Euro 2016: Surprises and predictions before the quarterfinals

Who would have predicted Iceland to win? Prof. Dr. Feindt looks closer at the 2016 European Championship and uses the Blue Yonder algorithm to review and calculate the results.

Predictions for 2016: The Year of the Algorithm

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Summary Budapest BI Forum: Science meets Business

IN Data Science, Events & Awards — 29 October, 2015

Building bridges between conventional business intelligence methods and cutting edge data-science - this is the Budapest BI Forum 2015 summarized in one line. Entrepreneurs, businesspeople, open source contributors and scientists got together in Hungary's capital, to spend three days attending hands-on sessions and talks. A perfect occasion for…

The Budapest BI Forum. We will be there!

IN Data Science, Events & Awards — 13 October, 2015

Three days of keynotes, workshops, talks and case studies provide an opportunity for experts to share their specialist knowledge. From October 13 to 15, 2015, the Hotel Mercure Buda will host the Budapest BI Forum, which focuses on business intelligence, analytics and applications at leading companies. One of the participants is Holger Peters, data…

Data science is not a marketing discipline

IN Big Data, Data Science, General — 09 October, 2015

What does a data scientist do, exactly? Marketing, for one, often provides a false picture, as Former CERN physicist and Senior Data Scientist at Blue Yonder Dr. Paul Schaack knows only too well.

Causality is not overrated

 In yesterday's post my colleague, Lars Trieloff, introduced the The Causality Trap  and how it can lead marketers to systematically spend money on the wrong customers, those customers who are most valuable on their own, regardless of whether they receive advertising or not.

The potential of causal data science

IN Data Science, General — 31 March, 2015

Data science has been amazingly successful in exploring statistical correlations and dependences and predicting probabilities of future events. Getting causal information from data would be the next qualitative step.

Which environment to choose for Data Science?

IN Data Science, General — 12 November, 2014

Summary: In the past, R seemed like the obvious choice for Data Science projects.  This article highlights some of the issues, such as performance and licensing, and then illustrates why Python with its eco-system of dedicated modules like Scikit-learn, Pandas and others has quickly become the rising star amongst Data Scientists.

Democratizing insights derived from data

IN Big Data, Data Science, General — 21 January, 2014

What used to be scarce or a privilege to some, is omnipresent today. Data is everywhere. We consume data, we create data, machines create data… Governments make data publicly available. More data is available to more people than ever before. So, data is not the problem.

The Data Science Academy: reflecting real-world practice, and aimed at strategic managers

IN Data Science, General — 17 January, 2014

Starting in mid-February, the Data Science Academy, created by Blue Yonder, will begin teaching. The head of the Academy, Dr. Ulrich Kerzel, describes the course content and how it was individually and specifically tailored to managers, specialists, and future data scientists.