Philipp works as a Sales Engineer at Splunk. His background is in data visualization and analytics with experience in automotive, transportation and software industries. Philipp’s focus is to leverage Splunk as a data platform for analytics and visualization. He recently won the Deutsche Bahn Hackathon analyzing a 10GB data set around railway infrastructure in 24h (read more: http://blogs.splunk.com/2015/06/08/splunk-team-wins-db-infrastructure-data-challenge-in-24h-iot-hackathon/). In collaboration with Robotron Philipp is working on data mining approaches for the IoT and industrial data to optimize business processes.

We are proud to have Philipp presenting at Data Natives 2015!

Can you describe your professional journey up to the point of joining Splunk?

First of all thanks for this interview and I’m looking forward to Data Natives 2015! Before Splunk I worked as a freelance software developer and consultant on many interesting projects – mainly in the automotive and transportation industries. I was focused on real-time 3D visualization to make heterogeneous data accessible and meaningful – regardless of whether it’s car data or complex infrastructure planning projects. As well as that I was researching visual text analytics and published two papers. For the creative part I’ve been active in digital arts for years and realized many audiovisual and interactive art projects like http://www.cubeflow.de.

What kind of problems do you aim to solve as a Sales Engineer at Splunk?

With the variety of ways that Splunk software is used by our customers, I deal with many interesting and different use cases covering IT operations, security, application delivery and business analytics. Recently I’m working on more and more projects in the area of industrial data and the Internet of Things.

How has the field of business intelligence evolved over the last few years with the rise of ‘Big Data’?

I think there is a continued shift in BI since the rise of ‘Big Data’ as new data sources and types following the ‘four v’s’ principle (volume, variety, velocity and veracity) come into play and add substantial value to existing data. Technically, it can be challenging to get insights from such a changing data landscape quickly. This is where Splunk makes the difference: as a universal platform for machine data Splunk provides this flexibility due to late binding and a powerful search language to correlate and analyze heterogeneous data at large scale – including both real-time and historical information.

If you could apply the technology being developed at Splunk to any real world problem, which would it be and why?

That’s a funny question because in fact all the technology developed at Splunk is used to tackle real world problems: to prevent and detect cyber threats and fraud, proactively monitor IT infrastructures to find and fix errors quickly, analyze and visualize business processes, machine data and sensor data to get new insights. For Example Splunk software is used at the Police station in Chandler, in the USA: They evaluate data to support officers on patrol and monitor problematic neighborhoods. And the IT departments of financial institutions use the software to secure online payments.

What are the key lessons you’ve learned in your career? Biggest ‘Ah ha!’ moments or mistakes?

Expressing it for a real data native: It’s about 10% inspiration and 90% perspiration. If you want to achieve 100% you need to combine 90% and 10% wisely.

What advice would you give to technically minded youths looking to get their career started?

Keep an open mind and learn about different technologies to connect the dots.

Which companies individuals inspire you, and keep you motivated to achieve great things?

There have been many companies and individuals that inspired me in different parts of my career, but one of my great inspirations is people in history: philosophers, inventors, artists. Right now I enjoy working with brilliant people here at Splunk.

Alistair Croll is an entrepreneur with a background in web performance, analytics, cloud computing, and business strategy. In 2001, he co-founded Coradiant (acquired by BMC in 2011) and has since helped launch Rednod, CloudOps, Bitcurrent, Year One Labs, and several other early-stage companies. He works with startups on business acceleration, and advises a number of larger companies on innovation and technology.

A sought-after public speaker on data-driven innovation and the impact of technology on society, Alistair has founded and run a variety of conferences, including Interop’s cloud content, Cloud Connect and the Enterprise Cloud Summit. He’s the chair O’Reilly’s Strata + Hadoop World conference; the International Startup Festival; and Next:Money. He has also written several books on technology and business, including the best-selling Lean Analytics,and is currently working on Different Better, a book about positioning in the digital age, with April Dunford.

We are proud to have Alistair presenting at Data Natives 2015!

You’re involved in a number of different organisations, from O’Reilly Media to CloudOps and Founder Fuel. What motivates you?

I’m after whatever’s interesting. The economist Herbert Simon observed that we live in an attention economy, because we’re surrounded—overwhelmed—by information, and what information consumes is our attention. And when we don’t know what to pay attention to, we focus on what’s interesting.

Some people solve for safety, or money, or fame. Most of the good things that have happened to me come from solving for interesting. That means I’m motivated by finding the next interesting thing, which can be hard to sustain. But we live in fascinating times, as we’re moving our culture and even our species from atoms to bits, so I don’t get much sleep.

[bctt tweet=”We’re moving our culture and even our species from atoms to bits, so I don’t get much sleep.”]

What attracted you to analytics as a subject, and when did you career first move in that direction?

And I think we are at a critical time in human history where we need science, attention, and data to solve some really hard problems: conflict, climate change. There’s no good reason, for example, for any human on the planet to starve. But for millennia, we’ve made decisions based on anecdote, opinion, and the loudest voice in the room.

I think data can change that, replacing opinions with facts. I’ve always been analytical. I studied hard at stats in college—it’s a long story I’ll explain over beers sometime—but my real interest came when I was at Coradiant. We built a product that could tell you where your website was broken, but we had to talk to people in charge of analytics in order to sell it.

And so often, those people didn’t have a good understanding of the business model. They were collecting data for the sake of collecting it, or at best, collecting vanity metrics that didn’t really drive the business.

What problems do you tackle at CloudOps?

CloudOps was founded by many of the managed services people at Coradiant, when Coradiant pivoted to focus instead on building application performance management hardware.

The company is helping enterprises to move to, and operate in, the cloud.People misunderstand the cloud. Just as the real reason for big data is to make better decisions, so the reason for cloud computing is to improve organizational agility. I help CloudOps think about strategy, and publish research on things like migration strategies, what kinds of applications belong where in the organization, and how to tie organizational processes—like lean startup, for example—to the underlying tools.

How did you get involved with O’Reilly Media, and what does your role of Co-Chair of Strata entail?

I wrote a book called Complete Web Monitoring in 2009 with Sean Power for O’Reilly, based largely on what I’d learned at Coradiant. When O’Reilly wanted to launch a big data conference they had an in-house data scientists, Ed Dumbill, who was already working on the idea; they needed an outsider with a background in marketing and analytics.

Before Strata I’d run MCd, and launched a number of events—Bitnorth, Startupfest, the Enterprise Cloud Summit, Cloud Connect, and GigaOm Structure—so I was fairly familiar with how conferences are run. The trick is to find interesting, unexpected stories. We call this “edutainment.” So much content is available for free online these days that there needs to be a unique experience associated with the event.

As co-chair, I help built the tracks and content, and work with keynote speakers to ensure their talks fit the tone of the event. Along with my other chairs—Roger Magoulas and Doug Cutting, as well as Ben Lorica, who handles the program—we write about where we think the industry is headed and what topics will be important next year. Because of the scale of the event we’re always planning well over six months ahead.

Are there any key sources for personal development and learning in your career?

I had an amazing professor in college, Tony Schellinck, who was a market researcher. He encouraged me to do an honours’ thesis in marketing, which I wrote on evolutionary theory and product lifecycle. He wasn’t tenured, because he was busy running an actual business. That’s not really a source, but he was a turning point for me.

