In contrast to 2015, when the Data Science hype was rolling across Germany, we now do have more and more universities offering specializations or whole degrees in Data Science and tightly related disciplines. Yet, still many aspiring Data Scientists have completed different studies, e.g., computer science, physics, mathematics or economics. To be honest - I highly appreciate the diverse backgrounds of Data Scientists I have been collaborating with.

Coming from a non-DS field, you'll need to do some additional homework in order to keep up with ML natives. But in the age of MOOCs (massive open online courses), there are enough offerings. I'll try to provide an overview and give some guidance. 

Data Scientist are pack animals - they need a team to develop and achieve their maximum productivity. Leaving them as individual fighters will turn them inefficient, stuck too often, lost in complicated projects - and most likely lead to churn. But how do you build a Data Science team? How do you achieve a good skill mix? And how do you create a culture of creativity, open-mindedness and productivity? There is not the "one size fits all" answer, but at least there are some clear guidelines.

For some years now, Data Science has been a much discussed topic. It all started as a hype, the new holy grail, substituting Big Data as the "teenage sex" of business crowd. But what is the status in the beginning of 2021? What is the maturity of Data Science in Germany? Have we succeeded in delivering on all those promises and expectations? And most important: is Data Scientist still the "sexiest job of the 21st century"?