Data science has never been more popular than it is today.
I recently had the pleasure of speaking with Marko Sjöberg, VP of Product at IBM, about his new book, The Data Scientist Brain.
Sjöber’s title is « Why You Shouldn’t Learn Data Science to be a Data Analysis Expert. »
His main argument is that the value of data science is not in the technical aspects, but in the human aspects of it.
In his words, « data science has been the subject of much study and discussion, but few have really been able to demonstrate how the human brain contributes to the value. »
The problem with data science in many ways is that it is largely a human job.
When you look at data, the human element is the most important part.
It’s the one that you are the most likely to be able to predict and adapt to the data.
The way we learn is by interacting with data.
Data science helps us understand the relationships among individuals and groups, the patterns of variation in the outcomes of experiments, and the relationships between the different ways people are interacting with the world.
The problem is that this kind of analysis is difficult for humans to do.
The human brain can’t process all of the information we’re presented with.
We have to be mindful of that.
We are better off if we focus on the data, and we should use that data to better understand the world we live in.
I hope this post helps you understand the challenges you face when you want to learn data science.
The Data ScientistBrain is available for pre-order now.
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