These two tech occupations have some similarities. If you're interested in any of them as a career option, it's crucial to understand the differences. While web development has been popular for decades, data science is a newer field.

The latter utilizes multiple disciplines to perform accurate data analysis. It also exploits new trends such as machine learning and artificial intelligence. As more companies build data science platforms to take advantage of these emerging technologies, this career will witness increased demand.

Web development involves the creation of websites to act as the virtual representation of a company. Modern solutions such as e-learning and e-commerce platforms require multiple integrations to meet customers’ needs.

A Comprehensive Comparison Between Web Development And Data Science

In addition to the definition above, we can compare the two fields in the following ways:

• While both use coding, web development utilizes it in the entire process. Data science applies programming only while inputting computer commands and providing output.
• Both use the Python programming language. Coding and database options for data science include C, C++, C#, Matlab, Julia, Haskell, Java, Scala, R, SQL, and Stata. Tools and coding languages associated with web development are CSS, Photoshop, HTML, Ruby, PHP, JQuery, and JavaScript.
• While data science relies on statistics, web development doesn’t.
• Data science utilizes both structured and unstructured data, while web development only requires company details.
• Both occupations present unique workplace challenges. With data science, you attempt to solve business queries after an analysis. However, it’s not always clear the kind of questions that the available data sets should address. Most web developers have to cope with unclear client requirements and general delays.

Comparison Between Web Development And Data Science Jobs

We can make comparisons between the two tech jobs using these three parameters:

1. Salary

Data scientists earn more than web developers. That's because their profession involves relatively complex and in-demand concepts such as machine learning and AI. According to Glassdoor, the current average base pay for data scientists is $115,506 per year. Associated job titles include data analyst, data scientist intern, and quantitative analyst.

Web development is an older occupation, so there's a steady supply of professionals to meet the demand. However, it's still a marketable job with fast-evolving concepts. Glassdoor places their average base salary at $69,633.

2. Career prospects

Data science skills are applicable in several industries, including insurance, computer systems design, scientific research, consulting, cable programming, and financial institutions. This flexibility makes it a highly marketable course with long-term career prospects.

Web developers are also in demand due to the many apps we utilize daily. Although they earn a lower beginner salary than data scientists, remuneration depends on various factors. They include your field of specialization, experience, company policy, and additional tech skills.

3. Learning curve

Creating a data science platform is a complex undertaking that requires advanced knowledge. The learning curve is high, with most companies hiring Ph.D. candidates with a thorough grasp of mathematics and statistics. This occupation also requires proficiency in programming languages, the most essential being Python and R. Python is also vital for emerging technologies such as machine learning.

There are three types of web developers:

• Front-end developers: These professionals have a deep knowledge of HTML, JavaScript, and CSS. An understanding of React, Angular, or Vue is an added advantage.
• Middleware developers: This level requires fluency in at least one of various programming languages. They include PHP, Java, Python, Ruby on Rails, NodeJS, and .NET (ASP).
• Back-end developers: These experts focus on mastering databases, including Oracle, MySQL, MongoDB, and MS SQL.

Most web developers concentrate on one programming language, framework, or database. A full-stack developer is someone who understands front-end, middleware, and back-end tech.

Other Differences Between Data Science And Web Development

Data science usually has a fixed budget because the parameters are clear. That’s not the case with web development because the cost keeps changing due to market demand for new features.

Individual web development tasks also tend to last longer than data science assignments. It takes longer on average to create a website than to perform data analysis.

Although it gained popularity in the early 2000s, web development is already a time-tested profession in the tech world. So long as you have the necessary skills, it’s easy to hold a steady job.

Data science is preferable if you enjoy experimenting and learning new concepts. It may not be as creative as web development, but its scope offers exciting future opportunities.

Conclusion

Data science platforms and web development are fast-evolving tech fields. They also utilize massive resources through free and paid courses, as well as boot camps. Your preferred option between the two depends on factors such as passion, skill acquisition, and career prospects. While they have some overlapping aspects, they also have clear distinctions. Ultimately, the choice depends on which one interests you more.