Beyond the Spreadsheet

Hey there! Welcome to "Beyond the Spreadsheet"- a blog about learnings, inspiration and life as a student in the Master in Business Analytics & Big Data (MBD) program at IE Business school in Madrid.

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Invivo: A Startup in the making...

IE is well known for being one of the most entrepreneurial schools around Europe so as many other Master programs do, the MBD students were challenged to build our own data-driven business ideas, the Startup Challenge.

The competition was tough, startups that revolutionized talent acquisition, others improved the health of the user, others were thought to bring amazing discounts to its customers, others of course were focused in the B2B segment. All wonderful, creative and innovative ideas that dazzled the judges and the fellow scientists.

They all deserve a huge congratulations, and their efforts really make me proud to be part of this program and school, but there could only be one winner. Hereby I present to you Invivo! A Startup with an astonishing ambitious project. They aim to revolutionize the way health metrics are delivered to the user, through the use of “infrared spectroscopy”. Yes, you read that right. This new technology ideally would allow the user to follow his/her own health metrics such as blood pressure, body fat, oxygen levels, hydration levels, proteins and much more with a small bracelet wearable. But don’t let me bore with this and let Daniel Julien, MBD student and co-founder of Invivo do the talking.

Can you describe in just five lines what Invivo is?

Invivo is a project we started with the intention of creating a technology to help people make health-related decisions. Many of the products that exist today either don’t track useful metrics, fail at removing the friction involved in terms of data collection or don’t provide anything more meaningful than pretty graphs.

The goal of Invivo is to create a physical device that can automatically track important biochemical data in order to give people objective and personalized insights about their health. We’re going to do this with a wearable that can scan someone’s blood non-invasively (i.e. without penetrating the skin), and then feed the resulting data along with other sources of information into an AI-driven app on thephone or web browser.

How did you come up with this idea?

It was the combination of different frustrations about the way we make health-related decisions AND some ideas on how this decision-making process would look like in an ideal world. If you think about the highest level athletes in society, and the kind of personalized attention they get from world-class professionals when it comes to their physical well-being, it seems like the perfect thing to try to democratize. Most people can’t plausibly access even basic health professionals on a regular basis. In fact, we all just end up turning to the Internet or our friends to educate ourselves about our health. But for the average person, adequately self-educating yourself about your health requires a lot of time and effort. Just the sheer quantity of information available can be overwhelming. They may also run into, and accept, factually wrong information that is presented convincingly. And there’s also the issue that the best information that science has to offer, via medical research and academic papers, is really hard to synthesize. One way to get around this is to take an empirical approach to your endeavours: observe and analyze. This is actually really important, because it’s almost impossible to start with perfect information. But more importantly, it also a way to go beyond the theory and the studies to figure out what works for you individually. We can use technology and data to do this very effectively. And even better yet, we can use machine learning to do the analysis automatically and discover some really insightful things about ourselves. But this is also where a lot of the products available today fail us. That which you can track easily, like the steps you take in a day, is irrelevant for a lot of different health goals. It’s quite clear that the most important indicators of your health are biochemical by nature. So this is the impetus for this idea.

Where does Big Data fit in all of this?

The term “Big Data” seems a bit ambiguous to me, but I generally tend to think it refers to either a) the ability to derive insights from data, i.e. data science, or b) the challenges that come with the creation, manipulation, and storage of massive amounts of data. If we’re talking about the former, I would say it fits in at literally every level of our project. Our whole platform will rely on machine learning to give our users some kind of insights about their health. Even when talking about the physical hardware, we’re going to need pretty sophisticated algorithms to make sense of the data it produces. If you’re referring to the challenges that come with voluminous amounts of data, I think that’s something that will come into view later on, and only if we’re successful at designing a product that people actually want to use. Otherwise, we won’t be able to actually generate any significant amount of data. But if this project does manage to survive, let alone thrive, I think it won’t be long before we have to start considering this seriously. Luckily, we live in an age where the technology and the services exist to scale up any platform very rapidly should the need arise. Just look at Snapchat: they managed to scale relatively quickly and painlessly given their rapid growth, and they relied heavily on tech giants to help them support that scale.

How can this project revolutionize health?

In the long run, we’re trying put a computerized version of the world's smartest health expert in everyone’s pockets. Regardless of whether they’re perfectly healthy or chronically ill, we want to democratize the ability to optimally manage your health. This is where artificial intelligence will shine. In the short term, the wearable we’re designing will make tracking biochemical data easy to do with a much higher frequency than was ever possible before. This should prove to be quite revolutionary.

What are the biggest challenges, technical and non-technical?

The biggest non-technical challenge has been trying to find other people with different skillsets to come onboard. We’re very lucky to have a founding team that’s very diverse, but we’re still missing very specific types of talents.

The biggest technical challenges all revolve around designing the physical product. There’s still a lot of uncertainty as to whether or not we can actually succeed at measuring different concentrations of molecules in a live person reliably and accurately. Many very intelligent people have tried to tackle this problem, in particular for blood glucose due to its applications for people with diabetes, but it’s proven very difficult to solve. The human body is a very complex system and there are a lot of factors that can interfere with the measurements, and essentially drown out the important information you’re trying to extract.

How has IE supported you to develop this project?

I find the atmosphere here at IE is very encouraging for entrepreneurship. Most people are open to and very supportive of entrepreneurial endeavours. Everyone we speak to has been very open-minded about our idea. It’s not hard to find someone willing to listen to us or give us some form of advice. Even the professors have been open to giving us feedback and putting us in touch with people in their networks.

Where and when would you expect to launch the business?

We hope to have a product available and in the market by mid-to-late 2018.

Would you have any advice for students who would like to develop their entrepreneurial skills while in IE?

Use your time in school to find people who complement both your skills and your personal traits. There are many teachers and classmates that can give you great feedback and advice for your development. IE is well known for its entrepreneurial spirit, so don’t be afraid to share your ideas between people from your class and other master’s. Talent is everywhere.

Invivo Team Members:

Abdel Kader Lariachi: https://www.linkedin.com/in/abdelkader-laraichi/

Deepa Mamtani: https://www.linkedin.com/in/deepa-mamtani-mba/

Stefano Zakher: https://www.linkedin.com/in/stefano-zakher-05b75896/

Alexia Lorenza (MVDM student): https://www.linkedin.com/in/alexia-lorenza-martinel-b6b66083/

Daniel Julien (Team Leader): https://www.linkedin.com/in/danieljulien/

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Data Science as an Art. May Student Highlight of the Month: Apos Mourouzis

Linkedin: https://www.linkedin.com/in/apostolos-mourouzis-465a3071/

Tell us a little about yourself. Where are you from, what languages do you speak, and what did you previously study?

I was born, raised and educated in Athens, Greece albeit in an international school, which exposed me to a diverse group of multicultural individuals from a young age. As my school was a British one, English became my native tongue, while Greek comes a close second (sorry Dad). I am also trying to come up to speed on both my Spanish and French, pero es muy deficil, n’est ce pas?

I was always intrigued by puzzles, so when I programmed for the first time in high school I found that this triggered my curiosity, as it was a very intricate, elaborate and constructive form of ‘puzzle solving’. In fact it’s quite funny because as a child I wanted to become a builder (I have no idea why), and I guess that programming is parallel to that, although with digital ‘building blocks’. I pursued this subject at university and studied Computer Science at Imperial College, which took the subject into a lot more depth than I had previously experienced. Following this degree, I wanted to compliment my technical skills with some business acumen so I took Masters in Management at Imperial Business School.

