It's About Time We Broke Up Data Science
It's highly unlikely that business owners are going to read this and begin to change their perspectives on how we define Data Science. Not because I doubt my influence or anything, but since I'm aware that the majority of my readers are at the beginning of their Data Science journey -- I really dislike the term "aspiring" -- but here is what I wish to tell you all… Stop trying to be good at everything in Data Science, and pick 1 (max 2) area's you want to specialize in and get really good at it! Let's face it... Breaking into Data Science is difficult for a number of reasons. However, I've come to a realization recently that much of the difficulty lies in the fact that the term "Data Scientist" encompasses so many different technical qualities that make it virtually impossible for one individual to meet all these criteria and stay up to date in each area -- and that's okay! I've been listening and speaking to Vin Vashishta, Chief Data Scientist and LinkedIn Top Voice 2019, and he believes that for roles to be defined better then more specialization amongst practitioners must occur.
Apr-14-2021, 10:20:04 GMT
- Technology:
- Information Technology
- Artificial Intelligence > Machine Learning (0.43)
- Communications > Social Media (0.70)
- Data Science > Data Mining (0.50)
- Information Technology