I spend a lot of time talking to people about unexpected things. For example, as I write this I’m flying back from a presentation to a number of big insurance firms, where I discussed the impact of the sharing or “gig” economy on insurance. In researching the talk, I probably learned from twenty Uber drivers—one was an ex-convict, one a Shriner, and one a deaf-mute.

The really interesting insights come when you marry two unexpected things together. That’s what humans are great at: having ideas if you give them a chance. So while there aren’t any specific sources I learn from, the best source is the one I haven’t heard of yet, but am just about to discover.

[bctt tweet=”The really interesting insights come when you marry two unexpected things together.”]

What advice would you give to young professionals looking to find their feet in software engineering and data related disciplines?

One in five jobs today will be done by a machine in the next ten years. I think that’s conservative: Consider that predictions for how fast we’d sequence the human genome were wrong, because we found better algorithms. Then consider that Tesla just bypassed the regulation of self-driving cars by effectively pushing software to vehicles already on the street. So it may be even more than one in five.

Now look at how we teach. It’s modular, standardized, bottom-up. That’s exactly the kind of thing a machine will be able to do. I’d focus as much as possible on top-down problems. Don’t ask, “these are the pieces I have; what can I build with them?”; rather, ask, “this is a thing that needs to be built; where can I get the pieces?”

This is more of a liberal arts take on the world. Amazon/Pinterest data scientist John Rauser said that the role of data scientist is a quarter math, a quarter engineering, a quarter skeptic, and a quarter narrative. I think that’s a good blend.

Finally—jump in. Careers don’t last a lifetime any more. In 1950, the lifespan of the average company on the S&P 500 was over 50 years; now, it’s barely 15. You’ll work for many companies. So while you can, take risks, and work in a variety of roles at a variety of companies, so you can triangulate what you’re good at.

Which companies individuals inspire you, and keep you motivated to achieve great things?

I see initiatives like Code for America and the GSA in England, and the government of Estonia, and think that we can do government so much better, speeding up processes and encouraging civic engagement. As a Canadian I have high hopes for Justin Trudeau’s newly-elected Liberal government, which puts a new generation at the helm of what I think can be an amazing country. And of course, there’s my daughter; I want to leave her a world better than the one I found.

(image credit: techmsg, CC2.0)

Louisa Heinrich is the Founder of Superhuman Limited. She brings over 23 years’ total experience (18 in Digital), working with businesses and governments to design strategies, products, services and organisational structures that use digital technology to improve individual lives, make a positive contribution to society, and achieve commercial results.

She has held many titles, including Design Director in the first dotcom boom, Executive for Future Platforms at the BBC, and most recently Head of Strategy for international Service Design agency Fjord. She has led teams worldwide for multi-national businesses, is a thought leader and a recognised speaker on the intersection of people, technology and business.

We are proud to have her presenting at Data Natives 2015!

What led you to the creation of Superhuman?

I saw some trends and challenges emerging across the digital world that I didn’t feel could be properly tackled from inside the existing agency model, or from inside a single corporate – trends in the way human beings are considered (or not) in product development, the way new ideas are developed and monetized, the way success is measured, the way strategies are adapted and adjusted as circumstances, technology and people’s preferences change. I created Superhuman to be as nimble as possible, responding to changes in the landscape and helping businesses respond to those changes as they emerge, in whatever way makes the most sense for the business and the challenge at hand.

You’ve been a startup mentor at Wayra and Highway1 for some time now – what do you find yourself telling new founders over and over again?

That the customer needs to be embedded in every part of the company, not just Marketing – a lot of entrepreneurs still subscribe to the notion that you can make whatever you like and then marketing will determine whether it succeeds in the marketplace or not. In reality, the most successful products and services are built from the start around a need, desire or challenge that people have. Marketing can’t fix a poor experience, and a great customer experience is the best investment a young business can make.

Your time at the BBC must have been fascinating. How did you go about fostering innovation within a national broadcasting company of that size?

The BBC is actually full of brilliant people who have a genuine desire to be innovative, to push things forward, to make the world a better place. It’s remarkable and humbling and wonderful, and I’m still friends with many of the fine folk I worked with while I was there. Of course it’s also rife with politics, like any organization of that size, but finding and connecting with like-minded folk from across the divisions can go a long way. Ad-hoc and under-the-radar projects often end up feeding into much larger programmes of work – some of the threads we kicked off years ago are still running now, albeit in different forms. Innovation is a state of mind, not a team or a process. Making things happen is often just a matter of having the drive and the patience to find a way through. And having such a volume of amazing content to work with is an ongoing inspiration!

[bctt tweet=”‘Innovation is a state of mind, not a team or a process.’ – @customdeluxe”]

The Internet of Things is one of the most heavily hyped subjects in tech – what’s the truth behind the buzzword?

The truth is that, outside of some operational contexts (supply chain management, manufacturing and logistics, etc.), nobody yet knows what the Internet of Things is going to be. How could we? The idea that virtually any object could have the capacity to communicate – it’s both mind-boggling and strangely banal. On the one hand, do you really want or need your toaster to talk to you? On the other, how wonderful would it be to feel close to a loved one who’s thousands of miles away, without having to look at a screen? I think it will take some time and experimentation before we really understand what all this means.

Are there any IoT applications that particularly excite or impress you?

I’m really excited about the idea of using technology to facilitate human interaction, to enable us to be more present in the real world around us. For example, we talk a lot about ‘Smart Cities’ but at the moment, most projects that fall under that heading are focused on infrastructure. What about the people and the communities that exist inside those cities? Aren’t they the real heart of the city? I think IoT could facilitate an ‘Internet of Neighbourhoods’ where people come together to form more close-knit communities, assisted by connected objects and places. We’re starting so see some of these things happen with the Things Network in Amsterdam, and I’m hopeful we’ll see more and more.

I’m also really impressed with connected objects that are completely intuitive and, at the same time, highly flexible and adaptable. One of my favourite examples is the Good Night Lamp by Alex Deschamps-Sonsino. It’s a family of internet-connected lamps – a ‘parent’ lamp and one or more miniature ones. When the parent lamp is switched on, the babies turn on as well. It’s so simple that everyone gets it instantly, and yet it can be used to mean whatever its owners want it to – a hello between friends, a check-in with a family member, an invitation, anything. And most importantly, all you do to ‘set it up’ is take it out of the box and plug it in.

I guess the things I most admire in the IoT space are the ones that genuinely make things simpler or better for people – a lot of the projects I hear about might add automation or features, but also come with a lot of overhead in the form of control apps, settings panels and so forth.

What superpower do you think technology could give us next?

Ha! What a question. Technology has already given us lots of superpowers: we can fly (in planes and helicopters and flight simulators), we can see and hear things that are happening thousands of miles away in real-time (Periscope and other live-streaming tools), we can be in multiple places at once (telepresence and VR tech like Oculus Rift), we can control things with our thoughts (Emotiv, MUSE, MindWave, etc.), we can remember thousands of names and numbers (any mobile phone)… I suppose for me it’s more about how we apply technology than what it’s capable of. The same technologies that enable us to do all this magical stuff could also be used in some rather dark and dystopian ways. So I’m more interested in the how than in the what.

I would really, really like a teleporter though.

Which of the other talks at Data Natives are you looking forward to checking out?