And to deviate from the more formal questions, my favorite colour is blue (I don’t think you have a choice when you grow up in Greece), I would always choose wine over beer and I have an antagonistic relationship with cheese!

Do you have any work experience? If yes, do tell us about it.

I have had the opportunity to work in several companies across different industries. My first internship was as a Software Developer with YossarianLives, a search engine that is solving the problems of the filter bubble by finding alternative results for search queries based on metaphorical connections with the search term. Following my Master’s degree I worked for another startup called Contadd which deals with embedded digital advertising.

Later I decided to move into a large corporation in order to understand exactly how things work behind the ‘veil’. While working for Shell, I worked as both a Risk Analyst and Change Analyst. I was lucky (or unlucky depending on the viewpoint) to be working as a Change Analyst during the oil crisis so I was involved in a lot of restructuring and cost reduction schemes which required constant tracking, managing and reporting to senior stakeholders, as it was one of the company’s priorities at the time.

What drew you to Big Data?

I was exposed to a lot of data while working as a Change Analyst in Shell, and although I managed to derive insights from this, I realized that with a proper skillset it would be possible to learn so much more than what I could extract with simple pivot tables and VBA.

More importantly, I feel that data - pure information - is the single most accurate representation of our world. In its raw form; it contains no bias, and this is the reason that data collection has always been the basis of science. Now with the vast quantities of data available from a huge array of mediums, it is very difficult to understand where causation truly lies. It is the role of the data scientist to cut through all the superfluous information and identify the truth of a situation.

And with data on human movement, behavior, likes, dislikes, weather, stocks, transactions all quantifiable and available, the insights that are possible by leveraging big data analytics would startle any historic scientist or philosopher (here’s to you Plato).

Are you pursuing any extra-curricular activity/activities? If yes, how does it help you as a Big Data student?

The Masters is my extra-curricular! But no, seriously – I think Madrid gives you endless activities to keep you entertained outside the degree, and for me this has included playing football with some of the other Big Data students (shout out to Los Pollos). However I also make sure to stay involved in activities that directly help in my progress as a Big Data student. Recently, this has been through the Venture Lab.

Following the second term’s Start Up Challenge, my team and I were accepted into the Venture Lab with our start-up idea. We now attend several workshops a week and are aiming to rapidly expand our concept in order to produce a MVP in the coming months. And what’s even more exciting is that the skills we learn daily in lectures can be applied directly to optimizing and tweaking our project.

Your LinkedIn profile mentions that you aspire to become a Data Artist. Can you tell us a little more about the “art” in this career.

Yes indeed! I find the term ‘scientist‘ implies a rigid, formulated methodology to deriving value, whereas I believe it is more important to creatively adapt your approach to uncover insights in big data. No two data sets are the same, and the best strategies require a unique blend of one's technical expertise and intuition. Data Analytics will give you the ability to sift through a whole ‘haystack’ to find the needle, but a data artist is someone who would say “Hey, how about this magnet…?”

It is an artist’s role to see things that others cannot, and then express them through a medium of their choice, be it through music, film, storytelling or any form of art. Big data requires not only this sense of perception, but also the ‘narration’ that comes with it. The inability to convey this in a clear format will negate the benefits of any insights.

For me it’s the creativity in Big Data that keeps me hooked, for example in a recent assignment aimed at understanding the status of water pumps in Tanzania, my team translated a seemingly useless column from Swahili to English to identify keywords that revealed additional clues about the location of the pumps. Over the next few years it will be the creative applications of this technology that will change the world we live in.

Plus being a “Data Artist” allows me to pretend I’m a suppressed and misunderstood creative. Cue application to Soho House.

What are your short and long-term professional goals after the Masters?

This is always a difficult question to answer and if you asked me three years ago I would have had a different answer, while in three years’ time I’m sure I will have yet another one. However one thing I am certain about is that I see myself always staying within technology, as it has been a central driver in all my decisions thus far.

In the short term, I would like to apply my data analytics skills to extract untapped value in the real world. Smart cities, art, the news and agriculture are areas that particularly interest me due to their constructive social value. Long term there are definitely unforeseen technological changes so I cannot accurately predict what I will be doing. But my curiosity will ensure that I stay at the forefront of these changes. At the later stages of my career I hope to do this with autonomy so I have the opportunity to travel and prioritize both my family and friends. I also want to keep strong ties with my home country, Greece, as it is a place with great potential that I would like to help see flourish again, as right now it seems to be having a domestic ‘mid-life’ crisis.

How would you define IE Master’s experience and what do you value most?

I find that the Master’s experience is quite similar to the experience of learning to cook a new cuisine – you’ve always been around the ingredients but you’re now learning to make a three-course meal from them. Yes, you may have the odd food poisoning but by the time you’re done you’ll have a line of customers waiting to try what you have on offer. If only I actually knew how to cook as well…

In regards to what I value the most, the fact that I have come from a working background makes me appreciate that I am now learning something new and tangible every day which can be applied to common problems in business. It’s always fun seeing the expression on my friends’ face when you can derive unexpected insights from their own company data.

And on top of it all, the lifestyle in Madrid is unparalleled, especially when coming from the rains of London. Leave your umbrellas behind.

What would be your advice for future students?

As potential Big Data Professionals you are taking on the mantle of digital explorers. A lot of the world’s hidden secrets will be available in the web of data you will learn to traverse. You will travel across unchartered (digital) territories and stumble upon (binary) treasures but it is important to maintain a sense of integrity throughout, as your ability to discover comes with the burden of responsibility. Do not twist the data to your or your employer’s advantage, as doing so will simply undermine your own profession.

And something else that has stayed with me since my time in Shell is that “perfect is the enemy of good”. Do not strive for perfection and miss the opportunity to deliver something good in the process.

But don’t forget, all work and no play makes Jack a dull boy! Make sure to really get out into the city. As one of the most beautiful places in Europe you don’t want to miss out on everything Madrid has to offer.

And in the words of a famous sentient AI being…hasta la vista!

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A productive Spring Break: Lessons from #IDCiot17

By Bethany Orense

Every term break could be a story about fun and relaxation, recovering from lost bedtime hours after the finals week, trying to get back in shape and simply finding oneself outside the classroom walls. Eat, sleep, work out, relax, repeat.

I did just that. This spring break was about food-tripping and sightseeing in Porto and The Hague, siestas, visiting a tech museum in Eindhoven, hanging out at a cool library, siestas, doing laps at the public pool and running at a park in Brussels, and siestas. Spring break was for me relaxing that way and I could go on talking about how much I enjoyed it but there is also this meaningful last leg of the break, Copenhagen. I particularly stayed longer in northern Europe to attend IDC Nordic’s IOT Conference in Copenhagen last 20 April 2017. I have looked forward not only to attending the event but also this moment when I will sit down to organize my thoughts and write about it -- because it’s IDC, it’s Nordic, it’s the trendy Internet of Things (IOT)!

IDC is a multi-national independent consulting organization more known in IT, telco and consumer tech markets. It provides market intelligence, advisory services and events in said expertise areas. I had read a lot of IDC market outlook and reports and used them in my market models back when I was a telecom Analyst few years ago. It was an honor for me to be in the event and learn from the experts live.

Having spent half of my career in the telecom industry, I am highly interested in data-driven technologies such as IOT. Telcos no longer deny that new revenue streams from emerging technologies are the way to go forward. What was particularly also interesting for me to hear is how telcos are leading the way for IOT technologies to be the new norm in the many ways of doing things. For example, Telia Sweden launched last year an app called Telia Sense. The app enables users to have greater control and monitoring of their car via smartphone. Telia is expected to deploy to rest of Nordic this year.

