Data Science vs. Computer Science: Comparing the Fields

A comparison of data science versus computer science reveals key differences between the two fields, such as their areas of focus. Data scientists collect, process, and analyze data to provide insights. Computer scientists explore the technical concepts and components behind the software and hardware that make technology work.

Though professionals in data science and computer science have different responsibilities and educational paths, their fields do share some similarities. For example, both are high-growth fields at the forefront of the digital economy. According to the World Economic Forum, data science roles like big data specialist and computer science positions such as software developer are experiencing much faster job growth than other occupations.

What Is Data Science?

Data science brings together math, statistics, programming, and artificial intelligence (AI) with a focus on specific techniques such as data analytics. Data scientists employ the tools of these disciplines to turn raw data into useful insights that can guide decision-making and shape long-term business and policy strategies for organizations. To do this, they utilize a multistep process that involves collecting, structuring, and evaluating data and then sharing their findings in clear ways that others can use.

What Is Computer Science?

Computer science’s primary focus is designing and improving computer technology. However, the discipline also involves creating algorithms that help with complex technical challenges and make systems faster and more efficient. Computer scientists incorporate information technology, programming, robotics, engineering, hardware design, and computer architecture into their work.

The Similarities: Data Science vs. Computer Science

A data science versus computer science comparison reveals there is significant overlap between them. In fact, professionals in the two fields work together to make information useful, turning it into practical tools, insights, and solutions. The following are some similarities data science and computer science share.

Skills and Qualifications

Data science and computer science professionals need similar foundational skills to perform their work, including programming, analytical thinking, logical reasoning, math, problem-solving, and communication capabilities. They often apply these skills in different ways, however. For example, data scientists often use programming for statistical analysis while computer scientists who become software engineers use programming to create and improve systems.

Education

The typical minimum education requirement for data science and computer science roles is a bachelor’s degree in an area such as computer science, engineering, or math. In both fields, employers often prefer candidates with a master’s degree for senior-level roles.

Job Outlook

Both fields are expected to see strong growth in the coming years. The U.S. Bureau of Labor Statistics projects that positions in data science will increase 34% percent between 2024 and 2034, while positions for software developers will grow 16% in the same period. Both of these rates are much faster than the 3% expected growth rate for the labor market as a whole.

Degree Program Length

While the amount of time it takes to complete a degree program can vary from one institution to another, particularly at those schools with accelerated or part-time program options, graduate degree programs in computer science and data science usually require the same amount of study.

The Differences: Data Science vs. Computer Science

While data science and computer science roles require some similar skills, the professionals who fill these roles apply them in very different ways. Data scientists focus on using data to find insights and help with decision-making. Computer scientists create and improve computer technology and systems, performing tasks that range from hardware architecture maintenance to app development.

A data science versus computer science comparison shows that the job titles, responsibilities, and programming applications are different for each field, as are the degree program curricula.

Job Titles

In data science, common titles include data scientist, data architect, and data analyst. In computer science, job titles vary widely depending on the specialization of the work and include software developer, computer programmer, and computer and information research scientist.

Responsibilities

Data scientists use statistics to uncover problems and opportunities. They collaborate with stakeholders to make sense of the results and share their findings through models and visuals. Computer scientists build technology — they write and test code, fix problems, and create software and applications that help businesses and customers.

Programming Applications

Programming serves different purposes in data science and computer science. Programming in data science applications — typically in Python, R, or SQL — focuses on performing statistical analysis and data manipulation. Computer scientists use their programming skills, combined with their understanding of algorithms and architecture, to develop software, systems, and applications. Both data scientists and computer scientists, however, use programming for AI and machine learning applications.

Degree Program Curricula

Data science degree programs focus on computational methods for working with data, covering topics that include statistical inference, machine learning, visualization, and big data management. Computer science degree programs cover computation theory, algorithms, data structures, system architecture, networking, and software engineering. Electives in these programs can offer opportunities to specialize in a specific area, such as software development or cybersecurity.

Prepare for a Data Science Career

As data volumes continue to grow — driven in large part by the power of artificial intelligence — professionals in the fields of data science and computer science will continue to work hand in hand. Data scientists will rely on the algorithms, systems, and architectures that computer scientists develop to analyze patterns, identify trends, and extract value from raw data.

For those interested in the rapidly evolving data science field, Tseng College at California State University, Northridge, offers a Master of Science in Data Science degree program that is designed to equip students with the concepts, techniques, and tools needed to address complex data challenges and pursue a range of diverse career opportunities. The program’s curriculum spans data analytics, data engineering, mathematics, statistics, machine learning, and other areas of data science to help students gain the skills they need to succeed.

Find out how CSUN’s data science program can help you unlock new career opportunities in data science.