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,
Background: Prof. Dr. oec. HSG Holger K. von Jouanne-Diedrich ist seit 2013 Professor für Wirtschaftsinformatik und Customer Relationship Management an der Hochschule Aschaffenburg, Bayern. Er promovierte am Institut für Wirtschaftsinformatik der Universität St. Gallen, Schweiz, und studierte Betriebswirtschaftslehre an der Universität Hamburg. Weiterhin hatte er verschiedene Stationen bei der Lufthansa, der
Social skills are not, perhaps, the first words that many people would associate with data scientists . They are far more likely to be seen as geeks, communicating mainly with computers. But the world of data science is changing, if indeed that geeky perception was ever true. Nowadays, data scientists and
With the spreading of artificial intelligence, advanced analytics tools have already conquered many areas of life. The SAS Analytics Day conference in Budapest (Hungary) examined the present status and the future potential of data science.
If you are asked to give an example of using mathematics in everyday life, most people will immediately think of dividing the bill in a restaurant, or possibly calculating percentages. For most of us, this kind of maths will not be a problem, but somehow the whole idea of maths
A restaurant cannot survive without customers. It does not matter how cutting-edge or delicious its food, or how many Michelin stars it has earned. The equation is simple: If it has no diners, there will be no income, and the restaurant will go out of business. This insight could be
Don`t jump into modelling. First, understand and explore your data! This is common advice for many data scientists. If your data set is messy, building models will not help you to solve your problem. What will happen is “garbage in, garbage out.” In order to build a powerful machine learning
I bet many of you didn’t even know the term machine learning five years ago. But Gartner did. The Gartner Magic Quadrant for Data Science and Machine Learning Platforms, 2018 was just released, and SAS has been in the leader’s quadrant for five years straight. According to Gartner, “This Magic
A recent documentary on TV amused me. It asked teens what they want to do professionally. The answers included YouTube star, DJ and – over and over again – “influencer.” Quite apart from the fact that all these are relatively new jobs, they also have something else in common: There
Part 5 of this series brings us to Rotterdam again, where I met with the two Notilyze founders Colin Nugteren and Tom Dogger. Both of them studied econometrics in Rotterdam, but go back as far as the F4 soccer team they were both playing in as kids. Company overview The
Kürzlich habe ich mich sehr amüsiert über eine Reportage im Fernsehen: Man fragte Jugendliche, was sie mal beruflich machen wollen, und die Antworten waren „YouTube-Star“, „DJ“ und immer wieder auch „Influencer“. Letzteres ruft gerade bei der Ü30-Generation Verwunderung hervor, da man irgendwie an Grippe denkt – die Aussprache ist gleich,
Students live and thrive in a community: the student body and its associations form a relatively tight-knit group that provides — or should provide — support and encouragement on an ongoing basis. For those away from home for the first time, this community can be a life-saver, almost literally in
There are not many conversations, presentations or media briefings about analytics that don’t at some point touch on the issue of ‘people and skills’. Convincing business leaders of the merits of analytics given the technology now available is often the easy part. It inevitably leads on to what the barriers
Im Jahr 1963 wurde zu Silvester erstmals der Sketch „Dinner for One“ mit dem britischen Komiker Freddie Frinton im deutschen Fernsehen ausgestrahlt. Im Laufe der Jahre wurde diese Sendung zur lieb gewonnenen Tradition und erlebt immer wieder Phasen, in denen sie zum Kult avanciert. Die zentrale Frage lautet ja bekanntermaßen:
