Data science and software engineering both are highly technical domains but both fields have some similar skill sets. The application area of data science and software engineering is quite different. Well, it depends on your choice which area of study you like the most, but for a rough comparison about data science and software engineering, we will discuss their ins and outs in this article.
Data Science vs. Software Engineering
Data science and Software engineering both known as high-package salaries. Both fields require programming skills, but what is the main difference. Data science is more specific to collecting data, gather and analyze and then making decisions. On the other hand, Software engineering focuses on developing different applications, features and functionality for users.
Most big companies such as Apple, Netflix, Airbnb are selling digital products to customers and serving millions of end-users. Both data scientists and software engineers are main supporting pillars of the digital era.
Software powering application for these products and make them functional, innovative and bug-free. The data which is collected by using these products are needed to store, collect, analyze and interpreted, which is equally important as developing software.
In the technology era of 2020 and beyond, both fields will play an essential role in reshaping the world. Both data scientists and software engineers getting high package salaries because of increasing demand for their job titles.
Let’s have a look at some big differences between both fields.
When it comes to methodologies, a data scientist’s work is to extract data, analyze and then transform it into useful information. The data science job isn’t simple because it is a mixture of different operations. A data scientist is responsible for collecting and analyzing data, while data analytics make sure to make right models by using a programming language. Sometimes a data scientist performs all functions alone.
On the other hand, Software engineers are responsible for developing software by using a method called SDLC. This process includes designing, implementing, testing, developing, deployment and maintenance.
A data scientist uses many tools for data analytics, data visualization, data collecting, machine learning, and modeling. For data analysis and investigation, they probably use Amazon S3, My SQL, MongoDB, and so on. For modeling, their choices are unlimited; they can work with Scikit-learn or Stat models.
Whereas, software engineer uses some other type of tools for developing, designing, and analysis. They perform many functions such as testing, programming, web application and much more. Usually, they use Text Wrangler, Emacs, Vim, and Visual Code Studio. Despite your job responsibilities, you are responsible for using best tools to perform your job.
Data scientists and software engineers need to continuously update their skills because as new technology evolves, they need to learn new skills.
To be a data scientist, a student should have a good command of at least one or two programming languages, machine learning, statistics, and data visualization. As you get more experience, you need to learn more skills, but these are the basic prerequisite for an entry-level data scientist job.
Nonetheless, a software engineer must know about different programming languages to develop programs. In addition, software engineers must have problem-solving skills. Working as a team player and eager to learn in broad aspects are additional qualities to work in the data science industry.
Is Data Science Harder Than Software Engineering?
Both jobs are considered as high technology fields, but they require different skill sets. Each job is necessary to solve technological complexities and business world problems. Both jobs require different methodology, tools and skills.
A common thing between them is use of programming language to make models. A big difference between these jobs is their final products.
A software engineer is responsible for developing software, applications and design systems for platforms.
A data scientist is responsible for digging insight, analyzing, modeling, predictive algorithms, visualizations and making data-driven decisions.
Summing it up:
Well, we explain major difference between a data scientist and a software engineer. Now it’s up to you. What do you think is data science harder than software engineering?
Both fields are lucrative, job-promising and need a continuous learning process. If you want to pursue a career as data scientist join best data science institute in Hyderabad and earn data science certification course in Hyderabad to be a part of this huge industry.
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