitive approach reveals what people say, think and feel about The Championships, helping us make quicker, more informed decisions about content."

Sam Seddon, IBM Client Executive for Wimbledon, stated that "Cognitive and Cloud technologies go together like strawberries and cream. We can easily combine IBM Watson services with real-time data feed and spin up new applications quickly, letting us innovate faster than ever before." Year-on-year capacity improvements are able to handle the continuing thirst of digital activity (see Table 2.1).

The combination of cognitive and cloud-based technologies helped Wimbledon's editorial team keep the 2016 tournament at the top of the agenda for fans worldwide. Not only did the team attract the traditional tennis demographic, but they also resonated with a younger audience and brought fans of other sports into tennis.

Table 2.1 The Championships digital activity.

  • 69.4 million visits and 395 million page views from 20.9 million unique devices
  • 24% increase in social media audience
  • 110 million video views, an increase of 25% from 2015

Alexandra Willis commented,

the focus on using cognitive social media analytics to engage with potential fans outside of the tennis community was a good way to convert the overcrowded sporting calendar from a risk into an opportunity. For example, when we saw that Liverpool Football Club had sent good luck messages to Caroline Wozniacki (who is a big Liverpool fan) we followed up with some football-related tweets to encourage that audience to visit our site.

The future is clearly digital, as Alexandra Willis further stated:

Crucially our focus on social media was a big success. Our total audience grew by 24% compared to 2015, and we analysed over 17 million pieces of social media commentary across Twitter, Facebook, YouTube and Instagram. We benefited from increasing our focus on video content with 110 million video views, a 25% increase on last year.

The BBC announced an extended deal with the AELTC to broadcast the tournament until at least 2024. The partnership is the longest in sports broadcasting history. Tony Hall, director general of the BBC, said,

By extending the rights to broadcast Wimbledon until 2024 we can continue our longstanding and valued partnership with the All England Club. Wimbledon is the pinnacle of the sport, and as such has a special place in the hearts of the nation.

Philip Brook, chairman of the AELTC stated, "We greatly value the BBC's commitment to delivering large national audiences for the championships across a multitude of high quality platforms." Evidence, if evidence be needed of traditional and new media technologies working in close harmony as sports consumption behaviours mutate.

  • 1 A culturally traditional sporting competition (The Championships, Wimbledon) presented a challenge for innovation in sport marketing. Do you agree with this statement? Give supporting reasons for your judgement and consider how well IBM dealt with this challenge?
  • 2 What does social media and technology through digital development bring to the sports industry sector? Is there another sporting event that would benefit from such an initiative as the one described in the case study?
  • 3 Using the Wimbledon case study as a benchmark for digital sport marketing, are there downsides to the use of technology in sports? Is there such a thing as social media ‘clutter’?
  • 4 Where next for sport marketing in the digital age? Consider examples that have emerged from your reading of this case study?

Source: https://www.spssanalyticspartner.com/case-study-wimbledon-2014/

The key aspect to the following conversation is the symbiotic considerations of digital social media. To understand digital is very important to further understanding of the impacts on the whole spectrum of sport business, and specifically sport marketing. Digital in the context of this conversation highlights the full cornucopia of channels available in communications in the sport marketing setting.

Conversation 2.1 Eric Stoller, Consultant

Eric Stoller is a higher education speaker, consultant and writer. He frequently gives keynotes and workshops on how digital technologies can be used for strategic communications, learning, and engagement and uses his own social media presence to share resources and curate content.

Alan Seymour: Well, good afternoon to you. This is Alan Seymour, All In Sports Talk, your host for episode 16, The Future of Sport. My first guest, delighted to welcome . . . Eric Stoller, an independent educational consultant who understands new mechanisms, new media, new means of communication, particularly in social media, and not really in sport, so a little off-piste today. Eric, tell us a little bit about your background.

Eric Stoller: Well, thanks for having me on the show. I love the off-piste reference, having grown up in the US in probably the flattest part of the country in Iowa where it’s all cornfields. We don't have anything like that. I live nowadays in the UK, and when you said I’m an education consultant, means a lot of different things. Most of the time I spend my days teaching digital engagement to organisations usually within education, universities, colleges, and some of the vendors that work within that space.

A lot of social media work, a lot of writing, content creation. I also write for www.insidehighered.com. I've been a blogger for them now for several years, and it’s my primary platform for content creation. Of course, you and I know each other through Twitter. I'm all over the digital engagement space.

Alan Seymour: Eric, I'd like to start to get some insight and maybe to develop a dialogue and a conversational piece here. I’ve just returned, in the last few days, from a sport entertainment digital conference. Lots of people there were trying to give definitions of what is digital and what isn't digital. For some people, digital may have meant, "Well, it's social media." For some people digital it's all about the technology. In reality, it's a bit like I get in a car. I don't want to know what the car is or what makes it work. I just get in the car because I need to get to a gig or an interview. It's the applications and the processes.

Tell us a little bit about your perspectives, I suppose, maybe some of your philosophies, some of your understandings. It may mean going

you’ve used or themes that you've used, energy, intensity, the ability to go global.

Perhaps using some of those frameworks, if you like, would you pinpoint some great examples of how universities, without necessarily naming them per se, or contacts that you've made, or case studies, exemplars of good practice of doing these things? Because I might preface, this is the word I'm searching for here, by saying I go across the globe, and I have no shame in saying this. It's kind of maybe a competitive thing I'm saying. I referred to sport as entertainment a few moments ago. If I didn’t, that's effectively what I meant.

Maybe in some cultures, particularly the USA, they can see that and they can build on it, so they kind of get it. I've just come out of formal academia, but I'm still in it. I'll always be in it. I sometimes think is it tokenism that they just say, "Well, we've got a social media account. We're going to do social media." But they don't actually get it or they don't actually do it. Well, I don't wonder, because one of the reasons I want to talk to you in this way today and with your expertise and reputation, and it is good, and it's really captivating lots of audiences out there, perhaps you can give us some more insight into that.

Eric Stoller:

I think a lot of organisations, and you hit on it, they'll say, "We have to be in the social media space." They might not necessarily define what that means. They'll put up a bunch of accounts, and they’ll start playing around with different channels. They won't necessarily have any goals or objectives in mind with what they're doing with it. I'm a big fan of experimenting with new social media channels, trying different digital this or that. At the same time, you want to connect it to what you're trying to accomplish. Do you have goals?

You talked about universities. I just saw a report the other day that was talking about institutions that have an Instagram presence that is driven towards recruitment efforts are doing really well with international student recruitment, and that they’re linking it back to their Instagram accounts. For me, that's connected to strategy. That's connected to what you're trying to accomplish. It’s not just we're taking pictures of our beautiful campus just because. We're trying to do something with it.