That is just one example and me being a telecom enthusiast. There is so much more to be said about IOT. But what is IOT really about? Let us start with the basics: IOT, as officially defined by the International Telecommunications Union (ITU), is “a global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies (ICT).”

Let us dissect this definition to make things (pun intended) clearer. The ‘advanced services’ ITU is referring to include the “things” that you often hear with the word “smart”, e.g. smart homes, smart buildings, smart factories, smart cities, smart TVs, smart wearables, smart cars, smart everything. Interoperability refers to the ability of technologies - even if they come from different manufacturers and whether they are an old, new or future version - to connect, exchange information, and make use of these information. For interoperability to happen, the underlying technologies must be transparent and must be free from access restrictions. Now the “interoperability of ICT” that ITU is talking about in its definition of IOT is the ability of your “smart things” and computer systems and infrastructure to connect with each other in real-time, in a seamless manner and obviously without the need for constant human supervision. For these elements to connect with each other, the key technologies include devices (mainly sensors and actuators) within the wireless context, data processing and storage, connectivity, and the end-user platform.

Why is there a need to connect things in the first place?

There is no need to connect things in the same level as humans need oxygen or food, clothing and shelter to survive. However, IOT is a basic element in making smarter lives a reality. It is needed to improve business operations across industries, and at the individual level, we need it to be more efficient and effective in ways we have not imagined before, reduce accidents, make things easier and overall, have a higher quality life. Now that we have an idea of what IOT is and how it impacts us from society down to consumer level, I wish to share some realizations and key insights from the event.

From a logical framework, IOT can be described as starting from "data collection (input), to analysis (processes), to automation and operative enhancement of businesses (activities), and then to new business models and revenues" (output) and higher quality lives (outcome). - The Business Value in IOT, Anders Elbak, IDC

IOT could be a radical innovation. But it is only the beginning as far as technology adoption is concerned. “Turning things around is typically an incremental journey for both sides - the IOT service providers and the businesses. We learn by doing. So start by doing things already, because you cannot imagine what can happen, what sort of possibilities can come up.” - Unlocking Growth with New Digital Eco Systems, Hans Dahlberg, Telia

For faster technology adoption, potential customers need to see how "IOT automates and optimizes by working real-time, and allowing for remote diagnostics and context-based help and recommendation functions." For me, this is the real essence of IOT. - Driving Adoption of Connected Products, Søren Stakemann, Getinge

In the context of security, “the challenge is securing the new class of devices that are connected through the Internet.” Anti-virus solutions and human security teams are a thing of the past. By modeling all connected devices, unsupervised machine learning provides predictive maintenance, your model can learn in real-time, it is scalable, and finds threats that would otherwise go undetected, in seconds. - Self-Learning Cyber Defence through Machine Learning, Anna Kaisa-Williams, Dark Trace

It helps to strike some sort of balance between technology push and market pull. Nordic has some of the best IOT R&D practices that revolve around direct application to real world scenarios. Technical University of Denmark’s Research Center on IOT is working on industrial IOT and Industry 4.0 projects. - IOT Trends for Industrial Automation, Paul Pop, Technical University of Denmark

Every interconnected thing around us is already producing (or is expected to produce) huge amounts of data at exponential growth rates. What do all of this mean for us, my fellow Big Data enthusiasts? Imagine this entire playground of data (i.e. the principles of volume, velocity and variety) and then all the liberties (which tools, analytical models to use) that come with it. As students and professionals, we are constantly taught to focus on the business and the societal imperatives when we go out there, so data cannot swallow us alive.

And may I just say Copenhagen is beautiful; its canals and bright buildings, open-faced sandwiches on rye bread and those cute chokolade romkugler hold true to promise!

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March Student Highlight of the Month: Felix Müller

LinkedIn: https://www.linkedin.com/in/felixbigdata/

Twitter: @FelixBigData

Tell us a little about yourself. Where are you from, what languages do you speak, and what did you previously study?

Guten Tag zusammen (English: Hello everyone)! I am from Germany and in the last couple of years I have lived in the beautiful city Munich, which you hopefully know from our famous Oktoberfest. But it has a lot more to offer than beer, such as castles, parks and great food. As the capital of the state Bavaria it is home to the prime minister and lots of international companies such as Allianz, BMW and Siemens. I studied Management & Technology, a degree providing a broad overview of business, finance and computer science at Technical University Munich. My mother tongue is German but I also speak English, and due to an exchange semester in Monterrey, Mexico, and my master in Madrid some Spanish. Because in my last year of studies I focused on Finance & Computer Science, I also know a few programming languages such as Java, R & Python ☺ In my spare time I love to cook and go to bars or restaurants with my friends and my girlfriend. I really enjoy hiking and travelling to different cities around the world too.

Do you have any work experience? If yes, do tell us about it.

I come directly from my undergraduate degree to IE. However, in Germany it is very common to work before and/or during your studies in the form of Co Op positions of internships. I had the opportunity to work for six different employers in the area of banking, consulting and FinTech. Currently, I am a Data Scientist at the Munich based treefin AG which offers a personal finance management app and I analyze payments remotely from Madrid.

What drew you to Big Data?

When I was studying abroad, I really enjoyed the databases class at ITESM, Mexico where we set up a small database for patient data. It was so fast and easy to get it up and running and then write a few simple queries to analyze the data. After I had told my professor that I am interested in the field and would like to do a related master, she recommended me to look for graduate degrees in Business Analytics. The more I researched about the topic, the more fascinated I became because of the great opportunities arising for the analysis of Big Data. Luckily, I had the opportunity to write my bachelor thesis about the analysis of payments with machine learning and the R programming language. This encouraged me even more to go to IE and explore the topic further.

Are you pursuing any extra-curricular activity/activities? If yes, how does it help you as a Big Data student?

Apart from the great bars and the nature such as la Pedriza (a mountain close to Madrid) or parks, I really enjoy my engagement for the IE Big Data Club. Last month we organized the “Data Disrupt” event, where we invited business professionals from companies in the FinTech & Healthcare sector to present latest trends to the student and alumni community of IE. We also plan other events such as a data-hackathon or keynotes from founders of big data startups. But what I like doing the most is teaching my fellow students the R programming language during the R recap sessions of the club. In our biweekly meetings, I present a few concepts about questions students have sent the club in advance. It feels great to help people understand a homework or a problem that they have been trying to solve for several hours by presenting a few concepts I would apply myself.

What are your short and long-term professional goals after the Masters?

I have accepted an offer to become a Senior Data Scientist at my current employer treefin AG after graduation. The position really fits my goals because I like to work on different topics related to Big Data, such as the data science for many different areas itself, but also the development of infrastructure. Moreover, my colleagues at treefin AG are experienced in the field, and I look forward to learning from and with them. In a few years I would like to lead a team of big data professionals for a company seeing IT as a main competitive differentiator or even fund a technology startup myself. I can also see myself teaching part-time about big data related topics. However, due to the fact that the industry is changing at a fast pace, I think there will be a lot of interesting opportunities arising that are hard to foresee right now.

How would you define IE Master’s experience and what do you value most?

I chose IE because of the practical and entrepreneurial spirit. We have lots of professors that do not only teach, but mainly work for a company or are self-employed. They can provide great insights of their industries and how the tools we are learning are applied in practice. The entire program contains a high amount of group assignments, which are helpful because we learn how to work with people from around the world and from different backgrounds. Also, my fellows are highly motivated and you will always find someone who can help you with your problem because he / she has already solved it. But my personal highlight is Madrid, because the city is so beautiful and definitely underestimated! For a German it is awesome to have 25 degrees Celsius in early March and meet your friends at a rooftop to enjoy a Saturday evening ☺.

