Data Science vs Software Engineering: Key Differences

We have traveled a long journey in terms of technology. Be it self-driving cars, human-like robots, virtual reality, and augmented reality. But there will always be confusion about choosing between two technologies for study or career. We have come up with an article to answer all these questions.

Data Science and software engineering are two different fields, but both stand up with different aspects. Both have many differences, and the role played by a data scientist is entirely different from that of a software engineer. If you want to know which field suits you, here is the answer for Data Science vs. Software Engineering.

Basics of Data Science and Software Engineering

What is Data Science?

Data science is the field of study that works with massive amounts of data utilizing relevant tools and techniques to derive valuable data. The day-to-day work of a data scientist involves collecting, analyzing, and interpreting this data to help businesses achieve their goals.

Data scientists operate in many different industries. Each has a distinct role in issue-solving and calls for specialist skills. These professions include data preparation, mining, modeling, and model management. 

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What is Software Engineering?

Software engineering is the systematic application of engineering ideas in software development. Planning, developing, creating, and testing the software application to match the requirements are part of the software engineering process.

Software engineering is a comprehensive study of engineering applied to software design, development, and maintenance. Software engineers use a variety of programming languages and tools to design, test, and deploy software solutions. 

Now that we understand the basics of data science and software engineering, here is the answer for Data Science vs. Software Engineering regarding the skills required.

Skills Required in Data Science and Software Engineering

The main objective or focus of a data scientist is remarkably similar to that of a software engineer.A data scientist's main objective or focus of a data scientist is remarkably similar to that of a software engineer. However, the means used to get there are far more diverse. An automated process that eventually benefits the business can be expected from both a data scientist and a software engineer. While software engineers may not work on all of these steps, they are involved in many of them, such as calling APIs, storing data, programming improvements, and model deployment.

Data Science:

Seeing the demand of data scientists in every industry it is obvious that the scope of a data scientist is very high. Let us explore the Prerequisites and Technologies required for a Data Scientist. Skills required will include SQL, R, Python,Jupyter Notebook, Data Analysis, Machine learning algorithms.

Software Engineering:

We all know a software engineer focuses on automation, testing and maintenance of the software. Software Engineers require skills like programming languages (JAVA, Python, C++ respectively), docker, selenium,scrum or agile methodologies.

After learning about the abilities needed for software engineering and data science here is the answer for Data Science vs Software Engineering in terms of salary.

Reward is the result of good work. Now we shall discuss salaries that a Data Scientist will get! It should come as no surprise that data scientists may add significantly to a business. Every step of the process, from data processing to data cleansing, requires persistence, a good lot of arithmetic and statistics, as well as a scattering of engineering skills. One of the most important factors in a data scientist's salary is experience.

At the beginner level, a data scientist makes US$95,000 annually.The typical annual compensation for a mid-level data scientist is between $130,000 and $195,000. A seasoned data scientist typically earns between $165,000 and $250,000 per year, depending on their level of experience.

In India,at the beginner level, a data scientist makes Rupees 9,40,000 on average per year.At mid-level data scientist will get Rupees 20 lakhs per annum and if you are at advanced level you will get paid an average of rupees 25 lakh annually.

This salary will vary in different countries.It is well known that software engineers command high average salaries and that employers want to hire them in huge numbers.

Standard US Salaries

Entry Level: $63,274, Mid Level: $86,561, and Experienced: $129,1M

Whereas in India ,Entry Level is Rs,274k ,Mid-Level ₹561k and Experienced ₹1MSoftware engineers and data scientists are both well-paid jobs with a variety of advantages and difficulty

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Difference Between Data science and Software Engineering

Data Science

Software Engineering

Parameters to be considered - Data Science is mainly about data visualization,different analytical tools and database tools like Mysql,Postgresql and many more.

Examples of visualization tools are Tableau,IBM Watson,google charts, jupyter.

Software engineering includes programming languages, testing tools, IDE’s based on programming language.

IDE’s are based on the type of work one is doing. Visual studio is used for web development,

 Pycharm or Spyder is used if you choose to code in the Python language. In case of Java best IDE would be Eclipse, Netbeans, if you are using c++ then visual blocks,netbeans etc.,

Processing in Data Science - Data science adopts a process-oriented methodology that allows the use of calculations, design acknowledgment, etc.

Processing in software engineering-Frameworks for software engineering include Waterfall, Spiral, agile systems, and more. 

Stages in data science may include Hadoop, MapReduce, Start, Information Stockroom, or Flink, among others.Different stages in data science -  

Different stages in software engineering - Information modeling,business planning, programming, maintenance, project administration, turn around designing, etc. are all stages of the software engineering process.

Data science roles Data Engineer, Big Data professional, data scientist, business analyst, and data analyst.

Release engineers, testers, data engineers, product managers, administrators, and cloud consultants are among the roles in software engineering.

Information about domains, algorithms, processing large amounts of data, data mining, structured or unstructured data, insights, likelihood, AI, machine learning, etc.

Knowledge of the fundamental programming languages, as well as setup, testing, and administration tools.

Next Steps

Now that we know about data science vs software engineering , it's time to become an expert. We recommend that you check Simplilearn’s Data Science Courses and Software Engineering Courses. If you are interested in getting started in software development, then you need to check our Post Graduate Program in Full Stack Web Development. This course can help you hone the right skills and make you job-ready in no time.

Please let us know in the comment section below if you have questions regarding the “Data Science vs Software Engineering" tutorial. Our experts will get back to you at the earliest. 

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Simplilearn is one of the world’s leading providers of online training for Digital Marketing, Cloud Computing, Project Management, Data Science, IT, Software Development, and many other emerging technologies.

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