A university library that is using Twitter for customer service, and to just share the vibe of the library. Students are taking exams and they're looking for quiet spaces, and the library is engaging with them. There's a lot of data on student engagement, and the more engaged students are, the more successful they will be at university. Digital engagement is an extension of that engagement that used to happen just in the hallway conversations, the face-to-face interactions.

The other thing too with social, and I'd be remiss if I didn't mention this, is that it's not the end all, be all. You have the on-campus conversations still, the face-to-face conversations. You have the one-to-one Twitter engagement that happens, or you have the Instagram photo that's seen and liked and commented on. It’s all interconnected. It's just part of this bigger sphere of how we all keep connected with one another in an increasingly global, increasingly mobile world.

Alan Seymour: I think that point, I wish you and others, and if I had to spread one kind of message consistently, in many ways part or all of what you've just said would be it. The number of people, if you look at communication and good communication, and interference and noise that stops that good communication, well, maybe some or all of those things are present in what all different social media channels are doing. I use Twitter, and I use other platforms. You made the reference, that's how we met. It's how I met lots of people who I'm now engaged with in conferences and writing articles and ultimately publishing stuff in the world of sports business.

I've often said to people, "Don't just believe the fact that you've pressed a button means that you've communicated." It's the classic student argument or default excuse, "I have contacted you. Did you not see my email?" And/or well, I'm now connected to the great and the good, because I've got an extra follower, and here's the follower. It's only the beginning. It's what you do. The best sale is the best opportunity to get another sale. You start the roll out and the momentum of that.

I think sometimes as well, give me a view on this, a typical open day might mean that the social media puts some presence out there and starts to use it, but does it seem cold? Is it sanitised? Is it just from ... a social media manager for the university, or an executive? Because one of the things that I'm absolutely passionate about is students do it well, or students are involved in this. They’re the best people to not only talk to and have, but actually get them to do it.

In your experience, give us some examples maybe, Eric, of how that actually is being applied across the educational space?

Eric Stoller: You see an increase in ambassador programs at universities, where they’re bringing in students. A lot of times ideally they're paying them to run some of their social media accounts.

Alan Seymour: We're now talking about ambassadors and student ambassadors within universities, Eric. Tell us a little bit about experiences you have,... how students should be taking on board this on behalf of the universities?

Eric Stoller: Sure. You can tell a lot about a university by the way they handle their social media presence. Is it a comfortable place? Are they open?

Are they warm? Is there a personality behind what they're posting on social media? Student ambassador programs are a really great way for institutions to create peer-to-peer interaction, because students connecting with other students, there's a real authenticity there. There’s a real lived experience there. Students can say this is what it’s actually like as a student who’s in a particular course, or living in a particular accommodation.

That’s a lot more real than maybe a more conventional marketing or PR-based communication that you get from someone who’s working at the institution. Now, that being said, there are a lot of really good social media professionals out there who are working at institutions who do a great job of embracing these new technologies, these new channels.

You were talking about open days a little while ago, and I think the really neat thing about open days for universities is they're exploring new channels to connect with students, students who are actually there at open days as well as prospective students who might just be tuning in. They're using Snapchat and they’re using a variety of ways to connect with these students, Live Instagram or Instagram Stories. I know there's been a lot of use of WhatsApp and some vloggers.

It really gives an institution the chance to show who they are in a unique way. Because after a while, everybody starts to sound the same with their website and their mission and vision. This gives the institution the chance to really shine and showcase the real humanity of the place.

Alan Seymour: I mean Eric, that is such a beautiful, and it is kind of nicely emotionally and almost is personalising and perhaps taking away some sanitisation, or almost some robotic approaches. I think you’ve made some really great points. They transfer and translate very much across lots of different sectors. We've talked about some of those sectors. I don’t want to necessarily go down the sport route per se here. Just picking you up on...

Eric Stoller: Can't we go to sport?

Alan Seymour: Go on.

Eric Stoller: I would love to talk about sports in terms of student athletes, if that's okay.

Alan Seymour: Perfect. Tell us a little bit about maybe then, because I did a recent interview where an ambassador, but a professional consultant was advising athletes how to use social media. Take that as a scenario. How would you advise professional athletes to use social media, Eric? If it's not too much of a fast ball.

Eric Stoller: Exactly. That's a great angle. I think that, well, first and foremost, I would talk about it in the context of how I talk about digital literacy and digital capability for all people, and walk it back. When someone becomes a professional athlete, the time to work on their digital presence and develop it and mature it has almost passed in a way. Because who they are and how they post and what they post, good or bad, is already formulated.

However, when you look at, say, student life and student athletes and what they're posting and sharing, there's this perception that young people by default have this innate digital native ability to use all things related to technology, social media, what have you. Of course, we know that that's not the case. Everybody has this spectrum of fluency that they bring to the table, and so young people coming in from, say, school to university, or whatnot, they've been using social media and their digital presence for just peer-to-peer interactions, social life, and maybe building up a bit of a reputation if they have been a sports star, and people have started to tune into them early on.

There's a sense of, what does it mean to engage in these digital spaces in a way that benefits you as someone who’s posting, engages with your audience, and yet doesn't cause you issues with your image or get you into trouble, or cause harm to other people? I think especially when you're a professional athlete, you're under the microscope. You've got media always wanting to pay attention to what you're doing. You've got fans from all over the place. Everything you post, even if it's online for just a few seconds, is subject to a greater level of scrutiny than other people.

I think that my number one piece of advice for professional athletes posting on social media is: always think before you post. It sounds so cliché, but that's the advice that holds true for everyone.

Alan Seymour: Eric, it's just amazing, because I did a guest lecture a few weeks ago at the University of Worcester, and I produced this slide which was effectively, it was comparing it with the hierarchy of needs and how we grow through from the solid base and reach a safety point. I said if you relate that to social media, advice particularly strong in safety is just what you've said. Traffic light system for me. Red, stop. Amber, pause, think. Is it going to be okay? If you’re happy with it, then press the button. It's a mantra almost that I’ve used as a piece of advice.

Let’s build on this, because I think it's a fascinating subject here. Something that you said, again, traditional versus non-traditional, or you've even I think in some part of the interview today almost inferred or used the word, well, you've certainly used the word experiment. If I took that further and maybe do something a little bit more disruptive, or risky even, would you recommend this?

Alan Seymour:

At this conference that I've referred to earlier, another great example, because they won the best award at, I think, it was for football business or something related. It's a well-known football club just gained promotion.... Part of the award and maybe the biggest reason, great advocates, great ambassadors in the use of social media.

They reverted back to, it's still digital, it's still a newer form of communication, but it's not the newest, email. They actually sent out over a million personalised emails to a relevant database telling them about all the highlights, giving them all the information. It was just so well-received. It showed this marketing mix, as you call it, absolutely right, but also the fact that you need to find these blends or the blending aspect of doing communication. Obviously, we’re talking in the context here today specifically about social media.