Alex’s of course, and Suzy Moat’s talk looks interesting. I’m also curious as to what Dr. Belusa will have to say on nanotechnology and health.

Which companies individuals inspire you, and keep you motivated to achieve great things?

How much time have you got? It’s a long list. But to name a few: my partner and collaborators in Superhuman: Ayman, Alex and Simon. My brilliant hacker/artist friends like Shardcore and Henry Cooke. My family and friends outside the tech world, who challenge me and call me on my bullsh*t, and who also happen to be the people we’re actually making all this stuff for – especially my godchildren, who will have to deal with the consequences. All the people I know who’ve sacrificed personal comfort – physical or mental – to do important and meaningful things. People who are unafraid to try something new, take a risk, speak their mind. My favourite poet, e.e. cummings, my favourite physicist, Niels Bohr, my favourite anthropologist, Joseph Campbell, and many many more. I tend to be inspired by people rather than companies. It’s people who make the companies go anyway, right?

(image credit: GX Software)

To see the first four rounds of conference speakers we announced, check the Data Natives 2015 website!

Data Natives, a first-of-its-kind conference for the data-driven generation, is set to bring together the brightest minds in data science and related technologies for a 2-day event in Berlin November 19-20.

What’s on the agenda

Data Natives features a packed agenda designed for those looking to push the boundaries of their ideas and work in data science and beyond. With 40+ industry talks and unlimited networking opportunities, the conference aims to break down barriers in the industry and forge lasting relationships among its participants. Talks will focus on three buzzing areas of data science – Machine Learning, Internet of Things and FinTech.

The conference will also host a Startup Battle, showcasing some of the most exciting companies poised to do big things in big data. Young startups will have the chance to pitch to influencers and investors in the tech community and compete for the prize of Best Big Data Startup in 2015.

Confirmed Speakers

Louisa Heinrich, Founder at Superhuman

Louisa is all about making connections for humans – with other people, with content, with products, services, brands and businesses. She believes that enabling and empowering people to do the things they need and love to do is the only way to achieve sustainable success. Her company, Superhuman Limited, works with businesses and governments to design strategies, products, services and organisational structures that use digital technology to improve individual lives, make a positive contribution to society, and achieve commercial results. She has been working in the consumer-facing digital world more or less as long as there’s been such a thing. She’s held many titles over the past 20 years, including Design Director in the first dotcom boom, Executive for Future Platforms at the BBC, and Head of Strategy for international Service Design agency Fjord.

Suzy Moat, Assistant Professor of Behavioural Science at Warwick Business School

Suzy Moat is an Associate Professor of Behavioural Science at Warwick Business School, where she co-directs the Data Science Lab. Her research investigates whether data on our usage of the Internet, from sources such as Google, Wikipedia and Flickr, can help us measure and even predict human behaviour in the real world. Moat’s work touches on problems as diverse as anticipating stock market moves (with Preis, Curme, Stanley, et al.), estimating crowd sizes (with Botta and Preis) and evaluating whether the beauty of the environment we live in affects our health (with Seresinhe and Preis). The results of her research have been featured by television, radio and press worldwide, by outlets such as CNN, BBC, The Guardian, Wall Street Journal, New Scientist and Wired. Moat studied Computer Science at UCL, where she was awarded the Faculty of Engineering Medal, and received a PhD in Psychology from the University of Edinburgh. With her collaborator and Data Science Lab co-director Tobias Preis, she recently led an online course on using big data to measure and predict human behaviour which attracted over 15,000 learners. Suzy has also acted as an advisor to government and public bodies on the predictive capabilities of big data.

Matthias Korn, Technical Consultant at datavirtuality

Matthias Korn, Technical Consultant at datavirtuality. His talk, “Beyond the Data Lake” will talk about the shift in digital era, which harnesses large amounts of data to make astute business decisions and improve operations, which is now an imperative. While our ability to generate data still far outstrips our ability to analyze it, we are making strides. Exciting new approaches are merging big data solutions with traditional enterprise data strategies. Logical data warehouses, in which there is no single data repository, hold enormous promise. By offering an ecosystem of multiple best-fit repositories, technologies, and tools, business can effectively analyze data for powerful insight.

Duena Blomstrom, FinTech & Innovation Consultant

Duena is an independent Digital Banking consultant, FinTech specialist, an entrepreneur and an Angel Investor, a mentor for Startupbootcamp and Techstars, a blogger with cutting edge opinion style, a public speakers at industry events, the inventor of the EX concept and for the past 18 years has been in the the Telco and the Finance world on the strategy and consulting side, be it for sales or marketing. Most recently, Duena has been the Head of Sales and Marketing for Meniga from when it was a tiny Icelandic start-up to winning Finovate 3 times and becoming market leader in customer engagement in finance and have therefore “seen it all” in digital. With a background in Psychology as well as Business, Duena is on a crusade to teach the industry that Big-4-wooden-language will get us nowhere; she is passionate about getting FIs to think of the concept of “Emotional Banking” or how to stop thinking feature set and start thinking customer’s feelings; and she is interested in all things at the intersection of technology, innovation and behavioural science.

Interested in sponsoring opportunities? Please get in touch at info@datanatives.io

Are you game for the Big Data event of the year? Mark your calendars now, and snag your tickets here!

• An Introduction to Lean Analytics – Presented by Alistair Croll, Founder at Solve For Interesting, Author of Lean Analytics

• Python for Financial Data Science – Presented by Dr Yves J Hilpisch, Founder of The Python Quants

In addition to his work with The unbelievable Machine Company, Klaas Bollhöffer is father of the Data Science Day (DSDay), coordinator of the Big Data Week 2013 in Berlin, and member of several program committees for Big Data / Data Science conferences in Europe.

We are proud to have Klaas presenting at Data Natives 2015!

You come from a background of project management and user experience design, how did that lead you to working with data?

In 2011, Ravin Mehta, founder and CEO of The unbelievable Machine Company (*um) approached me and asked: “Klaas, do you wanna initiate and develop Big Data at *um?”. Honestly, at that time I didn´t know anything about Big Data and said “Ravin, what exactly is Big Data?”. He replied: “Well, I am sure nobody really knows!”. And I was hooked!!

I am engineer by studies, a creative guy by heart and at that time a manager and concept designer by profession. For me, especially looking back today, the ideal fit to create a new business, new service offerings in probably any IT-related field or industry. But especially in the groundbreaking field of data. Of course I studied computer sciences and mathematics but I have never been a fantastic coder or machine learner. I am an allrounder and bridge business requirements to data and back. Exactly what a concept or UX designer is actually doing. 😉

When did you first recognize that working with data was your passion?

To be honest here, working with data is not my passion. Music is, creating ideas and new solutions is, managing change and cultivating digital pieces of land is. I see myself as a learner, a teacher, a communicator, an initiator and as a kind of “dog fly” when it comes to really getting data projects done.

What kind of problems do you tackle at The unbelievable Machine Company?

All sorts of. We don´t have a special industry or technology focus. A lot of problems we tackle are machine learning (even deep learning) or operational intelligence issues. But we also deal with search engines, optimize human-data-interfaces by creating visualisations or business dashboards, develop custom machine-learning as a service solutions in our *umCloud infrastructure, do trainings, design thinking workshops and C-level one on ones or – at the moment – focus a lot on the industrial internet and automization.

