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Data analysts have a diverse set of skill sets. They can essentially be software developers with expertise in Python or R. They can be data visualization or reporting experts proficient with Tableau, Power BI, or Excel. They can also have little or no technical skills whatsoever. Whichever breed of data analyst you’re striving to be, you’ll need the right skills and experience.
This week, we looked at the intersection of data analysis certs and degrees — and their impact on data analyst salaries. Importantly, we discussed why you don’t need a degree to enter the burgeoning field of data analysis.
You don’t need a four-year degree to become a data analyst. The demand is so great and the supply of college graduates looking to become data analysts so small that a degree can help, but it’s no longer required.
Data analysis certifications are no substitute for experience. However, certifications (even a few of the free ones) can certainly validate data analysis experience in a way that’s transferable between jobs and even industries.
Data analyst job descriptions vary wildly depending on the industry, company, and city where you work. However, we found that salaries are roughly tied to the cost of living. But that doesn’t mean you can’t increase your worth with experience and certifications.
As businesses create more data, they need people to help extract meaning from that data. That’s the role of the data scientist or data analyst. The QuickStart Data Science Bootcamp prepares you to mine, analyze, and visualize data with the Python and R programming languages — as well as use machine learning.
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