What would be your advice for future students?

Practice programming on real examples! You can only understand concepts be applying them to a problem that you are interested in solving. For example, download one of the most famous datasets, the wine quality data, from the UCI Machine Learning Repository and try to predict the quality of a wine. Also, there are tons of good videos and websites out there that you can use to learn about R, SQL, Python and statistics for free or a reasonable price. With this preparation you will definitely be able to get the most value out of your experience at IE. You will love it! I am looking forward to seeing you there at one of the IE Big Data Club events that I hope to attend as an alumnus as well ☺ And finally, go to the club events or even become a coordinator to maintain the high quality of activities available!

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Women in Data Science:  Insights on the 2017 Women in Data Science Conference.

by Tania Romero Sommerz

How important was the Women in Data Science Conference 2017 for you? How did it impact you as a student of Master in Business Analytics and Big Data at IE? How about as a future Data Science practitioner?

Exactly one year ago, I decided to leave my successful career in Finance to pursue a new career in Big Data & Business Analytics. It was not an easy decision after working 12 years in the same company, moving to a new country, but studying something completely different in a new industry is a challenge that I was enthusiastic to take. The way to understand how Technology & Data Science industries work and what are the opportunities for women made me develop an action plan to attend different events during the last month related with Women in Technology and Big Data. Having being raised in a “there is no gender difference” mentality, I really wanted to understand the challenges we, as women are facing, since it appears that men dominate this industry. For instance, in our Master’s program we are only 12 women out of 80 students. That makes us 15% of the class. For this reason, I decided to attend the WIDS Conference, which was the first one held in Madrid. WIDS is a global event organized by Stanford University event across more than 50 cities. It brings together female data scientists and big data experts with the objective of sharing their experiences, inspiring and mentoring fellow women to pursue a career in this field. Personally, the experience was extremely insightful. It was a unique opportunity to learn from successful and talented women in the field. I take them as an inspiration to me to keep dreaming and working hard about becoming, like them, a female leader in the near future. In the world of Big Data & Business Analytics we will have infinite opportunities to apply our knowledge, combining both technical and business-oriented standpoints. As a Master in Big Data student ( MBD), this conference gave me the opportunity to witness, with real examples, the different career paths I could take once I finish my studies. From Banking to Consumer Goods, Multinationals, to even startups. Because the industry doesn´t matter. As Elena Alfaro from BBVA Data & Analytics mentioned, “Today, data not only supports the business, in many cases data is the business”.

What were your favorite topics and takeaways during the Conference? Did you have a favorite speaker?

My favorite part of the event was the panel discussion on the role of Data Science in accelerating business. Real examples on how big data is transforming the way business is done nowadays and the privacy issue surrounding such technologies. From a traditional bank like BBVA, going through their digital transformation to Digital Origin, a FinTech startup who was born already as a digital company and how they are promoting new regulations to play a fair game in the financial industry. In today´s world, every single decision is taken based on data insights. To summarize my main takeaway, I will quote Rosa Maria Sanz from Gas Natural Fenosa, “Data doesn´t mean anything if we don´t have business translators that can extract value from the data to improve decision making.” It´s hard to choose one favorite speaker when you have such a group of talented women. From medical use cases that are saving lives, to business cases on how Pepsico is getting closer to consumers and understanding their behavior and needs. To business women, creating new startups like Shazura who works on visual learning through images and video recognition with artificial intelligence. To them business schools offering new programs to prepare future leaders in data science are also added. I am grateful with all of them for sharing their experiences and knowledge and especially with Carme Artigas, CEO & Co-founder of Synergic Partners and ambassador of WIDS Madrid. She has taken on a “mission to spread the knowledge about what Data Science is and the impact it has in all industries and society”. Carme is “committed to create awareness that in this field women must have a voice”. She is one of the best women leaders in Big Data in Spain and her career path has inspired me a lot.

It was interesting to learn from Ana Segurado that Telefonica’s Open future, in collaboration with the company BIGML developed a machine learning algorithm where they were able to identify that the success of new startups increases when they have at least one woman in their team. Also, Carme Artigas mentioned that Big Data needs multidisciplinary teams with diversity in culture and gender, statement which I fully agree with.

What is your message for women who aspire to be at the top of their game when it comes to Data Science and technical profession in general?

For Data Science, as for any other profession, regardless of the gender we need a set of skills. In this field, technical skills are necessary and we also need to develop other skills to excel and become amazing data scientists. We must challenge assumptions and think in a creative way to find different solutions. We must be great communicators, a skill that is strongly needed in this field as the main goal is not only to identify trends, patterns and insights but being able to effectively communicate them for decision making. We need an eye for details and get to a level of granularity analyzing data. And finally, we must be great team players who can collaborate with multidisciplinary teams. Based on this we can have a successful career in data science where one of the key objectives is to transform data into actionable, valuable insights for better decision making and process automation. I am lucky to say that being a woman has never been an obstacle to grow professionally. From what I am experiencing now and based on the feedback of the female leaders in WIDS I can say that sky is the limit for us! As any other profession, we must work hard to achieve our goals. We must be aware of the skills we need to develop in this profession, both technically and soft skills, which I believe are equally important. I truly trust in the power of Big Data and I want to encourage women to feel empowered and become part of this transformation playing a key role as future leaders in Data Science. As Sheryl Sanberg said: “ In the future, there will not be female leaders. There will just be leaders”

Watch a short summary here: https://www.youtube.com/watch?v=-6R4oU8MW-E

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How to “Hack” a Hackathon!

Juanjo, the program director, wisely recommended us to attend a Hackathon at the beginning of the MBD program. His argument was that it would be impressive to see how much we've learned during the ten month if we would attend another event closer to or after our graduation.

This is why we, Sondos, Matias, Hugo, Benjamin and Maurice, IE Big Data Students decided to attend Hackatrips, an event during Fitur, one of the biggest tourism fairs of Europe. The theme for this year’s fair and also for the hackathon was 'Sustainable Tourism'. According to the organizers, an ideal team would consist of three developers, one designer and one tourism expert. Even though this was not really a Data Science hackathon, which is our area of expertise, we decided to go in order to know more about the hackathon process and its dynamics. We did want, however, for Big Data to be the center of our project.

An hour after the event had started, we already knew what our idea was and what types of tools we need to implement it. However, as the first 6 hours went by, we were struggling in trying to achieve a fully integrated solution due to some technical restrictions, which is when we decided that it was time for us to pack our bags and 'leave with dignity'.

As we went to communicate our decision to the organizers, they cleared things up and explained that the purpose of the hackathon is to be able to present an idea while having at least a prototype available so that the jury could have a sense of what the purpose and design of the application were. Knowing that, we decided to focus on selling our idea and go with an approach that consisted in dividing the tasks according to our profiles in order to have something to show for the demo and presentation that were due the next day. Although just a few hours before it seemed hard to imagine, at the end of the first day we already had a working bot and a fully working CARTO map! The next day, we got there even more motivated, and by the time the final presentations were due, we already had an elaborated presentation, and a complete storyline.

Our project “BotTu”, is a data-driven solution aimed at analyzing unsustainable practices. It consists of a chatbot where users can denounce using images or text any violations against sustainability. All gathered information would then be centralized and stored. Later on, using CARTO maps, NGOs or governmental organizations could visualize where, when and what type of violations are being reported.