Of all the projects you’ve been a part of, do any stick in your mind as being particularly challenging or taking exceptional creativity to solve?

Dealing with deep learning techniques is of course really challenging (and fun) at the moment, and working on first projects this year for an international client of ours was not always that easy. We did 2 steps, 1 step back, 2 steps, 1 step back for quite a long time and failed quite often talking e.g. about quality metrics… but in the end we came out with a really groundbreaking application for our client (strong NDAs here, sorry…) and learned an awesome lot in applying deep learning to different real world problems.

What have been the major turning points in your progress as a data scientist? Any particularly valuable lessons or epiphanies along the way?

Good question and difficult to answer as I have the feeling that I am always changing in my day to day business. By far the most relevant turning point was as we saw that data science as a service was working and was generating sustainable business. That happened roundabout middle of 2014. My team started growing (from 3 in the middle of 2014 to 15 at the moment, constantly growing). The projects got bigger and more and more interesting. Machine learning was (at least a bit) more and more understood and in demand and we successfully started new teams in data engineering, consulting and operations. Pretty amazing year actually. The most valuable lesson for me was: “If you really believe in something, it will happen!”. It might take more time than you expect, but if you go on, work hard, be creative and open to change and have a – let´s call it – data (or digital) mindset you are able to become an enabler and a person others trust. We entered a spaceship some time ago and so far it didn´t even start. 2016 will be really amazing and crazy, trust me.

[bctt tweet=”‘If you really believe in something, it will happen!’ – @klabol”]

What advice would you give to young professionals looking to find their feet in data science or related disciplines?

Start today! Do not do a master or PhD for a few years (you can do later if you really feel you need it), go to meetups and other community events, talk to data scientists and people in the field, do a coursera course or become part of e.g. Data Science Retreat, learn, play and fail in Kaggle competitions and so on and so on. Just do it! And do it yourself! DIY – the old punk attitude is what´s needed. Add a few months, a few good people you’ll meet and you can start doing data science in an interesting field and company very, very soon!

[bctt tweet=”The old punk attitude is what´s needed. – @klabol”]

Which companies individuals inspire you, and keep you motivated to achieve great things?

I am a musician by heart and get inspired by great artists, writers and musicians. Lemmy, Turbostaat, Thomas Bernhard, Wittgenstein, Banksy, you name it! But most of my motivation is intrinsic and just a part of me. I am a natural born curiosity-seeker.

(image credit: Francisco Huguenin Uhlfelder , CC2.0)

Dr. Kirk Borne is a data scientist and an astrophysicist. He is Principal Data Scientist in the Strategic Innovation Group at Booz-Allen Hamilton since 2015. He was Professor of Astrophysics and Computational Science in the George Mason University (GMU) School of Physics, Astronomy, and Computational Sciences during 2003-2015. He served as undergraduate advisor for the GMU Data Science program and graduate advisor to students in the Computational Science and Informatics PhD program. Prior to that, he spent nearly 20 years supporting NASA projects, including NASA’s Hubble Space Telescope as Data Archive Project Scientist, NASA’s Astronomy Data Center, and NASA’s Space Science Data Operations Office. He has extensive experience in large scientific databases and information systems, including expertise in scientific data mining. He was a contributor to the design and development of the new Large Synoptic Survey Telescope (LSST), for which he contributed in the areas of science data management, informatics and statistical science research, galaxies research, and education and public outreach.

We are proud to have Kirk presenting at Data Natives 2015!

How did you make the jump from astronomy to data science?

The jump was a gradual one (a lifelong evolution) for me. As an astronomer, I was always working with data from telescopes of all sizes. My experience with these various scientific instruments and observatories in different parts of the world (including telescopes in the USA, in Chile, and at the German-Spanish Calar Alto Observatory in Spain) led me to work as a research scientist for the Hubble Space Telescope in the 1980’s. My service work at the Space Telescope Science Institute included database design, development and report generation, which ultimately led to my appointment as NASA’s Hubble Data Archive Project Scientist. We created one of the world’s first major public (open) data repositories for scientific researchers: open access, user-friendly search, web-based interfaces, and more.

This work eventually opened up new opportunities for me at NASA, and I became a contract manager in 1995 for NASA’s Astrophysics Data Facility and Astronomy Data Center, within the USA’s National Space Science Data Center (NSSDC). As I worked with data more and more in my daily professional life, developing better tools for management, indexing, search, access, analysis, visualization, and discovery, it was inevitable that a transition in my research and professional interests would migrate toward data science.

Can you describe the journey that led to where you are today, and your major influences along the way?

When I was at the NSSDC in the 1990’s, we catalogued, archived, curated, and provided access to over 15,000 space science datasets from many thousands of space instruments. It was during this period that I began to notice a dramatic increase in the size of the datasets that we were ingesting. The biggest jump occurred in 1998 when we were asked to ingest one single experiment’s data, whose total volume of 2 Terabytes more than doubled the total data volume (1 Terabyte) of the other 15,000 datasets combined! It was then that I realized that things were dramatically changing in the expanding “data universe”. I began to explore the power of data mining and machine learning to make discoveries in massive data – I was fascinated with finding the “unknown unknowns” in large data collections. I was influenced greatly by several groups, including: (1) the work at IBM (on the Advanced Scout project that mined the play-by-play databases for professional basketball games); (2) the customer-based data mining and marketing efforts at Capital One Credit Card Company (which was described in a business magazine that I found in the office snack room one day); and (3) and Usama Fayyad (who was working at NASA’s Jet Propulsion Lab with astronomers to mine large galaxy databases). That was the conspiracy of events and inspirational persons that influenced me the most at the beginning of my transition from traditional astronomical research (studying colliding and merging galaxies) to multidisciplinary data-driven research in numerous disciplines, organizations, and industries. Those influences led me to data science and into becoming the data scientist that I am today.

The full transformation for me occurred in 2003 when I left NASA (after 18 years) to become a faculty member at George Mason University in the Computational Science and Informatics (Data Science) PhD program. Ultimately, my colleagues and I launched the world’s first undergraduate Data Science degree program in 2007. The world was taking note of big data and data science, and we were right there in the middle of it. After teaching, advising, and doing research in data science at the academic level for 12 years, I was hungry to do more, in a broader context, for more organizations, in a variety of industries where data analytics is changing the world. When Booz Allen Hamilton offered me that opportunity as their Principal Data Scientist in the NextGen Analytics and Data Science group (consisting of more than 500 data scientists), I left the university and joined this remarkable team in May 2015.

What major milestones or landmark events have stood out to you during your time in the industry? What are you still waiting for?

The first milestone goes back over 30 years when professional organizations and societies formed initiatives around data mining and knowledge discovery from data. The creation of the kdnuggets newsletter by Gregory Piatetsky-Shapiro in 1993 was a definite landmark event in the history of data science. The birth of Google is another big one – they set out to do more than be a search engine company, but to organize all of the world’s information and to make it universally accessible and useful, which they accomplish with some amazing mathematics (linear algebra, the one university class that I took 40 years ago that is now on the top of my recommendations when new students ask me how to get into data science). Then there was a series of events that brought out the importance of data mining (and data science): the terror attacks in the USA on September 11, 2001; the Washington DC sniper case of 2002; and the now-famous Walmart strawberry pop-tarts data mining story of 2004. Those isolated incidents were not isolated in my mind or in the minds of data scientists – the power of data to know the world, to improve the world, and to change the world was increasingly more visible to everyone.