Let me just take it on a little bit more here, Eric, if I may. If you were giving another piece of advice to career aspirants here - I mean you are now an independent consultant. What does an independent consultant do? Because clearly we're having this interview here and we've connected through social media, and obviously you've built up a reputation talking about higher education and the use of social media. Do you get directly involved with brands, organisations, or are there some pieces of advice or thoughts, insights that you could give to my audience on that?

Sure. I've been doing this now for almost seven years full-time since I actually left a rather enjoyable, fulfilling full-time job to try this experiment, as I called it back then, in consulting. It's taken me from the US and from working in the US, to Canada, to Mexico, to now being based in the UK and working in Europe. I spoke at a conference late last year in New Zealand. You get the chance to explore the world as an education consultant.

One of the things that I think almost always comes up with my consultations with my clients - and a lot of times those are going to be universities - is I will be brought in to talk about social media or digital engagement, and that could mean a variety of things. It could be the top-level marketing and comms for the institution. It could be what the careers office is doing. It could mean what their student services is doing. Could be from a learning and teaching perspective.

Every single time I'm brought in with social media and digital as the key focus, a large part of the conversation turns into a conversation on organisational culture and a willingness to learn new things, every single time. Because the social media channels have been around there for a long time. Like you said, Twitter's been around for quite a while. Facebook's been around now since 2004. YouTube has been around forever, practically. New apps are coming down the pipeline, but the thing is it's not that the apps aren’t there, it's what it is that’s getting people to use them, to try them out. What are the motivations involved, the incentives involved?

As an organisation, are you rewarded for trying new things? Are you keeping up with your current audience? A lot of times when I'm speaking at events, I will literally ask the audience and I will say, "How many of you are afraid of using Snapchat?" Every time people will raise their hand, and I'll say, "You're not afraid of the telephone. You're not afraid of email. You've got to think of these apps as communication and engagement platforms."

The organisational culture and almost the ethos of lifelong learning, that's consistently something that comes up in each and every one of my consultations.

Alan Seymour: I mean, Eric, again, the echoes, the resonance here, it's just amazing. It is. I go to conferences like you do, and I always say, and I did a panel leading, moderating, talking about this. I was saying, "Shout. Go back to your CEOs. Go back and say, 'We can't continue to be so traditional or afraid to do something.'" Even the responses back, like you've just said with the Snapchat thing, without necessarily being too provocative here or naming, phrases like, "Well, you've done all your fun and entertainment, now come back and do your day job or your proper job."

I still think there’s this kind of reluctance, or this understanding, I suppose, and education is clearly going to play a big part. Resonate definitely with that. Change has to happen. Change sometimes can be slow. It can be dynamic by nature, but the very nature, I think, of digital particularly and now social media and all that space that we're talking about today, organisations and cultural changes need to happen.

I'm going to try and bring some summations. Sadly, we’re running out of time, but I want to continue a little bit more if I may, Eric, and then close.

Eric Stoller: Sure.

Alan Seymour: I should give you some time to tell my audience how we can make contact with you, etc. Using my metaphor or analogy earlier here of a sporting nature, the fast ball, the curve ball, whatever analogy I can use here. MOOC, tell us what MOOC means, what your views of it are. Does it work? Is it sustainable? Is it a substitute? Just particularly obviously in education. I'm going to put a little caveat to that maybe, that I've now come out of formal education. I've never come out of education and I will continue to be involved with academia, students, and everything, because the world of education is my passion, and it's my life.

I would never want to be on the side of the argument that says MOOC is everything, or we only use online education now. I have a feeling that some people are looking at online education as a panacea, or as the be all and end all, or maybe in some cases as a substitute for everything that may be wrong or everything that may be logistically difficult in a kind of formal, traditional higher education university environment. Some thoughts on that, if I could ask you, Eric.

Eric Stoller: That’s definitely another curve ball. That’s like saying, "Hey, we’re going to run a 5K, except the distance is now 26.2 miles.” Alan Seymour: Correct.

Eric Stoller: MOOCs, of course, are massive open online courses.

Alan Seymour: Thank you.

Eric Stoller: It was all about scaling learning. How can you bring about educational modules or courses or classes depending on where you're located and what they're called to a large number of people, with an online delivery system. I think that there was a lot of hype around MOOCs early on. Just like with a lot of ed tech initiatives, there's a lot of hype, and there's a lot of versus reality. I think that for me, online learning represents a space or a place for us to continue the conversation of learning with people who aren't... it's not geographically bound.

Are MOOCs the answer to everything? Of course not. I think they're useful, but I think also it's good to separate the moneymaking initiatives from learning and from actually widening participation. I think MOOCs as a vehicle for widening participation or opening up access to these amazing institutions of learning, that's a wonderful opportunity. Now, whether or not it actually comes to fruition for making money for these places, that's a completely different question.

Alan Seymour: Absolutely. Eric. Look, I'm going to bring some summation. We're almost touching my magic 30 minutes here ... I think the insights and the pointers you've made, what you've clearly done, and I congratulate you on this - I’m not being patronising at all; far from it - is that my audience, I've always believed sport is global, sport touches so many people socially, culturally, maybe politically, but I won't go down there necessarily.

Equally, the values and the distinctiveness and all the ways in which it could be done, lifestyle particularly today and the need to communicate, social media has really embellished the opportunities that exist. If you were making some closing pieces of advice to would-be

ibm wimbledon case study

Danielka Edwards

IBM Cloud Case Study Entry Blog

American Airlines old logo

The case study of American Airlines’ partnership with IBM to un-tap cloud resources and transform digital experience reveals the power of technology in shaping airline experiences. For American Airlines to achieve superior customer service through speed innovation and operational efficiencies in its business environment, it must migrate critical applications to the IBM Cloud based on a cloud-native microservices approach. “The route to customer experience transformation is through the cloud” Certainly, adopting cloud computing has its pros and cons for firms. In light of this, American Airlines can save money on IT operations, improve reliability in air traffic operations, boost productivity, and provide rapid app development and release, among others, in US operations. Businesses can quickly react to changing market needs with this agility and scalability of the cloud, demonstrated by American deploying its Dynamic Rebooking app in a record-breaking time.

Nevertheless, it must be noted that there are also disadvantages associated with it. The associated risks include security issues, data privacy, downtime, or interruptions depending on external cloud service providers. To this end, companies should critically examine all these variables while developing robust risk management strategies and appreciating what it means for them in the existing cloud environment. As a staff of American Airlines, I concur with the IBM Cloud solution. This case study shows substantial success in utilizing IBM’s cloud for improving customer experiences, innovative approaches to businesses, and matching technology to the goals of business organizations, among others. The quick building and rollout of the Dynamic Rebooking app, as well as the shift of key applications, highlights the relevance of the cloud for dealing with customer needs.

