Do I Need to Know Computer Programming to Work in Data Analytics?

coding + programming python Oct 26, 2022
A robot writing on a computer. Icons for Python and SAS (computer programming languages).

The Short Answer Is No, But There’s a Lot More to It Than That

The world of data analytics is a fast-expanding job sector. When the employment field is broadened to include positions such as research engineers and machine learning engineers, the growth prospects are even greater, Forbes notes, and the U.S. Bureau of Labor Statistics is forecasting that in addition to rapid employment field growth rates through 2026, wages will also be on the rise.

But while job prospects are good for those in or entering this field, many potential applicants have one major question: Do they need advanced training in computer programming to get a good job? Let’s look at this issue in more detail.

How Much Computer Programming Experience Do You Need to Have to Work in Data Analytics?

Those seeking to enter the fields of data science and data analytics should understand that this is a multidisciplinary field, and one can do quite well without a computer programming background or with a degree in computer science.

That said, knowing some programming will certainly help your odds of landing a great job.

I recommend that job seekers have intermediate or advanced knowledge of at least two computer programming languages. Which ones? For data science, the two most important languages are Python and R, followed by SPSS, SAS, and a few others.

Even if you are about to graduate and do not yet have a programming background, or if you are already in the field but lack these job skills, keep in mind that it is fairly easy to jump online and gain knowledge in any number of computer programming languages.

To Succeed in the Data Analytics Field, Treat Your Ongoing Education as a Life-long Commitment

Keep in mind that to truly succeed in this industry, you will need to keep learning. No matter what sort of education you had, this field is changing and often changing almost overnight.

You do not need to know everything there is to get started – and you will never know everything there is to know about the field. What you need to do is to always keep learning and keep growing – that is what will set you up for a long and successful career in data analytics.

Continuing education is as important in the field of data analytics as it is in any other field in any other industry – and perhaps even more so. Continuing education can increase your chances for a promotion, help increase your salary, make it easier to transition to a new career, improve your image and marketability, and increase your personal development. In the field of data analytics, it also means you remain competitive when compared to other job seekers since you will be up to speed on the latest trends, tools, and technologies.

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