[bctt tweet=”‘The power of #data to know the world, to improve the world’ – @KirkDBorne”]

Then, in 2011-2012, there were three landmark events that changed everything for us: (a) the publication of the McKinsey research report “Big data: The next frontier for innovation, competition, and productivity” in 2011 emphasized the dramatic shortage in data professionals that the workforce would be facing within the next few years; (b) the President of the USA announced the National Big Data Initiative (including several hundred million dollars of research investments); and (c) the publication of an article in the prestigious Harvard Business Review with the title “Data Scientist: The Sexiest Job of the 21st Century.” From my perspective, those three events launched the Data Science revolution that we are now experiencing. The next big changes will include the internet of things (with ubiquitous sensors everywhere, collecting massive streams of data on everything, all the time), also faster analytics (in-memory, on-the-chip, cleverer algorithms, machine learning on clusters and in the cloud, quantum machine learning, and more), and greater conversion of all businesses into data businesses.

In the 30 years since you joined the Space Telescope Science Institute what have been the most significant challenges you have faced?

One of the biggest challenges that everyone has faced in this field is cultural inertia, specifically resistance to change. Whether we look at academic institutions, government agencies, or commercial businesses, there have been a lot of folks who criticized, minimized, or otherwise ignored the revolution that was growing around them. Trying to get organizations, industries, or professions to change requires years of patience, persistence, and perspiration. Those of us who lived through those challenges are seeing the fruits of our labors now, in fact it is not just fruits but entire forests of opportunities! I learned through the years that the best way to bring about big changes fast is to go right to the top – so I was lead author on two position papers in 2009 that were submitted to the USA’s National Research Council of the National Academies of Science. One paper was focused on the transformation of my field (Astronomy) into a data-oriented data science research discipline (Astroinformatics), and the second paper was focused on changing the education system (not just in astronomy, but in all aspects of school-based learning and lifelong learning) by incorporating “Data Science for the Masses” everywhere in all learning settings. Those papers got noticed by significant persons, and the transformations are now well underway.

[bctt tweet=”One of the biggest challenges that everyone has faced in this field is cultural inertia.”]

The challenges that we previously faced have not completely evaporated, but there is hope that they are fading. We are seeing now the resistance is not so much from the leadership within organizations, but from the mid-level workforce – they haven’t entirely embraced the changes that a data-driven business requires, but they are moving in the right direction. The leaders of organizations are now encouraging, sponsoring, and rewarding such transformations in people, processes, and products. That is exactly what my company Booz Allen Hamilton is doing, and it is a wonderful thing to be part of.

Of your achievements and accolades so far, of which are you most proud?

That is a tough question, but I presume that you are not referring to my wonderful family, children, and grandchildren. I am most proud of my humility. (Hint: that was a small joke.) Seriously, I am humbled by the opportunities, talents, and aptitudes that I have been given. So, when I say that “I am proud of…”, what I really mean to say is that “I am humbled by…”. So, here we go… I am proud that I survived a very tough undergraduate education in Physics. I am proud that I completed my doctoral degree in one of the world’s top astronomy programs (Caltech). I am proud of the awards that I won for my work on the Hubble Space Telescope project. I am proud of the innovations that my group at the NSSDC created around the use and exploration of large datasets. I am proud of co-creating the world’s first undergraduate Data Science degree program. I am proud of my PhD students who have produced some incredible doctoral dissertations. I am proud of the Faculty Impact Award that I received from the Dean of George Mason University’s College of Science. I am proud to be among the worldwide top influencers in big data and data science. I am proud to be a member of the awesome Booz Allen Hamilton data science team. And I am proud to be a part of the Data Natives community of data-driven world-changing innovators. (As you can see, I have a lot to be grateful for – hence the humility!)

What kind of problems are you aiming to tackle in your role at Booz Allen Hamilton?

I get great pleasure in finding solutions through data. The scientist in me loves to explore data (evidence), find new discoveries, develop a hypothesis to explain it, and then test those theories. At Booz Allen Hamilton I am privileged to exercise that Data Scientist role across numerous internal and external projects: human resources, organizational change, training and mentoring, marketing, customer engagement, behavior analytics, risk mitigation, novelty discovery (including fraud detection, anomaly detection, surprise discovery), thought leadership, socialization of data science across organizations and industries, data technologies (including machine learning, data management innovations, graph analytics), predictive and prescriptive analytics, geospatial-temporal modeling, and much more. I feel like a child in a candy store most of the time, and I have to exercise some good judgement as to where to get involved. It is tempting to get involved in too many things.

What advice would you give to the Kirk Borne of 30 years ago? Anything you would have done differently?

I wrote a blog for MapR about my “growth hacker’s journey”. My message throughout that self-history was that I was often in the right place at the right time. I usually didn’t recognize that reality when I was experiencing each of those career moments. It took many years of hindsight to see the growth trajectory, how it was born, and how it took shape. So, I guess I wouldn’t have done things too differently (maybe on the micro level, but definitely not on the macro level). I would tell myself of 30 years ago the same things that I would tell a young person today at the start of their career:

(1) Don’t over-plan (over-specify) your career, since it will evolve in unexpected ways.
(2) Expect to find the essential value and meaning of your work later in life for the things that you are doing now, and that’s okay.
(3) Be ready to make big changes when the opportunities present themselves (just as I left the great Hubble Space Telescope project to pursue bigger opportunities, then I left NASA after 18 years to create a new academic discipline, and then I left a tenured Full Professorship in an innovative university in order to join a brilliant revolutionary business).
(4) Trust your training – I am amazed at how all sorts of things that I learned and experienced have become relevant and useful at different stages of my life.
(5) Be more tolerant of your own mistakes – remember this saying: “Good judgement comes from experience, and experience comes from bad judgement.”
(6) Listen to, but don’t react to the naysayers – do what you know is the right thing for you.
(7) Your aptitudes will be more valuable to you in the long term than your skills (aptitudes include the 7 C’s: cool under the pressure of hard work, courageous problem-solver, curious, creative, communicative, collaborative, and commitment to lifelong learning).
(8) And finally, don’t confuse your job with your career – I had many jobs, but I have had only one career: being a scientist who loves to make discoveries from data. When your lifelong passion becomes your career, hold on to that very tightly.

Which companies or individuals inspire you, and keep you motivated to achieve great things?

Of course, I have to mention my current employer Booz Allen Hamilton, which is making all of the right moves in the area of data analytics and data science. I also am inspired by the top big data and data science influencers – some of them are younger than my own children, and that excites me to see that the next generation is embracing the power of data to transform the world. I am inspired by organizations who apply data for social good, which includes Booz Allen, DataKind, Bayes Impact, Kaggle, and many others. I am motivated by the awesome and fast accomplishments, discoveries, and innovations that are occurring all around us in the data analytics world: in government, businesses, and academia. I have shared the stories of so many of those companies and organizations on Twitter, I cannot begin to keep count of how many — though maybe my 44,000 tweets are a good estimate of the number of data stories that have been worth sharing with the data science social community. Those are the people (my faithful and fearless followers who track my Twitter firehose of data stories) who are definitely the individuals who keep me motivated! The flood of new and interesting data sources everyday motivates all of us data natives to achieve great things, because “Data is what we do”. This is a great time to be doing data!