It is also important to admit that this success happened due to the teamwork of American Airlines and IBM. The fact that IBM’s expertise was utilized with the addition of the IBM Garage method speaks volumes about how crucial it is for a strong partnership and thorough implementation strategies leading to effective cloud adoption. In the long run the aim of the American Airlines is to cost save by avoiding existing upgrade costs via a migration to the IBM Cloud. The outcomes of this partnership showcase one of the most significant transformations in terms of operational efficiency and agility concerning customers’ experiences. However, sustainability and security can only be realized by remaining vigilant and acting appropriately on any emerging security/compliance issue. To conclude, the case study on American Airlines serves as a perfect real-life example of the positive opportunities associated with adopting cloud computing. On the other hand, it is important to conduct a risk assessment and continuous monitoring of security and compliance for sustainability in implementing cloud services.

American Airlines. (2018). American Airlines . IBM. https://www.ibm.com/case-studies/american-airlines

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Case study: IBM Technology Garden


Variable Notes

A look behind the scenes of our IBM Technology Garden

The story of the Technology Garden

A bit of context.

Every year at the Wimbledon Championships, IBM analyses millions of data points, from match and player statistics through weather forecasts to cyber security events and website metrics. For the 2019 edition, George P. Johnson Experience Marketing (GPJ UK) invited Variable to collaborate on Technology Garden and bring that data to life, enabling IBM to tell their story like never before.

In November 2019, IBM Technology Garden won bronze in the Unusual category of Kantar Information is Beautiful Awards in London.

“Our creative concept is the IBM Technology Garden where digital plants in the garden are grown using IBM tournament data. An artistic manifestation of moments of greatness enabled by technology.” — GPJ

Theme: Tennis in an English Garden

Our response

When working on expanding the concept of digital garden we draw inspiration from two major concepts:

  • Colors of UV light photography — a technique used by scientists to expose patterns visible only to insects like bees that see a wider spectrum of light than humans. This is similar to the role of IBM ’s data visualisation in “showing the invisible”.
  • Forms driven by the concept of morphogenesis — a biological process that causes an organism to develop its shape. We perceive this as a metaphor of flexibility of IBM software offerings that can constantly change and adapt to rising challenges imposed by Wimbledon and our ever more data driven world .

We started the project by looking at the types of data available in sample JSON and how it maps to different themes we wanted to talk about (e.g. “Tracking every shot” would use match statistics and “Securing the tournament” would respond to number of cyber attacks in the last hour). With the data in mind, we sketched a number of flower ideas and how the change in the data would influence their growth.

Like most of our data driven projects, we build simple visualisations using d3 to understand the data we are dealing with, the ranges of values, how it changes over time etc. This allows us to build generative systems that show enough variety while having predictable results — stay within given color palette or don’t grow outside of the screen for instance.

To communicate our process with the client and see progress of the visual side of the project we created a Figma board. It contains a data break down, initial sketches, work in progress screenshots and IBM design guidelines all in one place.

Physical Setup

From the very start we knew that we will be using a set of 3 Full HD screens, run from a PC and controlled by an iPad. In order to handle 4K (3840px x 1920px) of WebGL visuals, we equipped our machine with GeForce RTX 2080 for butter smooth performance.

From raw data to local server

Ibm services.

IBM is obviously collecting a vast amount of data during the Wimbledon tournament. Thanks to Watson , they utilise the power of visual and audio recognition, as well as statistics analysis to produce content for the Wimbledon.com website and their various partners.

We only needed a subset of it so IBM provided us a single endpoint combining all the data.

Server layer

In order to synchronise the iPad and the screens, we set up an Express.js server as communication middle point. It is responsible to get the realtime data of the Championships, format them and feed them to clients (iPad and screens) via a socket.io connection.

To make things easier, we packaged the server and the WebGL experience content in an Electron app running in full screen.

With offline mode, backup data from 2018 and caching, our setup has proven very resilient and we experienced no downtime or crash in the 2 weeks of operation during the tournament.

The graphic journey

IBM Technology Garden is a realtime data driven application developed using Nodes — Variable’s in-house visual programming environment for creative coding and data visualisation. The rendering is handled by PEX family of libraries. Although we started with pex-renderer leveraging it’s physically based rendering and high quality post-processing features, the final version of the installation uses our lower level WebGL wrapper called pex-context for maximum performance.

Developing a whole application in a browser based visual programming environment comes with a benefit: the architecture of it is always visible. It is very useful when it comes to identifying patterns and parts of the algorithms shared across flowers. This spatial approach to code organisation has also proven useful during code reviews and refactoring.

Visual Programming does come with its own challenges. Time based values, scene management and transitions are still areas where we experiment with multiple approaches.

The whole graph consists of 156 Nodes with around 90% of them developed for the purpose of this project only, directly in Nodes, in the browser while running the live application. As you will see further in this case study, we used nodes to load, parse and visualise data, create geometry and simulations, experiment with rendering algorithms and were able to deploy for both Mac and PC.

Below is a zoomed-in view of one of the flower scenes. Separation between data processing, geometry generation and rendering is encouraged and comes naturally within Nodes.

Splitting parts of our algorithms across multiple nodes, while keeping common data types for curves and geometry, allowed us to easily reuse flower “recipes” as the project progressed and changed direction. By keeping the data or layout part of the graph separate, and switching between the nodes responsible for rendering, we could test multiple visual outputs without the need to reload the application. This dramatically speeds up the exploration and prototyping phase.

In the image below, we switch from dark Tron-like aesthetics to a new brighter particle system and simply copy part of the old graph with flower filaments to the new one, all of that live while running the application.

Nodes is currently in active development, getting ready for a private beta launching in Q4 2019 / Q1 2020. Learn more about our journey so far or visit http://nodes.io and subscribe to be among first ones to try Nodes.

Initial explorations

For our initial pitch, we wanted to quickly prototype the experience of having an animation split across 3 screens in portrait mode. Using frustum offset in our camera class, we were able to record a particle simulation three times; once for each third of the image. When put together next to each other, it creates very rough yet convincing demo of large scale visuals.

Intro: instanced rendering & GPGPU animation

The IBM Technology Garden experience starts with an idle mode known as attractor state. This part of the installation is not data driven and we had freedom to create something impressive and always changing to catch the attention of people passing by. For this purpose, we designed a GPGPU particle system, meaning that once initiated, all the calculations were happening on the graphics card.

In our early tests, we were able to push the system to 10M particles yet 1M turned out to be enough for the final installation. To achieve realistic lighting and volume, instead of using point sprites, we use instanced planes rotated towards the camera and simulate shading of sphere in the fragment shader.

To achieve the beautiful mix of colors, we lay out our initial particles in layers that start blending during simulation creating unexpected combinations.

