Data science is a small subset of computer science which deals in the application of computational algorithms and machine learning to data to derive insightful trends & patterns in data which can be used to predict the future & shape business decisions accordingly.
Data science is a science . You use the scientific method : form hypothesis , run experiments ,collect data , build theories , and make predictions. Additionally, good data scientists have an extremely strong math background.
Computer science is not a science in this sense. While some Computer science research involves testing numerical algorithms , it is much closer to pure math. There are some graduate programs pursuing machine learning research; this is new although these programs are nowhere as strong as a traditional computational physics program.
Data science also involves creating new software platforms for analyzing data. Here, there is an overlap between computer science and software engineering.
Data Science vs. Computer Science: The Basics
Let’s start with the fundamental contrasts between these two computer professions. The elder of the two fields is computer science, which dates back hundreds of years. Ada Lovelace, the first “computer programmer,” 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 subject in technology that has risen in popularity as businesses and organizations strive to make sense of the huge volumes of data they collect.
Computer science is the study of how computers work in theory and practice. A Computer Science degree teaches you programming, software, operating systems, algorithms, and anything else you need to know about computers.
Data science, on the other hand, is more interdisciplinary, combining computer science and statistics. Although statistical analysis is not new, the size of the data sets and the processing power required for analysis are.
"Data science is a such a field that teaches students how to analyze and uncover patterns in massive amounts of data.”
Data is gathered (or mined) and examined in data science to find significant insights, trends, or patterns. To process, improve, and show their discoveries, data scientists employ programming languages like R, SAS, Python, and Java, as well as tools like Hadoop, Tableau, and Apache Spark. Mathematical principles and understanding, such as calculus and statistics, are emphasized in Data Science degrees. Other topics covered include machine learning, deep learning, data visualization, and databases.
Data Science vs Computer Science: Job titles
If you’re deciding which field to pursue, it’s helpful to know what job titles you might be qualified for later on in your career. After all, you don’t see many people with the title of a computer scientist on their resumes, so let’s have a look at what’s available. We used real-time data analysis to determine the top job titles for persons having a Bachelor’s degree in Computer Science to assist with this. Software development engineer, software developer, Java developer, systems engineer, and network engineer are the most popular job titles for Computer Science graduates.
Data scientists, data architects, data engineers, business analysts, and data analysts are examples of people who work in the subject of data science.
Data science vs. computer science: Common job duties
Another factor to think about while picking between Data Science and Computer Science as a career path is the type of work you want to conduct. While there is a lot of difference in individual positions in both professions, there are some similar responsibilities shared by both.
• Testing, documenting, and debugging code
• Creating or modifying software and mobile apps
• Designing components of an application and integrating them into a larger overall product
• Collaborating with a team of programmers to build and optimize code are some of the typical computer science-related job duties.
Some job duties of Data science related profiles include:
• Collecting, “cleaning,” and organizing data sets
• building data models
• asking and answering questions using large-scale data analysis.
• Visualizing data and communicating conclusions to stakeholders
Computer science occupations entail creating, changing, and delving into the inner workings of software applications in general. Data science jobs are a little more abstract—they generally involve gathering and analyzing large volumes of data from numerous sources in order to improve a process or answer a question.