[bctt tweet=”‘This is a great time to be doing #data!’ – @KirkDBorne”]

(image credit: Evan Bench, CC2.0)

Data Natives is coming soon! The conference focuses on three key areas of innovation: Big Data, IoT and FinTech. The intersection of these fields is home to the most exciting technology innovation happening today.

Whether it’s for individual consumers or multi-billion dollar industries, the opportunity is immense. Come and learn more from leading scientists, founders, analysts, investors and economists.

Early bird tickets are still available – don’t miss out on a great opportunity for yourself, your colleagues or your employees! If you need a little more convincing:

Data Natives has 7 Key Goals

We will leave you:

1 – Inspired for the future

Data Natives focuses on real-world applications of cutting edge technology to paint an exciting picture of the future. We aim to help attendees understand either the potential impact of the technology they are creating as technical professionals, or the scale of the opportunity that technology is providing for the rest of us.

When technological advancements are shaping the way we work in fundamental ways, it’s important to stay inspired, optimistic, and open-minded about finding more effective ways to operate.

2 – Empowered to seek business opportunities

This conference is a chance to look at some of the most innovative applications of technology, and the business value they have unlocked. Whether it’s hearing how an industry giant leveraged data to increase their margins, or how a scrappy startup is using connected devices to offer something revolutionary – you will leave the conference looking at problems in new ways, inspired to solve problems that previously you were resigned to simply coping with.

There will be plenty of opportunities to network with companies offering – or looking for – innovative solutions, or experts who could help add value to your business.

3 – Encouraged to be data-driven

As more and more data is available to us, an analytical mindset is a more and more valuable mindset. Whether you’re in marketing, HR, product design, project management or a technical field, chances are you work with data every day. Learning to ask the right questions and how to interpret data correctly is key to success.

By looking at how industry leading companies are using data in all aspects of their business, you will come away from Data Natives with a clear picture of how your companies processes may be improved. There will also be a workshop available from Alistair Croll on Lean Analytics.

4 – Learning from other industries

It is easy to exist within a bubble, networking and knowledge sharing within your own industry, when an exciting and crucial development may be happing in an adjacent industry. Don’t miss the chance to broaden your mind.

Our speakers will describe the transformation of major verticals, as well as the horizontal applications of data-driven technology. Whether your background is advertising, e-commerce, finance, transportation… There are valuable lessons to be learned from how other industries are finding value in their data, utilizing connected devices, or managing their finances.

5 – Experienced with hands-on workshops and expert guidance

In additional to a packed schedule of insightful talks from 50 guest speakers, we will also be hosting four workshop sessions with experts, covering key areas of interest and giving our audience a chance to get hands-on with the subjects that matter to you.

See the full schedule for details on those workshops as they are announced!

6 – Enjoying the ultimate curation of data driven content

The schedule of Data Natives has not been pulled out of thin-air – it comes from the lessons learned from >1,800 articles, and >100 past presentations at our events all over Europe.

Not just a standard, boring industry conference, it is a curation of the most valuable and interesting content we have found over the last two years. Many of our speakers come from long standing relationships and past collaborations, with talks that have been applied and refined over multiple events.

7 – Absorbing diverse input and fresh perspectives

This is not a conference to come and hear the same talking heads saying the same things you’ve been reading about online for months already.

We are hosting talks from data scientists, investors, analysts, consultants, academics and economists. It is our aim to provide a complete view of the technology innovations and opportunities. Inspiring, informative and accessible. Most of all, useful.

See the schedule (so far) and get your tickets here:
datanatives.io

(image credit: Christian Scholz, CC2.0)

With six top IT events under one roof, 300+ exhibitors and 300+ free seminar sessions, IP EXPO Europe is a must-attend IT event for CIOs, heads of IT, security specialists, heads of insight and tech experts. The event will take place on 7-8 October 2015, at ExCel, London.

The event showcases brand new exclusive content and senior level insights from across the industry, as well as unveiling the latest developments in IT. IP EXPO Europe now incorporates Cloud and Infrastructure Europe,Cyber Security Europe, Data Centre Europe, Data Analytics Europe, DevOps Europe and Unified Communications Europe.

As part of this outstanding event, Dataconomy will be hosting its fifth edition of Data Natives on the 7th of October, from 5PM until 8PM. It will be an evening of exciting talks from Data Science industry leaders, followed by enough time for beers, food and networking.

The first presenter is John Easton, IBM Distinguished Engineer, Lead Cloud Advisor for the United Kingdom, Ireland & Nordics, IBM Cloud Member and IBM Academy of Technology. His talk, ‘’Why Infrastructure matters for Big Data and Analytics’’ will look at how different analytical approaches can have very different platform requirements, showing attendees why their choice of infrastructure really matters for big data and analytics. By understanding that different analytical problems have very different infrastructure needs to deliver real business value, organisations can set themselves up better by building a solid analytical infrastructure that is fit to meet any challenge that this rapidly changing space can throw at them.

John is internationally known for his work helping commercial clients exploit large scale distributed computing infrastructures, particularly those utilising new and emerging technologies. He has worked with clients in a wide range of industries with a particular focus on banks and financial markets firms. He also has significant experience in the telecommunications sector. Previous to his current role, John led a pan-European team building infrastructures to support big data and advanced analytical workloads. During his time at IBM, John has led initiatives around hybrid systems, computational acceleration, grid computing, energy efficiency and mission-critical systems.

The second presenter is Rick Farnell, SVP and Co-Founder of Think Big, a Teradata Company. His talk, ‘’Big Data 2015: What we’ve learned in 5 years’’ will discuss how Think Big, a pioneer in big data services with Hadoop, is helping a global organization utilize multi-petabyte Hadoop clusters to drive tangible business results. Highlights in this presentation will include how this company is using best practices for data ingestion across multiple manufacturing facilities in Asia and the US, utilizing robust patterns for handling data quality, metadata management, pipelining, buffering, and security to establish Hadoop as an enterprise data lake. Working with more than 100 clients on Hadoop projects, Think Big, a Teradata Company, will describe other enterprise design patterns and successful organizational models used by their clients, and how to avoid the pitfalls associated with designing, managing, and scaling your enterprise data lake.

As Co-Founder and President of Think Big, Rick brings 20 years of management experience in scaling technology consulting organizations in North America, EMEA and APAC and is responsible for Think Big’s sales and services business. Previously, Rick directed a global division within Sun Microsystems and in 2009, he led Sun’s cloud open source software go to market strategy with Amazon Web Services.

The third presenter is Matthias Korn, Technical Consultant at datavirtuality. His talk, ‘’Beyond the Data Lake’’ will talk about the shift in digital era, which harnesses large amounts of data to make astute business decisions and improve operations, which is now an imperative. While our ability to generate data still far outstrips our ability to analyze it, we are making strides. Exciting new approaches are merging big data solutions with traditional enterprise data strategies. Logical data warehouses, in which there is no single data repository, hold enormous promise. By offering an ecosystem of multiple best-fit repositories, technologies, and tools, business can effectively analyze data for powerful insight.

datavirtuality enables companies to instantly connect internal and external data sources. The solution revolutionizes the technological concept of data virtualization and data integration and builds an enterprise wide database from relational and nonrelational data sources within a few hours. With 100+ connectors, the data can be processed immediately in analysis, planning and statistics solutions and also written back whenever needed in the source systems. The self-learning database automatically adapts to changes in the IT environment and user behavior. By using datavirtuality, companies achieve maximum flexibility and speed with data integration with a minimal administrative effort.