Flower A — AI Highlights

First flower is based on AI Highlights data, quick video clips showcasing the best shots and most interesting moments of a game. As we use data like player gesture and crowd excitement, we wanted to create a fast blooming flower full of expressive energy.

This is the flower where we ended up with probably the biggest amount of dead ends, as we experimented with number of approaches with the most notable two being:

  • a particle system based on procedurally modelled curves
  • an agent based system aka “turtle graphics” where we emit number of particles that split and replicate leaving paths behind them as they move forward used as guiding lines for a particle system

We ended up with the particles + procedural curves approach also used in Flower E where we describe it in more detail.

Flower B — Tracking every shot

The data that was to be used for this flower was very exciting: live match score from the games being played on a day.

The idea here was to have a vine that curved in the direction of the currently winning player. Our inspiration came from Moritz Stefaner’s ( @moritz_stefaner ) notabilia.net showing wild natural forms emerging from data as the branches curled and crossed based on an attribute.

With this kind of idea, before getting into the slower process of 3D manipulation, it is often better just to start simple and visualise as much of the dataset as possible in the form of small multiples in order to prove that your idea will look the way you think it will.

For this project, we were fortunate enough to have access to last years’ data. We could use them to test our development and see if the idea was worth pursuing.

The results from the 2D experiment were promising, so the next move was moving the concept into 3D. A key part of the idea came from the concept of the stem curving the direction of winning player, so we started with the curve creation. It worked like this:

  • Start drawing a line with points
  • Displace the points by the difference in score
  • Use the points to sample an adaptive bezier curve
  • Remap that curve to points
  • Connect the new points with cubes
  • Use the distance between points to calculate where branches should be

Some work in progress shots:

Instead of lines we use instanced cubes to keep draw calls as low as possible while easily control thickness of the branches.

One problem we faced was that the branches on the original concept were looking a little sparse.

Although the data visualisation was good it still felt like it was lacking aesthetically. We solved this by adding flowers to the ends of some of the stems to make the vine look ‘fuller’.

It really enhanced the animated version as the growth of the flowers combined with the bloom gave a great ‘pop’ effect as they revealed.

At this point, we hit another wall: although the flowers looked good, they were not data driven. It was important to remind ourselves we were working on a ‘data first’ project and as this was our richest dataset, we needed to stay true to the data. We didn’t scrap the flowers altogether though, we still bloom a flower on the point that wins the set, hence amplifying the significance of that specific point.

Once we had ported this to the lighter background and made the camera follow the growth accurately, we were left with what we presented at Wimbledon.

Below you can see the final render together with an explanation of the different visual elements.

Flower C — Securing the tournament

This is one of the flowers where we had the clearest vision of what we wanted from the start: a representation of IBM Watson deflecting or resisting potential cybersecurity attacks. Inspired by the shape of the dandelion, we decided to have a central Watson core with the dandelion seeds as attacks.

Below are some of the core explorations:

We eventually decided to go with:

Due to the sheer number of cylinders needed to create this effect, we ran into performance problems when calculating the positions of the particles using the cpu. We mitigated this issue by moving all movement calculations to the graphics card. With shaders calculating distances and positions, we could move the heavy lifting off and make the code significantly more efficient.

The result was very close to the original concept — which is a rare thing in a project with as much creative freedom as this one.

Flower D — Website Visits

This “flower” is actually more grass than flower. The density and the length of the strands depend on the number of visitors for the Wimbledon website. We tested a couple of different color schemes and PBR materials.

We even experimented with different layouts like this “underwater snake”. They were unfortunately too far from the aim of the brief.


The final colors are more in line the the overall color palette and the blades themselves are made our of instanced sphere particles instead of cubes like above.

Flower E — Weather

The last flower is responding to weather data like temperature or wind speed and direction. Our first prototype was very mechanical and rigid.

The most interesting part of the flower are the leaves modelled after a leaf of hyacinth as described in the classic On Growth and Form by D’Arcy Wentworth Thompson (1945 edition, free download, page 1045 of the PDF).

We first generate the edge lines of the leaf and then distribute particles between them randomly. That creates a point cloud volume matching the shape of the leaf. The initial points are then fed to a particle system allowing us do smoke like simulation using curl noise.

Problems with glare and change of visual direction

Once we have received the hardware, we could start testing the content. Quite quickly we realised that the dark background and sci-fi color theme will not work outdoors. Our studio at Makerversity has very big windows allowing lots of sunshine which was causing large glare reflection on the screens. Some of our experiment with a brighter background didn’t have this problem and, even though we were already half way through the project, the decision has been made to switch to bright colors. A direction that has proven much more pleasing in the end as it stands out from the usual high tech look.

Post-processing tech

In order to infuse the organic forms of our flowers with a more digital look, we decided to add a slight “electric blue” glow in post processing. As most of the scenes are made out of particles, adding Screen Space Occlusion also helped to add depth to each them.

Our final post processing pipeline is setup as follows:

Screen Space Ambient Occlusion (SSAO)

SSAO is a method of approximating ambient occlusion with local shadows occurring in densely occupied areas. The actual implementation we are using here is Scalable Ambient Obscurance (SAO) developed by Morgan McGuire and ported to WebGL by Travis Fischer. The main benefit compared to traditional SSAO is better performance and nice looking shading over wider area.

Bloom is what makes some particles seem illuminated or especially bright by blurring the area around them. To achieve very wide blur radius, we extract the brightest colors of the image and then iteratively downsample it (resize to a smaller image) and blur them at the same time. Those resulting images are then added together and composed on top of the final image. Because we use a HDR rendering pipeline, the saturation and hue of the colors stays intact.

Single pass Depth of Field (DoF)

A huge boost in the aesthetics of the project was achieved after depth of field implementation. This effect is commonly achieved using multiple passes (drawing and blurring texture multiple times), however Dennis Gustafsson ( @tuxedolabs ) wrote a brilliant and informative blog post about implementation of single pass DoF. This was optimal for us. Due to some of the performance limitations associated with WebGL, we wanted to keep the number of passes down to an absolute minimum to keep everything running realtime. In the end, it performed beyond even our highest expectations.

A small gotcha with this was that you need to modify the sample sized based on the resolution of the screen or your DoF will not correctly scale with resolution changes.

LUT color grading

For a final touch of artistic flexibility, we decided having fine control of the colour grading was important so we implemented 2 systems.

Firstly, we implemented Lookup Tables (LUTs): these works by having a hue cube flattened and saved onto a texture in slices. During this pass you can look up the colour of the current fragment at its position in the lookup table to get a new colour. This way you can import your lookup table into image editing software and alter the curves/colour profiles and the same operation will happen to your realtime colours.

The second control was simply sliders for brightness, contrast, and exposure. Due to the dynamic nature of coding in Nodes this gave us very fast and flexible control, allowing us to play with values as the scene is running and without the need for external software.