At the end of the event, we were awarded the prize of the best use of CARTO. Since this is a Madrid based Big Data Visualization startup, we were extremely happy with the result. We learned a lot. Not only did we 'hack' a Hackathon without the skills needed but we also kept going even when the goal seemed impossible to achieve. We recommend all of you to try something similar, if you have the chance. We are looking forward to see our progress towards the end of the course when we sign up for our next hackathon.

Things to keep in mind when you attend a hackathon:

1- This mistake has cost us hours: You do NOT need to have a fully working solution. As long as your idea is solid and you have a prototype to show, you'll be fine.

2- Collaborate with your teammates and give it your all.

3- Since time is limited, divide the tasks among your team as corresponds with every member's skills.

4- The presentation is very important. Make sure to spend enough time preparing for it.

5- Work efficiently.

6- Don't give up too soon.

http://hackathonlovers.tumblr.com/post/156393728753/entrevista-a-bottu-ganador-premio-carto-del-hackatrips

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Feb Student Highlight of the Month: Latika Kakwani

LinkedIn: https://es.linkedin.com/in/latika-kakwani

Tell us a little about yourself. Where are you from, what languages do you speak, and what did you previously study?

Hola & Namaste everyone! I come from a culturally rich and vibrant country, India. I was born and raised in a small town called Ajmer, but I have been living and working in Gurgaon for the last seven years. Ajmer is called the holy city of India as it is home to the only temple of Lord Brahma in the world. The tomb of the Islamic Sufi saint Khwaja Moinuddin Chishti is also here. On the other hand, Gurgaon also called the “millennium city” is highly urban where the local offices of more than 250 Fortune 500 companies are located. These two cities are disparate yet amazing. A little more about me, I speak Sindhi with my family, Hindi with my friends in India and English at my workplace and with friends in Spain. I finished my Bachelor's in Computer Science Engineering from University of Rajasthan. I love dancing, especially Indian folk and Bollywood, and I can’t stop myself whenever I hear a foot tapping number ☺

Do you have any work experience? If yes, do tell us about it.

I have more than seven years of diverse professional experience in Finance, Telecom and Networking domains. I started my career as a Software Test Engineer with a wireless networking service provider company, Aricent Technologies. I was working on a very big project for Nokia Siemens Network to implement 3G/4G network in Europe, the fruits of which are being enjoyed by everyone around the world today. Short after, I moved to Amdocs, a software solutions provider to telecom companies like Vodafone. I learned a lot about how telecom companies operate, how they manage the prepaid/postpaid subscriptions, customer queries, billing and fraud management. Later, I joined Royal Bank of Scotland as a Quality Analyst where I independently handled Quality Assurance of two critical Risk Management softwares used by FX derivative traders’ in London, Singapore and New York. I also have a little experience as a teacher in an engineering college, where I taught web-programming in HTML, JSP, Javascript and PHP. During all these years, I have worked around various constraints posed by legacy systems and helped stakeholders to improve their processes. My roles have helped me learn a lot about different people, different cultures and make great friends along the way.

What drew you to Big Data?

I developed a penchant to work with databases when I was in undergrad. I also participated in a contest held by IBM, to create a social networking website for an organization. Since then I have always loved to play with databases. But it was in Amdocs when, for the first time in my life, I was intrigued by the need for big data analytics and its applications at various levels in the organization. I was working on a telecom product for our client, Vodafone Germany, where I came across huge datasets of millions of subscribers. I saw how billing is done and how much efficiency and analytics is needed in Fraud Management and customer churn. Later, in my last company Royal Bank of Scotland, I worked on projects like Risk Analytics and reporting. These were the most important software/tools for investment banking for traders to manage risk and hedge their portfolios. I also got a chance to work on MongoDB. I was really impressed how the analytics projects worked and was fascinated by the vast amount of opportunities generated by NoSQL databases like MongoDB. But I was not adept in these technologies and I felt the need to learn more about big data, analytics and its application in numerous industries. Hence, I decided to pursue this Masters.

Are you pursuing any extra-curricular activity/activities? If yes, how does it help you as a Big Data student?

There are thousands of things to do in the heart of Spain, Madrid. Explore the history, enjoy the nightlife, learn a new language and what not. But besides all of these, I am really enjoying being a coordinator of the IE Big Data and Innovation Club. There was a tough competition to be a coordinator of this club and out of so many students I feel lucky and privileged to be chosen as a coordinator of the Club. At IE Big Data and Innovation Club we are responsible of complementing fellow IE students’ learning experiences, exploring potential areas where big data is applied, helping them reach industry experts, facilitating networking sessions and hosting hackathons where they can actually apply what they learned about big data inside the classroom. At the Club, I am responsible for creating events posters, handling part of the social media promotions, documenting events through photos, purchasing gifts for our resource speakers, booking venues, networking sessions with speakers, etc. But members are free to take part in other Club duties. I love our team and we all work in synergies and share the work and responsibilities to make all the events successful. I am looking forward to the Club’s upcoming events, these events are going to be super exciting and I am sure enriching for all Club members and participants. These events aim to demonstrate how big data is disrupting numerous industries.

What are your short and long-term professional goals after the Masters?

Short-term I would like to start as a Data or Business Intelligence Analyst and work in a data-driven company. I would like to work on the Business Information Systems of technology companies like IBM, Oracle, Microsoft, SAP, etc. I want to develop my skills and truly understand the key drivers behind a successful data strategy and efficient data governance. In longer term, I would like to build on my acquired skills to lead an analytics team and work as a project manager.

How would you define IE Master’s experience and what do you value most?

Amazing!!! It’s just been four months and I am already starting to feel nostalgic about this city (if I leave), the school, professors and most importantly the friends I have made here. I am going to miss all the parties, late night fun, group work, fun gossips about fellow students ;), being barely awake for my early morning classes but still managing to raise hands for some participation points. These and endless things. I feel so honored to be part of such a prestigious school, being trained by professors who are not just PhD experts but leaders in the companies they own and/or work for. They bring with them real world experiences and teach us in the most practical way. We have students from all continents of the world, having different domain experiences, classmates ranging from 21 to 41 years old. I am so amazed by the bunch of intelligent young students in our class. Sometimes, they challenge the experienced classmates and the professors themselves. I sometimes feel intimidated by the nerds in our class. They have an awesome solution to the most difficult machine learning and R problems. There is so much to learn from all of them. Going back to studies after almost eight years have been challenging initially. But the energy of the class motivates me a lot to achieve and strive more out of my comfort zone!

What would be your advice for future students?

I have two pieces of advice. One, before coming here, I would suggest future students to take up some courses in R, Python and Machine Learning and practice a bit. This would really develop a foundation for the program. The program is just ten months and it will pass with a blink of an eye, so a hands-on foundation will really be helpful. Also, learn some Spanish before coming to Madrid as it will really help interacting with local people as well during networking events. Second advice after coming to Madrid, apart from the usual assignments, take part in various competitions like kaggle, hackathons, summits, etc. This will enrich your learnings and help you think more like a data analyst/scientist. And of course, party hard and travel in and out of Madrid. You will create lifetime memories here. Good luck!!!

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Marketing Intelligence... the Big Data Way

On 16 Jan 2017, at 8:30 in the morning. After exactly 24 days of holiday and term break combined, believe me, it was not easy waking up and walking to school. But I must say that after all the vacation, I was eager to see my classmates again, remain sedentary inside the classroom for a few hours everyday and do some brain workout once again. Anyways, this is Term 2.

