Many STEM degrees have overlapping characteristics. For example, you can’t get very far into an applied engineering degree without learning a fair amount of mathematics. In the same way, it can be difficult to get far in data science without the aid of computer science along the way. But even though many of these education tracks develop similar characteristics and skill sets, there can be significant differences between job prospects. If you’re trying to differentiate between Data Science and Computer Science, begin by asking as few pertinent questions.
Isn’t Data Science just a Branch of Computer Science?
No, data science isn’t just a branch of computer science. Both data science and computer science have a great deal of integration, each is its own distinct field. Broadly speaking, computer science involves studying the theory and practice of modern computing, and often includes a repertoire of various coding skills and languages. That would include everything from software to the operating systems they run on, and to the base hardware that interacts with the OS.
Part of the reason why data science can appear to be a branch of computer science is because both careers can involve similar tasks. This is especially true with data analysis and programming. But common computer science career tasks might include things like testing for bugs in code, creating apps, or optimizing existing code. The majority of computer science jobs lead to various aspects of software development.
Is Data Science and Computer Science the Same?
Comparing data science vs computer science requires making a few fine distinctions. For starters, computer science programs aim to provide students with a wide base of foundational knowledge around computing. Students need a background in science, math, reasoning, and analysis. That’s in addition to a core curriculum surrounding networking, databases, programs, coding, and the overall design principles.
Data science and computer science often look similar because they can require similar skills. For example, both may learn programming languages like Python or Java. But computer science students would be more interested in the theoretical background behind which those languages operate, while data science students are only using tools provided by computer science in order to analyze metrics. As such, data scientists may need a passable proficiency in those tools, but not the same level of dedicated expertise that you might see with a professional programmer.
The difference between data science and computer science can be harder to spot on an undergraduate level. A degree like the Bachelor of Science in Computer Science tends to provide a broad understanding of a field, opening the way to a broad range of career options and educational paths. It’s only at the postgraduate level where you’ll find more obvious differences because graduate studies typically involve more specializations.
An MS in Computer Science program might further develop the graduate’s knowledge in algorithms, applied development, performance remodeling, and so on. A computer science master’s degree program would allow you to specialize further into AI, database management, computer graphics, computing performance, data analytics, software engineering, and so on.
What is Data Analysis in Computer Science?
It’s challenging to compare data analytics vs computer science because they share considerable overlap. In the context of computer science, data analysis involves modulating data requirements appropriate for data collection, processing, cleaning, and exploratory analysis. Basically, a data analyst takes a data source, and uses the data to create a story. These stories are visualizations that effectively convey information.
In computer science careers, that might mean using inferential statistics to create mathematical models that match the data. Data analysis can mean something else entirely in the context of data science, where collected data has to be separated and examined, and breaking down data into useful parts allows you to use it for testing ideas and theories.
Some people compare career paths like data science vs programming because both require analysis and programming experience. But data science careers have a far greater emphasis on analytical elements, while programming has a far greater emphasis on developing proficiency working with multiple programming languages.
Data science vs information systems is another common comparison, since both can be involved in data management. But the distinction requires understanding the difference between data scientists and data engineers. A data engineer is involved in creating and maintaining data infrastructure that keeps clean and relevant data coming in. By contrast, working in data science tends to be more focused on pulling insights out of collected data, which may or may not be cleaned or ordered. Tools like Power BI and Tableau transform data and help people understand it better.
Which is Better Data Science of Computer Science?
The answer will largely depend on your career goals, personal interests, and how far you want to take your education. Computer science takes a broader view of computing, which involves learning a wide range of skills. That confers it one potential advantage over a data science degree, a wider array of career options. Conversely, for those interested in data science careers, having a data science degree can be a distinct advantage.
It’s worth noting that while BLS data suggests a majority of computer science occupations require a Bachelor’s degree. Data science careers are similar, but more clearly favor postgraduate degrees for senior level management positions. You might want to learn more about what data analytics careers look like.
As far as personal interests are concerned, computer science tends to involve learning more about software-hardware relationships, which often leads to careers in coding or network management. By contrast, data science is more about finding ways to structure and analyze data, especially unstructured or partially structured data. And working in analysis careers requires critical thinking and insight to a higher extent than other fields.
Can You Become a Data Scientist with a Bachelor’s Degree?
Yes, but conditionally. Data science requires a strong background in mathematics, statistics, foundational knowledge in database construction, and proficiency in at least one or two programming languages, like Python. That means many kinds of bachelor degrees can be an avenue towards data science careers, even those which aren’t specialized into data science.
However, becoming a data scientist requires proficiency in a wide range of skills related to modeling data. Many of them are specialized to specific fields, like learning to create effective visualizations to communicate highly complex information to stakeholders who lack technical skills in those areas.
Many people enter into data science careers with a bachelor’s degree. But lacking a postgraduate degree, like the Master of Science in Data Science, can make it more challenging to find employment, and it can affect your prospective for career advancement.