Finally, the fourth presenter is Francisco Webber, Inventor and Co-Founder of Cortical.io, whose talk is going to be about “Spark Implementation Facing Big Text Data”. Cortical.io’s approach is inspired by the latest findings on the way the human cortex works. Their technology, the Semantic Folding Engine, breaks with traditional methods based on pure word count statistics or linguistic rule engines. Its central component, the Cortical.io Retina, converts text data into a Semantic Fingerprint, that contains all associated contexts. The system “understands” the relatedness of two items by measuring the overlap of their fingerprints. Because of their small size, Cortial.io’s fingerprints require a fraction of the computing power normally required to perform complex NLP operations. As a result, the Cortical.io Retina is very fast, reliable and easy to implement – a breakthrough technology that leverages the intelligence of the brain to enable the Natural Language Processing of Big Text Data.

We are looking forward to seeing you at Data Natives, London, on the 7th of October, at 5PM! Don’t forget to register on the IP EXPO website (http://www.ipexpo.co.uk/) until the 6th of October, at 7PM, in order to have free access to our meetup!

More info About Data Natives, London here:

http://www.meetup.com/Data-Natives-London/events/225069543/

Named #2 in the Top 100 Internet of Things Thought Leaders, Alexandra Deschamps-Sonsino brings a wealth of experience in building consumer-facing internet of things products, such as the Good Night Lamp and helping clients such as BBC R&D, Nokia, British Gas, EDF and British Telecom. She’s altogether an interaction & product designer, entrepreneur, speaker & curator focused on the limitless potential of IoT.

What makes you a ‘data native’?

Well I manage 21 Twitter accounts, so that’s got to count for something 🙂

Can you describe the journey that led to where you are today, and how your interest in IoT developed?

I’m an unlikely data native I think as I studied industrial design a pretty data-free field in the early 2000s. I went on to do a masters degree in interaction design where my peers were developers, computer scientists and UX people. That’s when my understanding and approach to the web developed. I understood through learning HMTL, CSS and PHP what my peers needed to hear when I wanted to make a web-enabled physical product. I started Tinker (tinkerlondon.com) (the first UK distributor of the Arduino) in London in 2007 and that was the beginning of getting involved in growing a maker movement in the UK around that tool. We worked with some fantastic clients who were also interested in understanding how those types of tools could help them experiment inside their business.

When I closed the studio in late 2010 I went back to consulting and work now more on a strategic basis with clients. I started curating the London Internet of Things meetup in 2011 for Pachube and it’s now the largest global community dedicated to the topic (6K+ members now). Over the last 3 years, I have developed the Good Night Lamp (goodnightlamp.com) a connected product for global families. This is an idea I came up with in 2005 during my masters degree. I work with a wood fabrication studio in London (Tom Cecil studio) and an M2M company outside of London (Eseye) to deliver the product to people all over the world.

What major technology milestones have stood out to you during your time in the industry?

I don’t think there have been any radically new technologies that have evolved recently (although LoRaWAN networks sound interesting but still tricky) but the audience for existing technologies have changed and the application space has changed too. Mobile phones have a lot to answer for when it comes to the development of the internet of things and you could argue that it’s slowed down the pace of development of some ideas because it’s easier to make an app than to develop a product. But product still have a big role in the lives of consumers otherwise we’d all be living in empty white boxes. The price of hardware components has dropped and there is enough information online to allow pretty much anyone to experiment with a on off prototype of a physical device that does something interesting to them.

[bctt tweet=”‘Mobile phones have a lot to answer for’ – @iotwatch #IoT”]

Crowd-funding means that you also don’t have to be subject to a very conservative investment landscape but can find and sell to a market more easily. These are all subtle changes in who has had access to particular technologies, not new in themselves.

What are you waiting (or hoping) for to happen next in terms of technology development for IoT?

I think I’d like to see more stable connectivity offerings from the M2M sector as they learn how to collaborate with whitespace offerings. We’ve struggled a lot with the Good Night Lamp to find global coverage. In Canada for example, I can’t send my parents a set of lamps because the 2G coverage is poor there. Connecting things is still quite tricky when you don’t have local wifi to rely on.

Of the projects you’ve worked on at Designswarm so far, of which are you most proud?

I still love Homesense – a bottom-up smart home project we ran at Tinker in 2009. We gave 6 households across Europe a toolkit that was Arduino based and matched them with a local developer. Each home developed their own application based on their own needs and the report is still online. The kit ended up in the New York Museum of Modern Art as part of their permanent collection. The whole project was built under creative commons as we wanted to treat is as open research. I still think the level of discourse around smart homes needs more reality and appreciation of the granularity of everyone’s home.

Are there any industries or sectors you see as ripe for IoT applications, or projects you would particularly love to tackle?

I’m currently working with Wintec Innovate, a research institute in New Zealand and they’re interested in technology-led rural innovation. I think there’s a lot to do away from cities in helping people connect to jobs, healthcare services and the source of their food, i.e. agriculture.

What connected devices do you use on a day-to-day basis, and why?

I have a Hive Home, a connected thermostat. It’s great as I can turn the heating on in my apartment 20 minutes before I get there and come home to a warm house!

Which companies individuals inspire you, and keep you motivated to achieve great things?

Even if they are now closed, the work of my friends at Berg was sensational. They really explored what physical interactions within a digital landscape meant and their work continues to inspire me.

Data Natives focuses on three key areas of innovation: Big Data, IoTand FinTech. The intersection of these fields is home to some of the most significant innovation happening today.

Come and learn more from leading scientists, founders, analysts, investors and economists. Whether you’re from a technical background or not, you will come away with a better understanding of the industry trends, technology driven opportunities and revolutionary business ideas.

Want 33% off your Data Natives ticket?
There’s only a few days left! 

Click here to read more and book your ticket! 

We’ve also added a student ticket at half price – just make sure to bring a student ID on the day!

To see the first three rounds of conference speakers we announced, check the Data Natives 2015 website!

Data Natives, a first-of-its-kind conference for the data-driven generation, is set to bring together the brightest minds in data science and related technologies for a 2-day event in Berlin November 19-20.

What’s on the agenda

Data Natives features a packed agenda designed for those looking to push the boundaries of their ideas and work in data science and beyond. With 40+ industry talks and unlimited networking opportunities, the conference aims to break down barriers in the industry and forge lasting relationships among its participants. Talks will focus on three buzzing areas of data science – Machine Learning, Internet of Things and FinTech.

The conference will also host a Startup Battle, showcasing some of the most exciting companies poised to do big things in big data. Young startups will have the chance to pitch to influencers and investors in the tech community and compete for the prize of Best Big Data Startup in 2015.

Confirmed Speakers

Christian Rebernik, CTO at Number26 GmbH

Christian was born in Vienna, Austria and studied economics and informatics in Vienna. Before he joined NUMBER26 in the position of CTO, he founded his own company and worked as a CTO for Zanox, Parship and Immobilien.net. On top of this Christian acts as a Mentor and Coach to several startups during their founding phase and he consulted the United Nations World Food Programme in the creation of the Share the Meal app.

