10 Reasons why Business Knowledge is important as a Data Scientist. My journey from Information Systems and Hackathons into Data Science.
I did not start programming when I was 10 years old. My first math competition was at the age of 23. I was quite good, but it was barely not enough to get into the finals. Right now, I am focusing on data science while I am studying computer science in a graduate program.
My dream of becoming a data scientist started at the end of my bachelor’s degree in Information Systems and Management. On one hand, I feel overwhelmed by my colleagues which are usually better mathematicians than I am. On the other hand, I think a bachelor’s degree which focuses on business and technology is beneficial to my journey. The reasons for my believes are based on mandatory business classes I had to attend during my undergraduate studies.
Knowledge Management is the backbone of each successful product. If I think of the thousands of documentations which are made for any software library I use, it becomes clear that this topic is essential. For example, can you imagine how to use the Python Pandas library without its documentation? Another example is how I had to introduce a knowledge management strategy while I was working as a data analyst. As a growing team, we had the problem that new team members don’t know anything about our dashboards. To remember and explain every piece of knowledge seems impossible. For me, it was beneficial to learn some fundamentals of knowledge management, especially if you have to decide what is implicit knowledge and explicit knowledge.
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