Thilo Stadelmann, Autor bei Data Science made in Switzerland

SDS|2015 Conference Review

The Swiss Data Science community recently met at SDS|2015, the 2^nd Swiss Workshop on Data Science. It was a full day event organized by ZHAW Datalab, with inspiring talks, hands-on data expeditions, and an excellent provision of space and atmosphere for fruitful networking. The conference took place on the 12^th of June at the premises of ZHAW in Winterthur. It attracted people with a wide range of skills, expertise, and levels from doers to managers, and had very strong support from industry, hence showing the huge potential and scope of the subject.

Review

After having the workshop kicked-off by the President of ZHAW, Dr. Jean Egbert Sturm, Professor of Microeconomics & Director of KOF Swiss Economic Institute at ETH, gave an insightful keynote talk on The use of ever increasing datasets in Macroeconomic forecasting. He explained to the audience the way to do economic forecasting using simple and standard analytical techniques. It was specifically very interesting for data analytics experts to see such a methodology that successfully uses down-to-earth analytical techniques integrated with in-depth knowledge of Economics. Continue reading

SDS|2014 Review

8. April 2014 / Thilo Stadelmann / 1 Comment

SDS|2014, the 1st Swiss Workshop on Data Science, took place on the 21st of March, 2014 – and we organized it. You can find an excellent summary of the talks on Frank van Lingen’s blog “ITelligence Insight” (Frank attended the workshop, but is not affiliated with us – so its ought to be a fair review), and the slides are available under the first link above.

So instead of repeating Frank here, I want to do two things: give you some impressions of the day itself, and draw some conclusions:

The data science skill set

29. November 2013 / Thilo Stadelmann / 1 Comment

Drew Conway´s data science Venn diagram is used by many (including me) to give a first impression of what data science is all about. And rightly so: I, for example, like it for its simplicity and “coolness”.

When in a more in-depth discussion, moving from mere buzz to concrete skills and project possibilities, we at the Datalab have gained good experiences with the following “skill set map”: