Data Science done right

Data Science done right
Philipp Rebsamen12.02.2019

As I have recently passed my MCSA in Machine Learning, Data Science and Analytics with Microsoft R and Azure ML, I decided to share some thoughts on the topic of Data Science here at CSA Engineering.

The term “Data Science” has been a buzzword for quite some time now, slowly replacing traditional concepts such as business analytics, business intelligence and in some case even classic statistics. As usual, buzzwords tend to be viewed as an “entry ticket” to being considered as a successful organization. Especially big companies, whose scale alone suggests that there should already be a plethora of different data types available to consume, understandably believe they have a great deal to gain from Data Science.
Unfortunately though, many times companies just hire or train specialists, provide them with access to their data and turn them loose, expecting smart ideas and break-through results in an instant. Data Science projects with such a mindset are usually doomed from the get-go and will turn into a real “Buzzkiller”. There should always be, at the very least, an overarching goal to pursue and everyone should commit to it.

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