Data Science vs Computer Science What Is the Difference?

Some people believe that data science is more or less the same thing as computer science. In this article, we will take a closer look at the overlapping areas and the specific differences between the two.

Here are the topics covered:

1. What is Data Science?
2. What is Computer Science?
3. Is Data Science Part of Computer Science?
4. 5 Main Differences Between DS and CS
5. Who Should You Hire and When?

What is Data Science?

Data science is a discipline that combines programming skills, domain expertise, and knowledge of statistics and mathematics to obtain meaningful insights from data. Data science practitioners use machine learning algorithms to produce artificial intelligence (AI) systems. They apply these algorithms to images, text, numbers, audio, video, and more. In return, AI systems generate insights that analysts can translate into tangible business value.

Data science aims to optimize algorithms and manage the tradeoffs between speed and accuracy. Experts will work together with data scientists to achieve a balance between assumptions and results. It has valuable benefits in business, research, and our everyday lives. By sifting through massive lakes of data and looking for connections and patterns, data science brings us new products, delivers breakthrough insights, and makes our lives more convenient.

What is Computer Science?

Computer science is the study of computer architecture, its design, and its application in science and technology. The hardware part of computer science deals with the basic structure of computers and their working process. On the other hand, the software part of computer science studies programming concepts and languages. Besides hardware and software, computer science also deals with operating systems and compilers.

The primary areas it covers include numerical analysis, computer systems and networks, programming language, artificial intelligence, the theory of computing, bioinformatics, and software engineering. Unlike data science, which rests on uncertainty and approximation, computer science relies on symbolic logic.

Is Data Science Part of Computer Science?

Data science is a branch of computer science that analyzes different types of data: structured, semi-structured, and unstructured. It employs several technologies to read this data, such as data mining, data transformation, and data purging.

Though data science is a part of computer science, it covers less computer discipline and expects a more in-depth knowledge of mathematics and statistics. It involves studying the historical trends and using its conclusions to redefine present trends and predict future ones.

5 Main Differences Between DS and CS

A working understanding of programming languages and algorithms is a must in both fields, but what one does with that understanding is the primary differentiation between the two tracks. Computer science focuses on the "how," while data science looks at the "why." Here we have listed the five key differences between the two.

Basic Concepts

Computer science is a field that has been developing for decades. It is an umbrella that covers many areas. Sub-disciplines include computer architecture, data structures, programming languages, software engineering, web design, database development, machine learning, algorithm development, and artificial intelligence.

On the contrary, data science is a more focused field that centers on one thing, and that is big data. Occasionally, data science and CS seem to be the same, but they have different end games. Computer scientists generate software that data scientists use, while data scientists apply that software to identify trends and find significance through statistics.

Career Options

If you're looking to choose which area to study, it helps to know about the job titles you'd likely qualify for in your career. The most common job titles seeking a Computer Science degree are software development engineer, software developer, Java developer, systems engineer, network engineer, and computer programmer. Those who work in data science may have titles such as data scientist, data architect, data engineer, business analyst, data analyst, statistician, and business intelligence analyst.

Job Duties

In general, computer science jobs revolve around modifying, building, and understanding software applications' inner workings. Data science jobs are a bit more abstract. Their work often focuses on improving a process or answering an unknown by pulling together vast information from multiple sources and analyzing it.

Some standard computer science-related job responsibilities include:

• Testing, documenting, and debugging code
• Creating or upgrading mobile apps and software
• Designing elements of an application and integrating them into an overall product
• Cooperating with a team of programmers to build and optimize code

Typical data science-related job tasks are:

• Building data models
• Collecting, cleaning, and organizing data sets
• Creating data visualizations and presenting conclusions to stakeholders
• Resolving issues with large scale data analysis

Salaries

Today, data scientists make more than computer scientists on average. This is due to the high demand for professionals who can handle the growing amounts of data businesses generate. The national average salary of data scientists in the United States is $113,309. A computer scientist is likely to receive an average remuneration of $107,086.

Real-World Applications

Data scientists can analyze customer behavior patterns to help a company form products and services that meet customer demand. Some specialize particularly in this type of business analytics. For instance, on streaming services such as Netflix, data scientists build an algorithm that predicts what shows you will like based on your former viewing history.

Computer science has led to higher data efficiency. With computerized financial systems, banks and investors operate more effectively. This year has brought a new area of development for computer scientists - remote work. Cloud computing systems and project management platforms, for example, allow employees to work remotely without sacrificing productivity or the ability to communicate.

Who Should You Hire and When?

Companies collect a ton of data, and much of the time, it's neglected or underutilized. Data scientists ensure that you use this information to make critical business decisions and drive significant success. They have a vital and high-demanding role that can impact a company's ability to achieve its goals, whether they be financial, operational, or strategic. Therefore, it is of utter importance to hire a top-notch data scientist because they can sometimes inadvertently cause financial loss.

As we've already mentioned, computer scientists develop mathematical models that can serve as interactive tools between computers and people. They specialize in various branches, one of which is cybersecurity. In today's remote work environment, having a cybersecurity specialist has become a necessity. Businesses and individuals are highly exposed to malicious intrusions from hackers, malware, spyware, and other dangerous hacking methods. With a cybersecurity specialist, your networks, computer systems, and websites remain secure.

Conclusion

Hopefully, by now, you've learned to differentiate data science from computer science. Here are some key points from the article in case you've missed them:

• Data science is the combination of three fields: data engineering, mathematics, and statistics.
• Data science is centered on the extraction of clean information from raw data to formulate actionable insights.
• Computer scientists develop and analyze algorithms to solve programs and study the performance of computer hardware and software.
• Computer science is the main branch, while data science is a branch of computer science.
• While data science is a relatively new field in technology, computer science dates back hundreds of years.
• Computer scientists generate software that data scientists use. Data scientists apply this software to identify trends and find significance through statistics.
• Career options as a data scientist are data scientist, data architect, data engineer, business analyst, data analyst, statistician, business intelligence analyst.
• Career options as a computer scientist are software developer, Java developer, systems engineer, network engineer, computer programmer.
• Currently, data scientists, on average, make more than computer scientists.
• Data scientists help a company design products and services that meet customer demand. Computer science has led to higher data efficiency.
• It is crucial to hire the best data scientist, as they can sometimes cause financial loss.
• Hire a cybersecurity specialist to ensure the security of businesses and individuals exposed to intrusions from hackers, malware, or spyware.