La duda es uno de los nombres de la inteligencia. - Borges Para data scientist/analistas de datos/viejos mineros/lobos de mar. En los comienzos de nuestra carrera de data scientists, el poder de cómputo era muy inferior al que disponemos hoy. Sin embargo, muchas empresas ya veían el enorme potencial de
In my first two posts of this blog series, we heard why two students chose to pursue a STEM field and what appealed to them about data science. We also heard how they put their knowledge to work on a real-world data science project. Today, we'll hear their advice to future
Phil Simon chimes in with some tips on how to set these folks loose.
Mein Name ist Daniel und ich bin in der vierten Klasse. Diese Woche wurden die Eltern in meine Schule eingeladen, um uns etwas über ihre Arbeit zu erzählen. Und mein Vater war mit dabei. Am Anfang war ich etwas unsicher, ob ich mich darüber freuen sollte. Denn wenn sein Vortrag
“There are known knowns … There are known unknowns … There are also unknown unknowns” This statement by Donald Rumsfeld is famous from the world of politics. But the phrase “unknown unknowns” was actually coined by a NASA data scientist to describe the huge possibilities presented to us by big data
People who work with data have had a number of job titles in my time, including data admin, data specialist, ETL developer and data integrator. The rise of the term data scientist as the de facto job market term for an analyst, however, left us data people a bit high
The information obtained from all your accessible data is a great source of power for your organization to exercise. Information is power! By applying artificial intelligence and machine learning models, you can infer details that might be very sensitive about a person or community, which may or may not be
British Prime Minister Theresa May made it clear that her ambition is for the UK to become the global beacon for innovation in artificial intelligence when she spoke at the Annual General Meeting of the World Economic Forum earlier this year. Great news, then, that two UK master’s in data
In Q1 2018, the Serbian economy grew by 4.5 percent, well ahead of forecasts. The data science community also grew, rapidly attracting talent and energy, but still not fast enough to meet demand! Things Solver is a Serbia-based data analytics and engineering company working with customers worldwide, and is one
We hear a lot about data science nowadays, but do you ever wonder how it’s being used to help solve real-world problems? In my first post of this blog series, we heard why two students chose to pursue a STEM field and what appealed to them about data science. Today, we'll hear
Are you curious? Do you have a passion for science, technology, engineering and math (STEM)? Do you enjoy robotics or statistics? Do you like to solve hard problems? If you answered yes to any of the above, you might have what it takes to be a data scientist. Recently, I
The data science community has embraced hackathons in a big way. My colleagues are active participants, some are organisers and many are habitual prize winners. We have explored how hackathons support innovation and build teams. But mostly, these have looked at how to inspire adults. As a parent, I was
At the German SAS Forum, Sascha Schubert and I ran some hands-on sessions or workshops on data science and analytics. You might say that this was nothing new, but I noticed some changes from previous forums that I think may point towards wider changes in the analytical landscape. Here, then,
Analytics platforms have a lot to live up to. The scope may be fairly straightforward, but expectations can be high, and there is a wide range of users and customers, all of whom have slightly different needs. This post explores what IT decision makers can expect from an analytics platform.