Marketing Intelligence – Term 2 first day, first subject, first session. If I were in the MBA program, this subject would have seemed normal. But for a Big Data student, it generates a fair amount of curiosity. Some of us in the class already possess an MBA or some related Management degree, so how different can this one be?

As soon as the Professor started talking, my curiosity heightened even more. What is Marketing Intelligence with respect to other fields called Marketing Science, Marketing Research, Marketing Analytics, Business Intelligence and Competitive Intelligence? Are they different at all? But the burning question is, how exactly is Marketing Intelligence done the Master in Business Analytics and Big Data way?

According to The Official Definition of Market Intelligence ™ by the Academy of Market intelligence, Marketing Intelligence is “…internal analysis, competition analysis, and market analysis about the total environment forming a broad spectrum of assembled knowledge, which is then used for developing scenarios so that timely reporting of vital foreknowledge for future planning …organization’s strategic interest for the whole market. (Grooms, 1998)”

This is a rather lengthy but useful 17-year old definition; summarized by the following words: “assembled knowledge”, “develop scenarios”, “future”, “whole market”. For me, these words combined means that information is scattered and I need to be creative in finding, processing and analyzing these data in order to have some idea about the future scenarios for my company and the entire market.

True to this, the very first thing established in class is that Marketing Intelligence involves creativity, a huge amount of listening skills, and establishing meaningful metrics among others. As creativity and soft skills are involved, it is safe to say that there are no hard and fast rules revolving around Marketing Intelligence.

There are many different ways of designing metrics for Return on Investment (ROI), advertising effectiveness, customer satisfaction, brand loyalty, and churn among others. But every company is different, and hence should be the approach.

As future data science professionals, we will learn to build expertise in business understanding from this subject – LISTEN to our clients in order to come up with actionable insights and relevant recommendations. We are expected to develop a new fascination for understanding and digging deeper into what it is that really needs to be solved before we even start collecting or exploring the datasets that we love the most. And once we already have our models in place, we need to understand that these models and numbers by themselves do not mean anything to the client. Because while the numbers for us studying Big Data already tell the story, it is not entirely the same for our clients. As our professor said on this first day of class, “there is something that lies within each number, there is a story”.

When we finish this program, the powerful analytical softwares and techniques that we are learning now will allow us to be in a position to learn about our company’s or an entire industry’s probable future scenarios through numbers. I guess that is what makes the difference between the subject being taught in this Master compared to others. It matters less whether the subject is called Marketing Intelligence or something else, the idea is to be able to relay numbers into one compelling story in order to maximise investments through effective decision-making.

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IE took me here

“Life begins at the end of your comfort zone.” (Neale Donald Walsch)

It was almost eight months ago when I decided to leave my comfort zone. Eight months since I made the choice to come here to Madrid and venture in a Big Data and Analytics Master. But where was I before?

I had a very comfortable life, a good job, bunch of friends, I was well known and respected in my country, had a promising career, a nice car and a beautiful girlfriend. I really couldn’t complain in any aspect of my life, but I could tell something was missing. I found myself stuck between two paths: Either I stay in my very comfortable zone and build up a safe career and safe life or, I strive for more but leave everything in the way and take the road of uncertainty.

Since day one I already knew what I wanted, but of course I had to ask others for validation. Most of the people I asked adviced me to stay, it seemed a more logical and reasonable option. However, there are times when logic and reason are completely overpowered by emotion and gut, and this was one of those times. I knew I had to escape my comfort zone.

That’s where IE showed up. I knew I wanted to do a Masters in Business Analytics and there are a good few options to do so, but I felt deeply moved by IE’s philosophy. It’s not only about acquiring technical knowledge, but the focus also in developing soft skills, leadership and innovation which I consider key in the formation of a human being. My decision was made, however nothing great comes without sacrifice and it is not easy leaving everything behind, investing in your formation and moving to a whole new city, where you are practically a stranger and everyone is a stranger to you. But that’s exactly what escaping the comfort zone means.

In retrospective, it was the best decision of my life. Madrid is a beautiful, mystical city and IE is a world class university. I’ve met so many friends from all around the world. In this years promotion we are slightly more than 75 students from 36 different nationalities! No international relation major can teach you how to deal with such a variety of cultures and backgrounds.

Classes have been incredibly interesting and insightful. Not only we have learned about new technologies and how to build them, but we have been able to interact and work with some of the most powerful companies in the Big Data market. We “met” IBM’s Watson, an Artificial Intelligence superstar and had the opportunity to toil with “him”. Also, some of us didn’t had a programming background and now we can fluently use programming languages for statistics and analytics. We’ve learned about Hadoop and how companies like Facebook, Amazon and Google depend on it. All of these and much more in just the first term.

There have been some bumps in the road, but that’s part of the joy of it. IE staff are always there to help you and make sure that you are comfortably established in the city. I’ve made so many new friendships that will surely will last a lifetime and I can’t help to look anxiously at the calendar, wishing that time could go slower or that my stay at Madrid could be longer.

Before IE I had a very good life, but I was right, there is always new experiences to live, new books to read, new places to travel, new friends to make, more knowledge to acquire and more than life can give to you. I’m loving my time in Madrid, I’m looking forward for the next months and I can proudly say that IE took me here.

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Introducing Amazon Go

Amazon baffles the world again!

For the last few years, tech and big data enthusiasts have heard about “self-service grocery stores” and how they could transform the way we do our routine shopping. Well, starting December this year, Amazon is making it a reality. The tech giant is testing a grocery store in Seattle, which lets customers walk in, pick their food from the shelves and walk out freely, without having to pass through checkout lines.

How? Well upon entering the store, the users tap their phones on a turnstile which logs them into a network and their Amazon account. According to Amazon, the system uses machine learning, deep neural networks, artificial intelligence and sensors for the payment system to work.

Every article the customers pick is loaded into their “virtual cart”. But the system itself is also smart enough to let customers hesitate and regret buying a product. If they put it back into the shelf, then it will also be withdrawn from the “checkout”. As they leave the store, the app adds everything the customers have taken and charges the purchased items to their respective Amazon account.

This technology can surely become a “game-changer”, and honestly it resembles a big data, machine learning and neural network masterpiece. But not everyone is excited about the news. Of course, and as it has happened with Uber, Airbnb and others, many job positions are being shaken once again. With Amazon Go, grocery stores would be able to drastically save costs, reduce waiting times and considerably increase their data collection capacity. But “human cashiers” will be taken out of the equation, and with this hundreds of thousands of jobs will be replaced by Artificial Intelligence.

Are all these replacements a bad thing? In the short term the logical answer is yes. Many people will be unemployed and that might hurt the economy. But with this new technologies new jobs are created and new set of skills become in-demand. We, as the human species will have to be prepared to adapt, probably faster than ever before. Yesterday Uber and Airbnb created a considerable change in the form of massive job migrations. Today, Amazon Go is making the same kind of change. Tomorrow, another new technology will definitely arise. Artificial intelligence is catching up with humans, and we cannot stop it. If we want to continue working, we have to be ready to adapt.

You can check out some more how it works in the following link: Introducing Amazon GO

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November Student Highlight of the Month: Peter Kerkhove

Each month, we would like to highlight one particular student in our class. This gives our readers a way to connect more with the students in our class. We are quite a diverse group and we would love to share our stories with you…

**November Student Highlight of the Month: Peter Kerkhove **

https://www.linkedin.com/in/peterkerkhove

Tell us a little about yourself. Where are you from, what languages do you speak, and what did you previously study?