Companion iPad controller

We wanted the controller to be as simple and user-friendly as possible to keep the focus on the main screen. The iPad is in the hands of a host who explains what is visible on screen and go through the timeline of each flower depending on visitors interests.

In this spirit, we have built a React app that would be saved as an App on the iPad’s homescreen. The controller app was a good candidate to go full functional JavaScript with the use of React hooks . Based on Create React App , it is enhanced with the foundations of many other apps: react-router , react-intl and emotion . It communicates with the Electron App –the one running the server and the display– via socket.io .

The user flow is straightforward. The home page presents the 5 flowers:

After tapping on one of the five flowers, we fetch in realtime the latest tournament data available. We then land on the selected flower screen which includes an explanation of the data used and how they influence the shape of the flower. A timeline with previous data is also present so the visitor can experienced different flower for each dataset.

The device offers a second reading layer for the data and serve as a support to tell the story behind the data.

Parting words

At Variable, we believe that data can be experienced, not only counted. IBM Technology Garden achieved both of those goals as we managed to create something beautiful yet readable and true to the data.

Thanks again to GPJ for giving us this opportunity and creative freedom, and to IBM for the amazing work on the data side.

If you have any questions or interesting project you would like to discuss, say hi on Twitter @variable_io or drop us a line at [email protected] .

The cover image was generated using ofxTSNE by Gene Kogan ( @genekogan ) and ofxAssignment by Kyle McDonald based on ImageTSNELive example from Machine Learning for Artists also by Gene Kogan.

Case study written by Marcin Ignac ( @marcinignac ), Damien Seguin ( @dmnsgn ) and Simon Harris ( @simonharrisco ) from Variable.


Written by variable

Data Art and Generative Design Studio in London

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IBM Watson for Cybersecurity Takes Center Court at Wimbledon!

ibm wimbledon case study

141-year-old tennis tournament – The Championships, Wimbledon utilizes IBM Watson to protect their brand against increasing risk of cybercrime.

The world is getting intertwined with billions of internet-connected devices fueled by artificial intelligence and machine learning. The number of such connected devices in every realm of today’s world will soon outgrow the world population by many folds. As we strive to advance in this digital age, the dangers arising specifically from the lack of security aspects of digital revolution are overlooked by most and thus the absence of good governance, policies, standards, adequate controls and availability of funding to effectively address vulnerabilities is creating serious challenges.

One of the organizations facing these challenges, in today’s digital realm, is the 141-year-old tennis tournament – The Championships, Wimbledon (or simply called Wimbledon) [1].

Magnitude of the Issue

In today’s digital realm, most fans experience Wimbledon off the field. Hence, Wimbledon must leverage its digital platform to deliver that great experience through its website, mobile app, TV, social media, etc. [2]. The Wimbledon website had 436 million page-views in 2017, a 10% increase from 2016 [3]. (Figure 1). With this massive “digital” fan base, comes the increases risk of cybercrime as well and hence, a cyber-attack during the game, disrupting Wimbledon’s digital platform, would really hurt Wimbledon’s 141-year-old reputation. As a result, the need of a cyber resilience tool which utilizes machine learning and artificial intelligence to stay a step ahead of these cyber-attacks is heightened.

Pathways to Just Digital Future

ibm wimbledon case study

It’s not just the volume of attacks that is mind boggling, it is the deceptive nature of attacks that is more concerning. Usually most of the attacks would be released to trick the security operations analyst (and automated tools) into focusing their energy on a part of the system, while at the same instant, unknown to the analyst, some completely other part of the Wimbledon digital backbone is being targeted. This is what is defined as “low and slow” coordinated attack [5]. A security analyst would not be able to able to correlate these data points manually without the help of a SIEM tool.

IBM Watson to the rescue

IBM has been the official Information Technology partner to the Wimbledon for 29 years [6]. In 2017, IBM brought in Watson (integrated with QRadar – IBM’s Security Information and Event Management tool), a supercomputer that uses machine learning and artificial intelligence to analyze data points, to assist the security operations at Wimbledon to investigate 200 million events and help identify, detect and protect against the potential threats during the tournament, with speed and accuracy [7].

The entire infrastructure (QRadar + Watson) brought together and correlated data, in real-time, from over thousands of connected endpoint devices and peripherals on the platform and populated the QRadar threat matrix and dashboard. This dashboard provided the security analyst the complete picture of the attack and a set of steps and recommendations that should be initiated to mitigate the cyber threat. In some instances, Watson was able automatically invoke other connected components on the network to derail the attack [8].

ibm wimbledon case study

The results were fantastic. IBM QRadar with Watson was able to correlate huge volume of events 60 times faster than an average human security analyst . This translated into 5 times more number of events being analyzed . More importantly, this resulted in ZERO successful breaches impacting the Wimbledon website [10].

Going Forward at Wimbledon

Cyber-criminals are looking for different and creative ways to evade technology – either by developing new malware that can detect correlation activities and stay in a “hibernation” mode awaiting the right moment to execute, or by targeting the less skilled humans in the organization [11]. The attackers only have to be successful once while the power-combo of a security analyst with IBM Watson, at Wimbledon, has to stay on top of every attack each time. Going forward, the executive management at Wimbledon should start increasing the overall awareness about cybersecurity and its potential threat, not only internally, but also to its fan base, while continuing their ongoing investment in the technology to protect their brand from a bad cyber day. It’s a continuous improvement process and not just something that could be easily accomplished within the two-week period when the tournament is on.

The Future?

With the exponential advancement in, and the ease of access of machine learning and artificial intelligence capabilities, cybersecurity is not just a problem related to the IT department anymore. Today, cybersecurity touches every single business unit within an organization – including an organization’s C-Suite and the Board. But are the Boardrooms sufficiently prepared to address the rapidly growing cyber risk and integrate cybersecurity into the organization’s overall business strategy and make sure the organization is not left operationally paralyzed when a cyber event knocks on their door?

