Data Science vs. Data Analytics

A few years ago, it was predicted the number of job listings in data analytics and data science would grow to 2.7 million in 2020 (this year!). And just recently, Linkedin named Data Analyst as one of the top 10 jobs with the most number of openings globally.

What’s the Difference? Data Analytics VS Data Science?

A few years ago, it was predicted the number of job listings in data analytics and data science would grow to 2.7 million in 2020 (this year!). And just recently, Linkedin named Data Analyst as one of the top 10 jobs with the most number of openings globally.

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So what’s the difference between the two career paths, and which one is right for you? Let us explain in very simple terms.

Alright! So very simply, a data analyst’s job is to look through data to see trends and communicate what stories the numbers are telling. A data scientist both interprets and figures out ways to model the data. Data analysts more likely use off-the-shelf tools while data scientists sometimes build their own tools.

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How would you know which one is for you?

If you’re interested in our Data Science Fellowship, you might already have a background in programming, statistics, or a STEM-related field. Be prepared to learn how to code. If you’re new to working with numbers, data analytics is more your jam. No coding is involved and you start with the Data Analytics program we offer.

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What will I actually learn?

If you join our Data Analytics Bootcamp program to learn analytics, you’ll be focusing on how to use different tools like SQL and PowerBI, how to analyze,and present data using visualizations. You’ll build projects around different types of data by working with a mentor and peers. You will be asked to present and articulate your results.

On the other hand, the Data Science Fellowship will start with coding in, a deep dive in statistical analysis, and big data techniques including machine learning. Data science is all about the context and domain it’s applied to, so you’ll spend time creating projects in hackathons. By the time you graduate, you will have the full skillset to start a data science career.

Both programs are offered on part-time learning schedules with 15-20 hours of commitment per week. In both cases, you’ll be paired with a Mentor.

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