While you may be captivated by the universe of possibilities presented by the rising IT business, keeping up with the profession and its various specialized skills may be difficult. Data science is one topic that has sparked a lot of interest in the community.
You may be aware of computer science and the interesting programming careers connected with it if you work in the area, are a self-taught coding specialist or are simply interested in technology—but where does data science fit in? Is one better than the other for aspiring technologists?
We’ll compare data science with computer science in this essay to help you make sense of it all.
Basics
- Consider the fundamental differences between these two computing jobs. Computer science is the more ancient of the two, dating back hundreds of years. The first “computer programmer,” Ada Lovelace, lived in the early 1800s, more than a century before the first modern computer was built. Data science, on the other hand, is a relatively new technological area that has emerged as firms and organizations attempt to make use of the massive amounts of data they collect.
- Computer science is the study of the theory and practice of how computers work. A Computer Science degree teaches you programming, software, operating systems, algorithms, and anything else you need to know to run a computer.
- Students studying computer science learn programming languages such as Python, JavaScript, and Java, as well as the fundamental ideas that allow these languages to function. School teaches operating systems, networking, security, algorithms, and computer architecture. Overall, computer science is concerned solely with computers.
- Data science is an interdisciplinary field that combines statistics and computer science. Although statistical analysis is not new, the size of data sets and the processing power required for analysis are.
- Data science is a subfield of computer science that teaches students how to analyze and uncover patterns in huge volumes of data.
- Data is obtained (or mined) and studied for important insights, trends, or patterns in data science. Data scientists use computer languages such as R, SAS, Python, and Java, as well as technologies such as Hadoop, Tableau, and Apache Spark, to process, augment, and present their findings. Data Science degrees focus on mathematical principles and understanding, such as calculus and statistics. Machine learning, deep learning, data visualization, and databases are also covered.
Job titles
If you’re trying to determine what to study, it’s a good idea to be aware of the job titles that you might be able to qualify for later in your career. After all, you don’t see many people with the job title computer scientist going to work, so let’s shine some light on what’s available. We used real-time data analysis to determine the most popular job titles for people with a Bachelor’s degree in Computer Science.1 The most popular job titles for those with a Computer Science degree are: software development engineer, software developer, Java® developer, systems engineer, and network engineer.
People that work in the field of data science include data scientists, data architects, data engineers, business analysts, and data analysts.
Education needed
Before you enter either of these fields, you should look into the amount of schooling required. Both data science and computer science occupations require postsecondary education, but let’s take a closer look at what employers are looking for in candidates.
A Bachelor’s degree in computer science is most certainly required to be a competitive candidate in the job market. According to the Bureau of Labor Statistics, software developers, one of the most common computer science-related jobs, typically demand at least a Bachelor’s degree.
Data science positions, on the other hand, usually demand additional education beyond a Bachelor’s degree. According to our survey of data scientist job ads, employers were mainly looking for individuals with at least a Bachelor’s degree—and 31 percent of job advertisements were looking for persons with a Master’s degree.
Knowing what education is required for your ideal employment will help you decide where to begin. A data scientist may require more study hours than a software developer or programmer with a Computer Science degree. Because there is considerable overlap in subject matter, an undergraduate degree in Computer Science may be an appealing alternative for aspiring data science specialists.
Key Differences Between Computer Science and Data Science
- Data Science is the study of mathematics that includes ideas such as Statistics, Algebra, Calculus, Advanced Statistics, and Data Engineering, to name a few. Computer Science is the study of computations that includes subjects such as Data Structures, Algorithms, Computer Architecture, Programming Languages, and so on.
- Computer Science teaches us about processor design and operation, as well as memory management in programming domains. Data Science teaches us how to use data to analyze how data will be kept, processed, and transformed to minimize redundancy and make it valuable for future use.
- Computer Science teaches us about the operation and applications of computer technology. Data Science is the study of how to extract information and knowledge from various sorts of data.
- Computer science subfields include computations, probabilistic theories, reasoning, discrete structures, and database design. Data Science includes, among other things, simulation, modeling, analytics, machine learning, and computational mathematics.
- Computer science is the main branch, whereas data science is a subset of computer science.
- Data Science is concerned with the safe processing of data, whereas Computer Science is solely concerned with the successful development and use of computers.
- Data Science is all about data, whereas Computer Science is focused on computation.
- New concepts in computer science are being developed, and more efficient and advanced gadgets are on the way. Data is getting increasingly difficult to manage and keep track of on a regular basis.
- Algorithms are important to computer science, with a focus on software engineering and development. Data Science is the synthesis of three disciplines: data engineering, mathematics, and statistics.
- Computer science is involved with scientific problem-solving methodologies. Data Science is concerned with data organization and processing.
- Computer Science has various research disciplines in which to study and flourish, but Data Science research areas have recently changed and expanded, giving us more options.