(Word Count: 769)

[1] Wimbledon History – 1870s, http://www.wimbledon.com/en_GB/aboutwimbledon/history_1870s.html

[2] Wimbledon serves more AI in 2018, Elizabeth O’Brien, June 2018, https://www.ibm.com/blogs/game-changers/wimbledon-serves-ai-2018/

[3] IBM at Wimbledon 2018, June 2018, https://www.ibm.com/thought-leadership/wimbledon/uk-en/

[4] IBM at Wimbledon 2018, June 2018, https://www.ibm.com/thought-leadership/wimbledon/uk-en/

[5] Wimbledon 2017: Manicured Lawns, Ivy-Covered Buildings, Tennis Whites and Cyberattacks,  Johnathan Van Houten, July 2017, https://securityintelligence.com/news/wimbledon-2017-manicured-lawns-ivy-covered-buildings-tennis-whites-and-cyberattacks/

[6] IBM at Wimbledon 2018, June 2018, https://www.ibm.com/thought-leadership/wimbledon/uk-en/

[7] Wimbledon 2017: Protecting the oldest brand in tennis with the latest in cognitive security, 2017, https://www.ibm.com/case-studies/wimbledon-2017

[8] Cybersecurity Behind the Scenes at Wimbledon, Eleanor Dallaway, August 2017, https://www.infosecurity-magazine.com/news-features/cybersecurity-behind-the-scenes-at/

[9] IBM Security helps Wimbledon focus on the court, not the cloud, IBM Security (YouTube Channel), October 2017, https://www.youtube.com/watch?v=m-hq2aOMeuE

[10] Wimbledon 2017: Protecting the oldest brand in tennis with the latest in cognitive security, 2017, https://www.ibm.com/case-studies/wimbledon-2017

[11] Challenges Facing Using AI in Cybersecurity, Ahmed Banafa, March 2018, https://www.bbvaopenmind.com/en/challenges-facing-using-ai-in-cybersecurity/

[12] Featured Image: American Men Long Shots (Again) to Win Wimbledon, June 2018, https://www.outkickthecoverage.com/american-men-long-shots-win-wimbledon/

Student comments on IBM Watson for Cybersecurity Takes Center Court at Wimbledon!

Your last question reminded me of the AI roundtable I organized in my previous job, where we invited C-suite executives to discuss AI’s impact on the business. All the executives were highly aware about the importance of AI/ machine learning/cyber security, but they are not necessarily sure about how to deal with it. One interesting discussion we had is that what the company is lacking the most is not just the tech-experts, but also the “translators” who can translate the needs from the businesses for the tech-experts to solve the right issue, and also translate the solutions that the tech experts developed into business values. While developing an overall strategy around cyber security is important, I think the board will also need to consider a broader view on their HR strategy.

As a tennis fan, I found this article very interesting. I watch the Wimbledon every year, so I am definitely in the population of people that this technology is trying to protect. That said, I am a bit confused as to why the website is so important. I get most of my Wimbledon content from google or ESPN. Are they feeding from the Wimbledon website? Overall, I do think that cyber threats is something every organization will need to think about. Most large traditional organizations only really consider taking the necessary steps after a disaster (take Target’s for example), but its great that technologies like IBM Watson are doing this in a way that is more efficient.

It was great to read about the success of IBM QRadar and Watson, both in terms of speed (60x faster than human analyst) and preventing any breaches on the Wimbledon website. [1] I hope that all companies are taking the necessary steps to protect their own and their consumer’s information, as we have seen the terrible implications of cyber attacks on the reputations of Target, Under Armour, Yahoo, Equifax, and others, where consumer trust is hard to gain and earn back. I do feel that the vast majority of companies today are taking this threat very seriously, and there have been a lot of startups being backed by venture capital firms that attempt to address cybersecurity issues. The big challenge I see with machine learning and artificial intelligence to tackle this issue is that while machines are excellent at processing and analyzing historical data, the most threatening cyber attacks are unprecedented, and therefore likely a challenge for machines to detect based on historical information. I am also concerned about heightened personal cybersecurity for individuals, as today, most people store all their personal information on their personal computers and phones, and most individuals don’t have the means to purchase/attain personal cyber protection.

[1] https://www.ibm.com/case-studies/wimbledon-2017 .

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SPSS Analytics Partner

SPSS Statistics for Data Analysis in Academia- The Perfect Match

Wimbledon High School is an independent day school based in London. Established in 1880, they offer a holistic education of cross-curricular study alongside consistently excellent teaching to over 1,000 girls, aged 4 to 18.

The school has embraced a ‘STEAM’ approach, combining the Arts with STEM subjects in enriching interdisciplinary study that fosters creativity and problem solving and prepares students for university and beyond. They run over 140 co-curricular clubs, ranging from music, sports and drama to robotics and data science. The Racket Research Club was formed when teachers and students brought together their love of STEM subjects and interest in data science with an interest in sport. It promised an environment where students could learn, explore and gain from the experience of working with specialists in the field.

The Racket Research Club at Wimbledon High School was given license to use a dataset from All England Lawn Tennis Club (The Championships, Wimbledon) for the purposes of educational analysis and interpretation.

Members of the club were tasked to understand whether there were any patterns or trends within the dataset, testing their own hypothesis within the tennis game and whether there were any statistical factors that impacted the outcomes.

Given the scale and size of the dataset, the school was very keen for the girls at Racket Research Club to work with the data to support class and project work and gain valuable data analytics experience.

The Racket Research Club

The Racket Research Club is just one of the groups that Wimbledon High School operates as part of their numerous STEM activities. This club has been running in the school since 2018 and there are, on average 8 to 10 regulars in the club.

The students in the club are in key stages 4 and 5 (ages 15-18) and they were fortunate enough to continue during Lockdown as project work could be presented and delivered remotely.

Historically the Racket Research Club had not been using any tool or specific data analysis application to support their research and had been working mainly with MS Excel to analyse the data and produce graphs.

Dr Clare Roper, Director of Science Technology & Engineering who oversees the Departments of Biology, Chemistry, Physics & Computer Science, runs the numerous groups within the Big Data Science Club, including the Racket Research Club, and was keen for the students to publish their tennis data research.

Given the size of the data set, Dr Roper realised that supporting the club’s findings with credible statistics could only be achieved with the help from a trusted data analysis tool. The results were not going to be of any value to the scientific community if they were not backed up with statistics.

Exposing the students to this type of project work and experience in their school years was an unmissable opportunity, particularly for those students who were showing an interest in STEM subjects and occupations. The school is dedicated to inspiring and guiding the girls within a supported environment, to experiment and get involved in projects that deliver real life experiences and a unique perspective into today’s working life.

Having historically used the statistical analysis tool SPSS from IBM, Dr Roper contacted them to understand what software options may be available to the school, and IBM referred the school to IBM SPSS Partner Version 1 and their dedicated SPSS team to assist.

The club initially made use of a trial version of the software and within that short space of time, were able to sort the data and produce their results. One student involved in the research project created her research paper which was subsequently published on the International Journal of Performance Analysis in Sport. She initially performed some descriptive statistical tests to check the data for normality and then ran a series of ANOVAs (analyses of variance) and ANCOVA (analyses of covariances), to evidence the statistical differences between serve speed in various categories (1st versus 2nd serves in female and male players).

After the success of the Racket Research Club research publication, Dr Roper was keen to deploy SPSS to a larger group of school users. This would create an opportunity for the following:

  • Eliminate where possible, any coding groundwork. The users could confidently enter their data and trust that SPSS would deliver the right results without any complicated coding or programming
  • As some of the Maths and Biology modules included an element of statistical analysis, pupils and staff would benefit from gaining access to SPSS to support their class work
  • Any of the Big Data Research Club members would gain access to the software

The longer-term solution for SPSS was to allow a larger group of staff and students access to the software. The school sought the advice of Version 1’s SPSS team to understand the various options available to them.