Rick Farnell, Co-Founder and SVP International of Think Big

As co-founder of Think Big, Rick brings 20 years experience in scaling global services organizations. He’s responsible for Think Big’s international business. Previously Rick directed a global division within Sun Microsystems. In 2009 he led Sun’s open source software go-to-market strategy with Amazon Web Services. On Sun’s leadership team, Rick helped integrate the acquisitions of SeeBeyond and mySQL. In the 90’s Rick was the first senior hire into C-Bridge, where helped develop their RAPID consulting methodology. His leadership helped scale C-bridge to over 900 consultants in three years and to a successful IPO in 1999.

Dr. Ralf Belusa, Senior Director Innovation at zanox

Dr. Ralf Belusa learned writing code at the age of 6, and started his first company at the age of 16. Ralf studied recently a year astrophysics, wrote his doctoral thesis on human cell research, master and diploma thesis in nanotechnologies and system theory and acts as a mentor and investor at Microsoft Ventures. The Wirtschaftswoche awarded the zanox Manager and startup founder as of the 100 most important Digital Managers of Germany and Europe.

Tugdual Grall, Tech Evangelist at MapR

Tugdual Grall is a Technical Evangelist at MapR, an open source advocate and a passionate developer. He currently works with the European developer communities to ease MapR, Hadoop and NoSQL adoption.

Before joining MapR, Tug was Technical Evangelist at MongoDB and Couchbase.  Tug has also worked as CTO at eXo Plaform and JavaEE product manager, and software engineer at Oracle.
Tugdual is Co-Founder of the Nantes JUG (Java User Group) that holds since 2008 monthly meeting about Java ecosystem. Tugdual also writes a blog available at http://tgrall.github.io/

Interested in sponsoring opportunities? Please get in touch at info@datanatives.io

Are you game for the Big Data event of the year? Mark your calendars now, and snag your earlybird tickets here!

With 17 years of Financial Services experience under his belt in places such as London, New York, Tokyo, and Singapore, Nasir Zubairi has brought his own touch of innovation and value to numerous organizations and startups. His current role at FinLeap sees him advising and building the next generation of FinTech companies to ultimately change the face of the financial industry.

We are proud to have Nasir presenting at Data Natives 2015!

How did you make the jump from financial services to FinTech?

It was 2008. I was working in a bank. I recognised that I was not happy waking up in the morning, not happy at the prospect of another day in the office. I decided to make a change. I did not go straight into Fintech, I first went to business school – I was thirsting for new knowledge after a long drought.

Can you describe the journey that led to where you are today, and your major influences along the way?

Sorry to be non-descript, but all my experiences, all the people I have met, all the things I have done, personally and in business, have shaped my direction and brought me to this point. I like to learn something new and useful every day and have been blessed to be able to achieve that.

What major milestones or landmark events have stood out to you during your time in the industry? What are you still waiting for?

Very specifically – the Lehman Brothers bankruptcy and the takeover of ABN Amro by RBS. I think these two events seeded a major change in perspective about banking; not in a positive sense. The knock-on impacts – the credit crisis, regulatory reform, banker bashing, the “99%” movement…. are catalysts for the rise of “Fintech”. More focus on the sector led people to see the cracks in the services being offered and to be proactive in trying to do something about them.

What am I waiting for? I am waiting for the first bank to issue a mobile phone instead of a credit card. That will be game-changing. Right now it is more evolution rather than revolution.

[bctt tweet=”‘I am waiting for the first bank to issue a mobile phone instead of a credit card.’ – @naszub”]

What have been the most significant challenges you have faced while trying to drive innovation in the finance sector?

I set up my first venture in 2010. this was when the Fintech movement was really in its infancy. It was so hard to raise money. Investors did not think treading on the bank’s patch made for a wise business. What could a start-up do against the mighty goliaths in the Industry? Ha!

More broadly, the whole process of starting and building a business, though incredibly exciting, is hard work, especially the first time. No matter what you think you know about it, the reality is very different. Building your network requires a monumental effort – I used to be so exhausted at the end of the week from all the “selling” that I just didn’t want to talk at all over the weekend.

Of your achievements and accolades so far, of which are you most proud?

Being voted “Best Mentor” at the Awards for Enterprise in 2012. I was so happy to find out that I was useful!

What kind of problems are you aiming to tackle in your role at FinLeap?

The opportunities in Fintech are massive, we have barely scratched the surface. I would love to find a way to provide access to credit for the 2 billion people that are unbanked in the world. What a problem to solve.

What advice would you give to the Nasir Zubairi of 20 years ago? Anything you would have done differently?

No. I would not have learnt what I have learnt if I had not done things the way I have and I probably would not have known the alternatives and to advise myself differently. Vicious loop. The key is to try not to make the same mistakes again.

Which companies or individuals inspire you, and keep you motivated to achieve great things?

I am a great admirer of Warren Buffett and his pragmatic approach to investing and growth. Also Soichiro Honda; he took on the giants and won.

(image credit: CGP Grey)

To see the first round of conference speakers we announced, check here!

Data Natives, a first-of-its-kind conference for the data-driven generation, is set to bring together the brightest minds in data science and related technologies for a 2-day event in Berlin November 19-20.

What’s on the agenda

Data Natives features a packed agenda designed for those looking to push the boundaries of their ideas and work in data science and beyond. With 40+ industry talks and unlimited networking opportunities, the conference aims to break down barriers in the industry and forge lasting relationships among its participants. Talks will focus on three buzzing areas of data science – Machine Learning, Internet of Things and FinTech.

The conference will also host a Startup Battle, showcasing some of the most exciting companies poised to do big things in big data. Young startups will have the chance to pitch to influencers and investors in the tech community and compete for the prize of Best Big Data Startup in 2015.

Confirmed Speakers

Matteo Rizzi, Partner at SBT Venture Capital

Matteo has been actively engaged in the FinTech space for over 20 years and has deep connections amongst global banks executives, startups and investors. He knows how to bridge traditional banking with new or disruptive technologies, because he understands both.

Lars Trieloff, Director of Product Management at Blue Yonder

Lars Trieloff is the Director of Product Management at Blue Yonder Analytics. Before joining Blue Yonder, Lars Trieloff was responsible for product management at Adobe and Day Software. Lars has been a Apache Cocoon Committer and has worked as a developer at various organizations like SAP. Lars holds a MSc of Software Systems Engineering from Hasso Plattner Institute in Potsdam.

Klaas Bollhöfer, Chief Data Scienstist at The unbelievable Machine Company

In addition to his work with The unbelievable Machine Company, Klaas is father of the Data Science Day (DSDay), coordinator of the Big Data Week 2013 in Berlin, and member of several program committees for Big Data / Data Science conferences in Europe.

Kirk Borne, Principal Data Scientist at Booz Allen

Identified as #2 data mining influencer and top big data influencer (#1 in 2013 and #3 in 2015), Dr. Kirk Borne is an Astrophysicist and the new Principal Data Scientist for Booz Allen Hamilton’s NextGen Analytics and Data Science strategic innovation group. He previously was a Professor at George Mason University (2003-2015), serving as a data science teacher, researcher, and advisor. He has advised numerous agencies and businesses in the use of data for discovery, decision support, and innovation across many different industries.

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