Data Science Vs. Software Engineering, Which Is Better?

Terms like data science and big data are relatively new to students looking into choosing a career in an IT field.

Of course, traditional software engineering is still one of the most prospective career choices in the new digital world.

But should you be sticking to it or turning towards data science?

This article explains it all.

Data Science vs. Software Engineering, which is better?

Data Science is better for individuals who want to study machine learning and statistics, but Software Engineering is better for those who want to learn how to code to solve everyday problems. Data Science is regarded to be better because it pays slightly more and is more in demand.

That being said, it depends upon which career choice you find interesting where your only inclination towards data science could be due to a rather unsaturated market, as it’s a relatively new field of study.

So you’ll have more opportunities in terms of growth, jobs, learning experiences, etc.

However, keep in mind that data science can never replace the importance of software engineering in the industry.

Individuals from both fields may have to work together on specific projects for ideal results.

If you choose software engineering, you will probably go through a four-year graduate program with an option to continue studies further in specialized subfields.

The main subjects are mathematics, statistics, programming, logical solution, and more.

As we live in a digital world, software engineers have a high demand in the market, with thousands of job openings coming up every week.

On the other hand, choosing data science can make you a part of the system that’s growing at a rapid pace.

After your four-year graduate program, you can select any technical field of study such as Ecommerce, IT, etc., and specialize in data science to become a data scientist.

The primary subjects include Statistics, Artificial Intelligence, Machine Learning, Mathematics, and more.

The skillset required to become a successful data scientist is diverse, where you may need knowledge from several educational fields to be good at what you do.

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What do Data Science people do?

Data is the new currency where companies earn loads of revenue by exploiting it for their corporate gain.

But this data is only valuable if put through unique practices and analyzed by a professional that’s skilled in the given domain.

That is where a data scientist comes to the rescue. The study, exploit, and analyze data to make it usable in business practices.

For example, if you’re a fan of Marvel movies, you may know the Iron Man’s personal assistant JARVIS. JARVIS was an AI-based program that harvested data from multiple sources, applied mathematical principles to it, and delivered calculated results.

Of course, you can’t be as excellent and efficient as JARVIS, but you can work on making an AI similar to it while pursuing a career in data science.

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What do Software Engineers do?

Software engineering involves creating software with computer tools by applying the various engineering practices paired with logic.

The process may include analyzing requirements, finding optimum solutions, and writing the needed computer code.

Software engineers also spend a lot of their time debugging existing software or testing it for consumer usage.

Software engineers often have a solid grip on various mainstream programming languages.

Since new languages come out regularly, they have to stay up to date to deliver high-quality software. Hence learning workshops and meetings are a common occurrence in a software-engineering-dominated industry. Some common programming languages are C++, Java, Python, and Ruby.

Data Science Or Software Engineer, Who Earns More? (Solved) 

Now let’s talk about the spicy stuff.

In short, Data Scientists earn slightly more around $126,830 per year,  compared to Software Engineers earning $110,140 annually according to a May 2020 report by the US Bureau of Labor Statistics.

As you can see, there isn’t much difference in the pay grade, so you don’t need to worry if you pick either of the choices.

Of course, if you’re picking a specific career, you want to be aware of the financial rewards that accompany your choice.

Luckily, in this case, both options have a lucrative annual pay where data science takes a slight edge over software engineering.

Data Science Or Software Engineering, Which Is Harder? (Must Read) 

Data science is thought to be more difficult since it requires you to be a jack of all crafts, with skills in arithmetic, machine learning, and a variety of other areas, whereas software engineering requires you to learn how to develop software.

However, it depends.

Both careers require technical expertise and many soft skills that can effectively help you deliver the right results.

To help you better understand and make a choice, let’s discuss the skills needed for either career separately.

Technical and soft skills needed for data science are:

• Deep knowledge of the toolkit, including database systems, coding languages, cloud tools, command terminal, etc.

• R Programming fluency

• A firm grip over machine learning practices and AI

• Technical writing skills and communication skills

• Familiarity of business acumen

• Strong interpersonal and team skills

Technical and soft skills needed for software engineering are:

• Logical field of view

• Communication fluency and team support

• Solution-oriented approach

• Adaptable demeanour

• Time management skills

• Deep attention to detail

As evident by the above points, both careers have many interchangeable skills that significantly affect the working nature of the respective field.

You can weigh them out, apply them to yourself and figure out which career would be relatively more manageable for you.

Final Thoughts

To conclude this article let’s recap:

Data science revolves around collecting, analyzing, and processing data, whereas software engineering focuses on developing computer software that brings practicality to the user.

Both careers require strong technical skills and computer knowledge, where programming languages are the most critical component.

After reading this article, we hope that you’re now aware of the many necessary details before jumping into a career choice between data science and software engineering. Cheers!

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