SPSS Academic Solution from Version 1

Version 1 are the sole supplier of the SPSS Academic License in the UK and Ireland, providing IBM SPSS to over 250 Universities and Colleges. It’s Version 1’s aim to increase the ability of students and academics to both learn and teach statistics using IBM SPSS.

SPSS is an advanced statistical analysis tool used in all industries throughout the world to understand complex data, gain statistically significant insights and predict future outcomes. From an academic point of view, SPSS is heavily used by students and staff for all types of statistical analysis, survey research, and for administrative purposes. By using SPSS, both students and staff can gain statistically significant insights from data and produce intuitive reports to convey the results

Version 1’s SPSS Academic team engaged with the school’s stakeholders to understand the license requirement across pupils and staff, and were able to tailor a bespoke license solution that catered for both sets of users within the school’s commercial budget allowing for use both on and off site. Once the SPSS trial had expired Version 1 provided temporary licenses to ensure students stayed up and running with SPSS while the contract was put in place. Once the purchase was complete the school was able to quickly install the software on the school’s hardware and any specific pupil’s laptop.

Benefits of using SPSS

The benefits to the school staff and in particular, the students when using SPSS, has been considerable:

  • The students benefit from the unique experience of working with real-world datasets, running tests and analysing results in a supported academic environment, enriching their understanding and knowledge of organising datasets and testing.
  • Some of the science subjects within the school curriculum have a statistical element (Biology, Maths) and those students that have had exposure to statistical analysis within the science clubs have benefited greatly from this experience within their curriculum course work.
  • Organising and running the tests on very large data sets has been much quicker and easierwith SPSS.
  • SPSS has an easy-to-use user interface. Students can explore and analyse data using code or a visual user interface.
  • SPSS also provides help at every step. Students can get help from the Help menu or help to understand statistical tests and techniques as they work

Looking Ahead

As a result of The Championships, Wimbledon data and subsequent publication of the results, the opportunities for taking advantage of SPSS’s usability and features have been realised with access broadened across the school. This will give the school the opportunity to expand the scope of their Big Data Research Clubs and include their students in more real-life data science projects offering an unrivalled level of insight and experience.

For those girls with a particular interest in STEM subjects, this early life exposure to data science methodologies and research provides an invaluable foundation of learning that underpins their academic studies and introduces the opportunity for exciting careers in science and technology.

Claims Management SPSS Modeler

SPSS Learning Hub

Version 1 are the sole supplier of the SPSS Academic License in the UK and Ireland

We provide IBM SPSS to over 250 Universities and Colleges to increase the ability of students and academics to both learn and teach statistics using IBM SPSS. We also provide solutions to improve student retention rates, deliver the best student experience and create a smarter student recruitment strategy. Version 1 offers a variety of options for integrating statistical and data mining instruction into the classroom ranging from individual user licenses to smaller school or college licenses and ultimately unlimited user University site licenses.

The ocean stretches to the horizon

As cyberattacks grow in volume and complexity, artificial intelligence (AI) is helping under-resourced security operations analysts stay ahead of threats. Curating threat intelligence from millions of research papers, blogs and news stories, AI technologies like machine learning and natural language processing provide rapid insights to cut through the noise of daily alerts, drastically reducing response times. Watch the video to see how AI helps analysts connect the dots between threats.

Read the IBV report on AI and automation for cybersecurity

Get insights to help you anticipate and stay ahead of cybersecurity threats.

AI improves its knowledge to “understand” cybersecurity threats and cyber risk by consuming billions of data artifacts.

AI analyzes relationships between threats like malicious files, suspicious IP addresses or insiders in seconds or minutes.

AI provides curated risk analysis, reducing the time security analysts take to make critical decisions and remediate threats.

Cognitive security combines the strengths of AI and human intelligence. Cognitive computing with Watson® for cybersecurity offers an advanced type of artificial intelligence, leveraging various forms of AI, including machine-learning algorithms and deep-learning networks, that get stronger and smarter over time. Watch the video to see how IBM Security® QRadar® Advisor with Watson® helps you get a head start in assessing incidents to reduce your cyber risk.

The rise in remote work trends and interconnectivity of endpoints comes with its own set of cybersecurity challenges. To combat these, there is a need for a modern, AI-driven endpoint response and detection tool that can proactively block and isolate malware and ransomware threats and propel endpoint security into a zero-trust world.

Leverage the power of cognitive AI to automatically investigate indicators of compromise and gain critical insights. QRadar consolidates log events and network flow data from thousands of devices, endpoints and applications, correlating them into single alerts—so you can accelerate incident analysis and remediation.

Orchestrate and automate hundreds of time-consuming, repetitive and complicated response actions that previously required human intervention. The open and agnostic platform integrates with your security infrastructure and establishes a central hub for managing your response playbook with speed and agility.

Get cognitive insights, contextual analytics and benchmarking to make sense of security events—while protecting your endpoints, users, apps, docs and data from one platform. Discover endpoint vulnerabilities, protect corporate data and uphold compliance, with containment plus identity and patch management from the industry's first and only AI approach to UEM.

Use autonomous AI threat detection and threat hunting capabilities to ensure business continuity by blocking ransomware and zero-day attacks. Deploy the cyber assistant, an AI-powered alert management system that helps combat alert fatigue within security teams, reduces analyst workloads, and cuts down on false positives, saving valuable time.

Case studies

Wimbledon partnered with IBM Security to protect its digital presence from thousands of cyberattacks over the course of the iconic sporting event.

With financial services as the most-targeted industry, Cargills Bank has taken a proactive approach to safeguarding customers’ data by deploying an AI security solution.

Environmental firm RGS Nordic uses IBM MaaS360 with Watson to gain 100% visibility of hundreds of mobile devices on its work sites.

Sogeti Luxembourg and IBM® developed an alliance to provide companies with a security operations center that could uncover advanced persistent threats faster.

Get an overview of AI technologies, their origins and evolution.

Explore how AI impacts the cybersecurity workforce, ethics and other security issues.

Read insights about risk in a changing world, including factors that can amplify costs.

Explore the IBM-commissioned Total Economic Impact™ study that examines the benefits of QRadar with Watson.

Learn about protecting critical systems and sensitive information from digital attacks.


  1. Wimbledon Case Study

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  2. Wimbledon Case Study

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  3. Wimbledon Case Study

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    Wimbledon is increasing. Last year, the Championships were shown on 129 TV channels in 185 territories, enabling over 748 million households to watch the action. The number of unique visitors to the official Wimbledon web site - www.wimbledon.org - also grew dramatically, reaching 8.6million, an increase of 83% from the year before.

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  20. IBM Watson for Cybersecurity Takes Center Court at Wimbledon!

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