I’m originally from a small town in Belgium, but the last four years, I’ve been living in Zurich, Switzerland. Zurich is a great little town: very international, clean and with forests, lakes and mountains surrounding it. It also a great place to keep practicing languages. I speak Dutch and English fluently and French, German and Spanish at an intermediate level and I used all of them there regularly. I studied Literature and Linguistics with a focus on the latter, and then Management and Applied Business Economics.

Do you have any work experience? If yes, do tell us about it.

I worked for Zurich Insurance which is one of the largest insurance companies in Europe. I started in the Brussels office where I learned a lot about international and corporate insurance. After about a year there, I wanted to have more hands-on experience with IT projects and started working at the headquarters in Switzerland. The company provided me with lots of opportunities to explore what I liked and learn new skills going from change management to requirements engineering but also to building reports and improving my data analytical skills. My roles have always been very internationally focused and I learned a lot of about different cultures and met great people along the way.

What drew you to Big Data?

While gathering requirements for reporting or for IT solutions, it was always clear to me that businesses need more insights into their customers, into their operations, into their risks. The tools and existing solutions that are being used usually aren’t enough to deliver. Everyone knows that Big Data is the solution, but not many people really know how it works or how to implement it. And that’s what draws me in. I want to understand better what it is, how it works and how to deliver suitable solutions that bring actual value.

Are you pursuing any extra-curricular activity/activities? If yes, how does it help you as a Big Data student?

Besides enjoying the nightlife in the city and getting to know more IE students, I’m very excited to be Microsoft Student Partner (MSP) at our University. The main responsibility of an MSP is to host workshops and give demos of Microsoft’s technologies. With the new CEO, the company really has been focusing a lot on developing analytic capabilities. They have some great tools such as SQL Server Management Studio, Azure, Power BI and their newly launched Cortana Intelligence Suite. I’m looking forward to learn more about those products better and share that knowledge with my fellow students. I think, it will also nicely complement with what we’re being taught at IE!

What are your short and long-term professional goals after the Masters?

In the short-term, I would love to work for a company which already has a well-established data science team. This way, I’ll be able to further develop my skills and truly understand the key drivers behind a successful data strategy. Longer term, I’d like to apply all that knowledge and skills more directly in companies who want to make the transition towards the digital and data-driven economy.

How would you define IE Master’s experience and what do you value most?

The energy you get from being here! The IE experience really is giving me an incredible buzz to drive myself further! Go that extra mile and to get out of my comfort zone. You learn so much new things during class and the topics are so wide from business courses, to coding, to maths and stats. There are interesting projects to finish, prepare for presentations, complete assignments that always seem to take more time than you think. You meet amazing people from all over the world. You will laugh so much and have so many thought-provoking conversations. Everyone also seems to be doing something cool all the time; like participating in competitions such as Google Adwords, Kaggle or starting their own company. It’s truly amazing to see all that creativity. And I haven’t talked about the parties yet!

What would be your advice for future students?

Start playing around with data! There is so much courses online that you can follow, so many resources at your fingertips. It’s a great preparation for the program and it helps you find out what you like and what you’re good at. And then once you’re in Madrid, be open for new experiences. Get to know as many people as you can, they all have great stories. And most importantly: Get out of your comfort zone! Do those things that you usually would pass for!

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What is all the fuss about big data?

Author: Deepa Mamtani

About four months ago, I lived in Sandton, Johannesburg’s affluent suburb home to the yuppies, the professionals and the desperate housewives. I had a pretty decent setup – my own flat, a slick Audi A1, gym and club memberships, invites to the coolest parties, plans every weekend and a promising career path laid out for me at one of the biggest consulting companies in the world. Fast forward four months down the line, I live in a tiny flat not even half the size of my flat in Sandton, I use public transport, parties and gym memberships seem like luxury and my weekends now consist of me spending time in front of books and my laptop. How did this happen you say? Two words – big data.

You see, big data is where it all started. Four months ago, I took a decision to leave my consulting career and my life as I know it and go study in Spain at IE. I applied to study a Master’s in Business Analytics and Big Data and got accepted. Now, in my 30s, I have rebooted my life as a student and swapped my heels and corporate attire for sneakers and jeans all because I wanted to study Big Data.

Why the hype?

My first interaction with this term came about four years ago when I was a newbie in the consulting world. I had the opportunity to sit in a financial services strategy session where all the hype was around big data – not because it was so relevant, but because everyone was trying to get their head around what it was. In the past three years, I have not heard a term being more used and misused by every client and consultant regardless of sector and industry. Things have progressed now; more and more people understand the need for and the value that big data and analytics brings. But there are still some of you reading this and thinking, ‘I don’t really understand the hype and what this is?!’ Don’t worry, you are not alone. This was also me once. I vaguely knew of the term but I didn’t grasp the concept. So, I’ve written this post to help you understand the breadth and depth of what big data is so you’re not this guy:

Size does matter

Using data to uncover insights is not a new concept at all. But the way we do it, where we look for the data and how we extract value from it has considerably changed. With the advent of social networks and smart phones, the amount of data we can create with every swipe of our hand is astounding. According to DOMO’s Data Never Sleeps 4.0, they calculated that for every minute, there are:

• About 2.4 million users liking Instagram photos – about the population size of Qatar

• About 7 million Snapchat users watching videos – about the size of London’s population

• Around 972 000 Tinder swipes – that’s a lot of potential hook ups!

• 99 200 answers answered by SIRI – I doubt those questions were on the meaning of life…

• 400 hours of new videos shared on Youtube – probably more cat videos!

What did you think they meant by big when they came up with the term, Big Data? Size. Does. Matter. But this is not even everything. Big data is not just unstructured social media data, it can be structured data like customer records, patient records, stock market data, sensor data etc. Essentially, it is an amalgamation of all kinds of data. There is a whole bunch of data, in different forms, covering different topics, being put out into the web or generated constantly. Now imagine if you can take all this data in all of its forms and use it to extract insights to benefit your organisation or society? To track and predict weather patterns to help farmers, to correctly diagnose patients using a database of information gathered by doctors, to accurately price your products and predict demand. These are just a few examples of how big data and analytics is being used to revolutionise the way we do things. Insert nerdgasm here. If you are not yet impressed, now is the time to be.

In more formal terms, the term big data refers to the volume of unstructured and structured data that traditional databases and platforms cannot process. It also refers to the technology and platform to process, in real time, the vast volume of data. So, in a world where we are spewing out data at every turn, being able to understand and analyse it, is going to be (read is already) a very sought after skill. Klaus Schwab, the former president of the World Economic Forum, has dubbed this era as the fourth industrial revolution driven by the digital age and the data economy. The World Economic Forum’s book on ‘The Fourth Industrial Revolution’ predicts that most traditional professions will be obsolete in the next two/three decades. In more crude words, adapt or die. Hence, my decision to give up everything and go back to school.

It’s not rocket science, just data science

By now you’re probably thinking, that’s all well and good but I don’t need to learn about big data to be relevant, I just need to let the nerds understand it and explain it to me. Well yes, you can adopt this position. In fact, you can definitely adopt this position if you are already in the C-suite of your company. However, if you are still a pleb with higher aspirations then you need to rethink the skill set you are offering to the working world. The good news is that you don’t have to be a computer whiz kid to enter the data science profession.

All you need is an aptitude and keen interest in the subject. The reason I chose to do this Master’s at IE was because this Master’s caters to professionals without a background in computer science, programming or statistics in general. And hopefully, ten months later, my gambit of giving up my once cushioned life and forcing myself out of my comfort zone, would pay off :D (here’s hoping!).

