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[DataFramed Careers Series #3]: Accelerating Data Careers with Writing

Today is the third episode of this four-part DataFramed Careers series being published every day this week on building a career in data. In today's episode, we discuss with Khuyen Tran, Developer Advocate at Prefect, how writing can accelerate data car

Jun 2022

Photo of Khuyen Tran
Guest
Khuyen Tran

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

Key Takeaways

1

Writing can be a great way to acquire and reinforce knowledge in data science, and an awesome way to accelerate a data career.

2

The best content provides value to the audience, and prioritizes helping people over being popular.

3

To succeed as a writer, write about topics that interest you, not just topics that you think others will be interested in.

Key Quotes

Writing really helps me to reinforce my knowledge. Sometimes there's some knowledge that you think you have, but once you try to write it down, you see the gap in your knowledge, and you are able to understand it better after writing. I think a lot of people really want to learn about certain concepts but haven't had the chance to do more research on them because they are stuck in their daily work routine. Writing is another way for you to get out of that routine and do research on the topic that you are interested in.

For a piece of content, it doesn't need to be popular. As a writer, you should aim for your content to be helpful. Even if it's only useful for 10 people, it’s already good. If I know my content will be helpful for even a small subset of people, it motivates me to keep going. I also don't check my notifications on Medium anymore, because I never want to feel de-motivated if one of my articles isn’t popular

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