Data Science vs. Computer Science: Which Path to Pursue?September 18, 2022 2022-10-30 12:17
Data Science vs. Computer Science: Which Path to Pursue?
The tech industry is booming. It has stood the test of time and proven not to be a bubble as predicted. With the ballooning promises that the industry has to offer, keeping up with various niches within the industry can be a little bit challenging.
Some of the roles and careers in tech are very similar and drawing out a difference could be a daunting task. Data science and computer science are two of the most similar roles in the tech industry. These roles are often mistaken to be more or less the same thing. But are they?
Computer science and data science go hand in hand. However, there is a vast difference between the two. This article looks at data science vs. computer science, how the two roles differ, and the special similarities between the two.
Are you contemplating a career in either field? Keep on reading to discover the difference and gain some clarity on which path to follow. Let’s get started.
What is Data Science?
Data Science is the study of data to identify patterns and get useful information from the data. It involves the exploration and analysis of data to draw information and insights used to make future predictions.
Data Science is an interdisciplinary field comprising computer science and advanced statistics. It involves techniques such as data mining, data cleaning, data exploration, data analysis, data visualization, model development, and deployment.
Data is mined and analyzed to draw valuable insights, patterns, and trends. The field mainly uses python, R, and SPSS programming languages to process, analyze and visualize their data.
Roles of Data Scientists
Here are some of the tasks a data scientist is expected to perform day in day out:
- Device data collection process for new data
- Explore current data available
- Clean, query, and understand the company data
- Explore data in a data frame and perform exploratory analysis to understand the data
- Understand the business question to which answers are being sought and determine the impact of the model/algorithm on the business
- Develop models to cater to the business challenges at hand
- Deploy the developed model
- Visualize data and report on the results of the model.
What is Computer Science?
Unlike data science, computer science has been around for ages. You probably have heard of it over the past few years.
Plainly put, computer science is the study of how computers work. It is the study of computer design, architecture, and its applications. It includes the study of both the hardware and software part of a computer.
Computer science is majorly software engineering. However, computer scientists can easily fit as database administrators, system analysts, web developers, network architects, and hardware engineers.
Roles of computer scientists
Here are the major roles of a computer scientist:
- Define and understand the requirements of the problem at hand
- Understand the business process
- Understand and design the system and software
- Test, deploy and implement solutions
Data Science vs. Computer science: Difference
While data science draws a lot from computer science, there are several outright differences between the two fields.
- Computer science mainly focuses on the computer structure, design, and architecture. The main emphasis is on the hardware and software design.
Data Science on the other hand majorly deals with data, data structures, and algorithms. A major part of what data scientists do is to analyze data, identify patterns, draw insights and make future predictions.
- Computer scientists have a background in computer engineering while data scientists have a background in mathematics and statistics.
- Computer scientists are more on automation and object-oriented programming while data scientists are more focused on data analysis, data visualization, and algorithms.
- Computer scientists mainly work with system users to simplify and automate systems while data scientists mainly work with product managers and other business-facing roles to advance the business while leveraging data and data analytics.
Data Science vs. Computer Science: Similarities
There are a lot of similarities between data science and computer science. Both careers have a lot of similar roles. They are often cross-functional. Here are the similarities between Data Science vs. Computer Science:
- Both careers require a deep understanding of business processes and their products. Computer Scientists must understand the business process in order to automate and simplify systems. Data scientists must also understand the business process to build algorithms that improve the business process.
- Both roles require a good background in computers. Computer Scientists majorly focus on computer design, structure, and architecture while Data Scientists must have a deep background in computers in order to build and deploy algorithms.
- Data Science and Computer Science are scientific processes. Both roles follow a systemic approach to the scientific process.
- And finally, both roles are cross-functional. Both data scientists and computer scientists can start in the other respective role and easily switch to the other.
Starting and Succeeding in Your Tech Career
Both Data Science and Computer Science are lucrative careers that could offer you a lot of self-satisfaction. Let us examine how to start and succeed in your data science and computer science career:
How to Succeed in Data Science
Data Scientists are majorly business oriented. They work with business executives to understand business goals and build algorithms to advance the business. Data Scientists examine how available business data can be used to make business predictions and inform business decisions.
To succeed in Data Science, you must first understand business processes and how to use data to improve business. You must be flexible and open to new ideas. You must also be innovative and capable of providing unique solutions to business problems.
You must also develop a stronger understanding of consumer behavior and how to use data to further customer satisfaction. Finally, you must have good soft and relational skills as you’ll work with a lot of people from different departments.
How to Succeed in Computer Science
Computer scientists are majorly code-oriented. They focus on simplifying business processes and systems. They are majorly involved in writing code, creating applications, and developing websites. They also help in network administration and system management.
To succeed as a Computer Scientist, you must have the ability to translate theory into application. You must provide practical solutions to business problems. You must also simplify systems for users.
Honing on several programming languages is an added advantage for you as it avails you several ways to solve problems.
Finally, other than tech skills, you must also ace your Soft and relational skills. This allows you to easily relate with your colleagues and helps you to explain your solutions to business problems.
Data Science vs. Computer Science: Salaries
Both fields are very lucrative. In fact, both fields pay almost twice as much as the average salary in the US. However, data scientists make a little bit more than computer scientists. This is due to the high demand for data scientists by businesses.
Businesses have shifted from making speculative and intuition-based decisions. They are gradually moving to data-backed decisions hence the demand for professionals who can handle business data.
The average salary paid to data scientists is about $116,000 per year compared to the $103,000 paid to computer scientists. However, both fields are cross-functional and you can easily double up as both a data scientist and a computer scientist.
Start Your Tech Career
Tech is the career of the present and the future, that’s for sure. With the advancement in technology and new developments day by day, the industry is meant to last. It is no longer a bubble as earlier predicted.
The tech industry is very lucrative and rewarding. And that’s just the beginning. A career in tech is definitely the right step into the future: whether Data Science or Computer Science.
Well, that’s it. We hope our data science vs. Computer science comparison helped you draw clarity on that matter. Are you contemplating a career in tech? We could help you with that. We offer informative courses to help you kick-start and build your career. Check our courses section or get in touch to get started.