About the author: Deepa Mamtani is a Master in Business Analytics and Big Data 2017 candidate for IE University

Disclaimer: All the writers of this blog are IE Master in Big Data students or alumni. Neither the author nor the school owns the pictures displayed above

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Constantly evolving & converting innovative ideas into reality. Now, more than ever, we are IE!

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Machine Learning: Science-fiction is not so fiction anymore.

The world is evolving at thunder-speed, and an increasing number of machines are being designed to catch up with humans in many activities. Ever since IBM’s Artificial Intelligence (AI) Deep Blue defeated the world Chess Champion in 1997 a lot has been going on. Self-driving cars, close-to-perfect face-recognition software, stock investment geniuses, chatbots and even AI doctors are close to be (or already are) part of our daily lives.

The scary (amazing? interesting?) part of this is that machines can outsmart humans. One has just to see how Watson, also an IBM AI robot “destroyed” the other (human) players in a game of Jeopardy in 2011. So… what’s the limit?

A few years ago, AI boundaries were given by the codes written in the robot’s programming. Humans taught a bot how to perform a task and work his way through it. “Learning” was not possible unless the programmer changed the codes. But now, deep neural connections or complex “neural networks” allow robots to learn and adapt. In other words, they can teach and program themselves, just like humans do. Just refer to Google´s AlphaGo, an AI that defeated Lee Se-dol, 18 times World Champion, in a game of GO. The ancient Chinese Game was considered impossible for computers to play, given that there are more possible positions than there are atoms in the universe. AlphaGo was taught the basic rules of the game, and with practice it got better and better until it could defeat the World Champion (Byford, 2016).

So… what’s the limit again? I honestly cannot answer that question, and most likely no one can. Giving robots the capacity to learn, adapt and “think for themselves” seem like a concept from the Sci-fi hit “Terminator”. But this time, this is real life. This isn’t fiction anymore. That doesn’t mean that we will eventually be dominated and exterminated by human-like robots (I hope) but it will definitively change the way we see and experience the world. A lot of jobs will no longer be as in demand as they are now, but new ones will definitely arise. Soon, simple tasks like answering a product query, not-so-simple tasks like driving a car and complex tasks like giving an accurate diagnosis for a rare disease will be done via AI. Is this the kind of world we would want to live in?

The answer to this question is very personal, but be prepared to adapt because one thing is for sure: The Artificial Intelligence revolution is coming!

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“This is so much better than what we have expected.”

It has been three weeks since the start of our MBD classes. This period had been nothing but extraordinary. And how can it not be? How often do you meet and connect for the first time with more than 70 brilliant minds from 36 different countries, with a promise that you will all be together through thick and thin at least for the next 270 days or so?

Three weeks since. In such a short span of time, we have already created countless little random memories: In the bus going to the Segovia Campus, a “sportsfest” in the name of IEUnite, playing football, strolling at El Retiro, shopping at Sol, munching on tapas and sipping wine elsewhere, spending small breaks just sitting down by the green grass fronting MM11, home-cooking and pigging out on each other’s traditional national dishes, dancing to El Taxi at every club, or just drinking cerveza at some speakeasy place in this beautiful neighborhood. To those of us who did not have any particular task in organizing any of the abovementioned and upcoming events, we give a big hug to the IE Community and classmates for taking the time to reserve our venues, arrange meeting places and basically take part in the preps.

There will be other blogs about academic- and campus-related activities. But this one is all about those little random memories that we have and we will continue to create outside the classroom together. As one classmate puts it, “This is so much better than what we have expected.” Because these little random memories are also a form of learning and they work hand-in-hand with academics. And in the end turn all of us into well-rounded human beings.

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A quick insight into our bloggers!

Warm greetings to our batchmates at MBD, the alumni, the rest of IE Community, and Business Analytics and Big Data enthusiasts all over the world! My name is Bethany Orense, one of the MBD fellows for this intake.

It is indeed an exciting time to be in school once again. As fellows, it is one of our goals to document and share with you and the rest of the world our batch’ exciting journey within the program, within IE University, and this breathtaking city called Madrid. We have been warned that as this academic year goes by, we will have our fair share of ups and downs as graduate students. It will not be easy all the time. But it will all be worth it.

We strongly invite you to share your thoughts and feedback about topics that you would like to read from this site moving forward, not only once but whenever you can. Our articles our meant to make things lighter and constantly remind everyone that we are all in this boat together. With Jose and Pato, we hope to somehow inspire you more with our upcoming blogs.

Thank you for reading and looking forward to this exciting journey with you my fellow MBD students!

Beth

To my fellow MBD 16-17 students, the rest of the IE community and readers, words are not enough to express my excitement in meeting you and sharing this experience with you. We have an amazing year ahead of us, with challenges, but with even better opportunities to learn about things we never dreamed of doing.

Hopefully, this blog site will serve as proof of these dreams. We will be capturing the most unforgettable moments throughout our year, mainly for three reasons:

First, to recap our courses, networking opportunities, challenges and learning experiences.

Second, so that future generation MBD’s can have a glimpse of this program and the amazing people that are part of it.

Third, to provide insights of future opportunities either as data and analytics professionals or as entrepreneurs/innovators. Personally, I will try to post insights about business opportunities and content within all sectors in the Big Data space. As an entrepreneur and venture developer/ start-up consultant myself I have had the opportunity to work in many industries.

In the last two years, I have come to see the impact of data-driven companies in the Information/Digital Era. Of course, I want to be part of it. I bet you all want to be part of that as well. So I hope you enjoy reading the upcoming blogs, your year and have a memorable experience. We will do our best to capture it all.

Jose

Hi everyone! I’m Pato, MBD student. We will be updating you with some information about the school, the courses and of course, a bit of the latest Big Data news and career opportunities that surround this amazing technology world.

To all of you who are reading us, I would like to invite you to share your opinions, insights and knowledge with us. Big Data is all about sharing information, and we love it!

Pato

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Every step you take... I’ll be mining you!

Everyone is looking sharp. Men in their suits , and women looking gorgeous in their dresses. It is the formal opening day of our program and we are heading to the IE campus at Segovia. Segovia is a small, lovely town near Madrid. It’s a sunny day and we cannot wait to witness the town’s profound historic background and breathtaking landscapes. You could see it in everyone’s eyes the joy, eagerness and curiosity of one who has just started living a dream.

We were welcomed at the IE Segovia campus. The buildings are architectural masterpieces built in the twelfth century. They have been restored to host IE’s undergraduate programs, recognized as one of the best in Europe. The building’s cutting edge technology combined with a historic layout let you appreciate the best of the past and present eras. Inside, PhD Lee Newman, dean of the Human Science and Technology School and the program’s directors welcome us with a smile. The day has finally come, it’s official, our master has started. We sit in a beautiful hall, beside our schoolmates representing all six continents and 66 nationalities to be precise.

We listen intently to the speakers, all funny, smart, witty and open to help us. The dean, PhD Newman was the first to speak and gave us our first ever assignment: create a war cry for the program. Seems easy, but organizing more than 70 students, all with different backgrounds can be quite a dare. We tried different songs and yells that represent our team, until a glimpse of light came into our minds: Every move you make Every step you take Every single breath Every word you say I’ll be MINING you!

Taken from ‘The Police’, Every Breath You Take it is indeed a war cry that fits like a ring. We came here to learn how to responsibly use every single piece of data for a greater good, and to do that, some ethical mining has to be done. That being said, our first group work was a success. The day went by and the excitement only increased. We all knew we made a great choice. IE is amazing, Madrid is beautiful and our program, Big Data deeply arouses our curiosity. This surely will be one of the best years of our lives.