Data-Science-Plattformen müssen vielen Anforderungen gerecht werden. Ihre Aufgaben sind relativ genau definiert – und die Erwartungen, die Unternehmen mitbringen, oft sehr hoch. Darüber hinaus sind die Anwendergruppen alles andere als homogen. Dieser Blog erläutert, was insbesondere IT-Entscheider erwarten. Was ist eine Data-Science-Plattform? Die Antwort ist einfach: Sie dient dazu, Erkenntnisse
Beim diesjährigen SAS Forum Deutschland in Bonn boten Sascha Schubert und ich einige Hands-on-Sessions zu Data Science und Analytics an. Nichts Neues, denken Sie wahrscheinlich. Aber mir sind einige Veränderungen zu vorherigen Events aufgefallen, die meiner Ansicht nach auf einen größeren Umbruch in der analytischen Landschaft verweisen. Hier also meine
For part 7 of this series, I had the pleasure of interviewing mathematician, former colleague, and data science “rock star” Longhow Lam. Since there’s no need for an office for his one-person company, we decided to meet for lunch in a very hot (31 degrees) and sunny Amstelveen city
Several weeks ago, I wrote about practical advice from a Chief Data Scientist in my blog “From Aristotle to Pi: Practical advice from a chief data scientist.” Now I want to offer my advice as a newbie trying to navigate through machine learning concepts and how to code them. Over
In a previous posting, SAS Customer Intelligence 360 was highlighted in the context of delivering relevant product, service, and content recommendations using automated machine learning within digital experiences. Shifting gears, SAS recognizes there are different user segments for our platform. This post will focus on building custom analytical recommendation models
Data science is hot. Being a data scientist has been described as one of the world’s sexiest careers – though that may say more about the people coining the description than data science – and data scientists are both in high demand and increasingly well-paid. It is, in fact, highly
What can you learn from a chief data scientist who's worked in analytics for for 25 years and has been involved in the development of many key SAS solutions, including SAS Enterprise Miner? As a veteran of the analytics industry, Wayne Thompson has witnessed the evolution of machine learning and
Prof. Dr. oec. HSG Holger K. von Jouanne-Diedrich has been Professor of Business Informatics and Customer Relationship Management at the Aschaffenburg University of Applied Sciences in Bavaria since 2013. He holds a doctorate from the Institute of Information Systems at the University of St. Gallen, Switzerland, and studied business administration
There is a saying that you learn something new every day. The idea behind it is that every situation offers the potential to learn something. In other words, you are always learning from those around you, and from what happens in your everyday life and work. This sounds wonderful. Ongoing
Part 6 of this series takes us to the first Dutch SAS partner, PW Consulting, where I talked with Technical Director Willem Boersma, Data Scientist Wouter Hordijk and Sales Manager Jeroen de Nooijer. Company overview PW Consulting was founded in 1988, one year after SAS Netherlands opened. For those who
In my previous post, I talked to Prenton Chetty, Head of Analytics at Nedbank, about changes to analytical projects. In this post, we discuss how data science teams are organised and the operational challenges of running this type of team. Do you think data science teams should be centralised or
In my last post, I talked to Prenton Chetty, Head of Analytics at Nedbank, about the impact of analytics on the business, and how modelling has changed the conversation and improved decision making. This post continues our discussion, and explores Prenton’s views on how data science is changing with AI,
Innovation labs remain an important way of introducing both innovation and analytics to business, especially as artificial intelligence becomes more important. I caught up with Prenton Chetty, Head of Analytics at Nedbank, to discuss how he sees his role changing in the future. Tell us about your current role at
The SAS Data Science and Advanced Analytics Forum brings together businesses and universities, and at a recent event, universities described courses that focused on providing students with technical skills and competencies to handle data, together with some understanding of how data scientists use software. Businesses, however, emphasised the importance of
Im Gastbeitrag beschreibt Deloitte, wann, wie und warum Unternehmen Data Science benötigen. In den letzten Jahren haben sich analytische Modelle zur Echtzeitentscheidung in vielen Branchen etabliert. So bieten Airlines bspw. im Zuge ihrer Customer Journey individualisierte Angebote. Selbiges gilt auch für den Onlinehandel. Da es sich bei Data Science um
Zur Person: Dr. Volker Stümpflen verantwortet als Leiter Data Strategy & Operations bei der Mediengruppe RTL vor allem den Auf- und Ausbau der Data-Science-Aktivitäten sowie die Realisierung und Monetarisierung speziell analysierter Datenmodelle mit Fokus auf Nutzerverhalten und Nutzerbedürfnisse. Er verfügt über große Erfahrungen mit der Vernetzung großer Datenbanksysteme und Applikationen,
