Informational Technology (IT) is an important aspect for businesses to ensure efficient management of their services and operations.
In this industry, you might have heard about two notable Names-Web Development and Data Science. Both are highly important fields that businesses focus on. However, when it comes to choosing a career between the two, many fall into a conundrum.
Which side is the better choice for a business? Also, in a professional capacity, which field offers more opportunities for career prosperity?
Certainly, the fields of data science and web development notice multiple advancements and have their structure. In the context of functionality as well, both are not directly related.
If you are at this crossroad, you should properly understand the job opportunities, features, and market demands common for each route. This article would help you make your decision about which course to pursue.
Brief Overview Of Data Science:
As a field of study, Data Science focuses on integrating programming skills, domain expertise, and mathematical knowledge. Data scientists use statistical analysis to derive usable insights after gathering and interpreting business-centric data.
These professionals hold experience and skills in interdisciplinary technology, algorithm building, and statistics. Typically, data science incorporates the use of machine learning algorithms to compute data like audio, video, images, text, and numbers to create AI systems. These systems can accomplish tasks that take too much time to complete manually.
As a result, many brands hire such certified professionals. They analyze and then utilize a relevant data science trend to enhance the business operations.
Brief Overview Of Web Development:
Web Development, on the other hand, centers around the building and maintenance of websites suited for the intranet/internet. As a discipline, this includes multiple aspects like web publishing, web programming, web publishing, web design, and database management. Web developers learn each of these elements, either exclusively or in a general sense.
A company’s website essentially becomes their main front in front of the customer base. So, they hire a web developer or a team of developers to handle the entire process. Currently, a lot of brands across industries are opting for e-based business routes, like building e-learning and e-commerce platforms. Web developers are useful here.
Web developers build web applications that are accessible via internet browsers into remote servers. Statistically, businesses that use Progressive Web Apps (PWA) save around 75% of their development and maintenance costs.
Data Science Vs Web Development- Key Points Of Difference:
The following are the main differences between Web development and data science.
Web development centers around building a company website suited for intranet/internet platforms, with emphasis on client needs, company information, and technical skills. On the other hand, Data Science involves analyzing raw data with the help of technology and specialized skills.
- The origin of web development dates back to 1999 while data science recently came into focus in 2008.
- Both of these professionals use Python. However, data scientists use it for data analysis while web developers utilize it for website infrastructure building.
- Web Developers do not work with statistics but data scientists do.
- Data Scientists need to use coding skills, but they need to learn and apply other skills as well. However, web developers strictly work with coding for most of their work.
- Web development focuses mainly on meeting the requirements of clients, i.e., what they wish to see on the website. Whereas Data Science centers around the needs of the company more, i.e., insights they need to optimize their performance and services.
- In data science projects, the budget is at a fixed rate but can become very expensive. In the case of web development, the budget varies from project to project, based on the needs, tools used, and additional features.
- Data for web development revolves around consumer interaction with the brand. Data science focuses entirely on business information.
- The time duration for web development projects can stretch long compared to the data science projects.
- Data scientists do somewhat have an idea about web development. However, web developers are not well-versed in data science skills at all.
- Web developers work with analyzing customer-related insights, market data, and some company information. Data scientists focus on interpreting unstructured and structured data mainly.
- In terms of data science, trend options and there is prospects, AI and ML are growing in popularity. Future trends are quite scarce in the web development market.
Data Science Vs Web Development:
Here is a more detailed comparison of the two fields of study. Consider these while choosing your main aspiration behind joining a data science and custom web development company.
1.) Learning Curve
In this field, you would need a high-level educational qualification to apply. To note, applicants must have a Master’s Degree at least to get recruitment from the best companies. Also, many firms hire Stats and Maths-oriented students with a Ph.D.is degree.
Two main languages data scientists must learn are R programming and Python, with the latter holding higher preference among applicants and companies alike. Maximum Deep Learning and Machine Learning (DL/ML) libraries operate with Python frameworks, like Tensorflow.
Additionally, aspirants must have statistical knowledge to prosper in this field as well.
These field of career breaks down into three main types:
- Backend developers- Choose among database options like MySQL, MS SQL, Oracle, Cassandra, MongoDB, Postgres, and more.
- Middleware developers- As a Middleware developer, the main choices revolve around PHP, Java (Spring Framework, JSP, Servlet), NodeJS, Python Flask/Fast API/Django, and Ruby on Rails frameworks.
Additionally, there is the option of becoming a full-stack developer; these professionals are adept in all three distinctions. The salary scope and demand for full-stack developers are at the highest compared to the other three.
2.) Work experience
As a data scientist, you would get the opportunity to gain high profits, relatively more than as a web developer. However, the tasks related to data science are slightly limited.
This field is directly tied to businesses and their operations. Although new trends do crop up in this field, there is not a huge scope for experimentation available here.
These professionals focus on finding the solutions to issues related to customer interests from the brands.
This, in turn, increases the demand for web developers among companies. As someone interested in broadening your career, web development is an interesting choice with high growth opportunities.
Plus, the industry itself is constantly evolving, with the changing demands of customers and the urge of companies to produce something innovative and unique each time.
3.) Job Prospects
The demand for data scientists is high among big enterprises mostly. Smaller companies do not require AI implementation in their products or services. Yet, you would still notice many job prospects if you are planning to work as a data scientist.
However, competition is high in this field, especially because of the huge pay prospects and complex skill criteria. Aspirants that focus more on learning about data science and growing their experience have a higher likelihood of getting hired than those with mediocre skills and experience.
Of course, this is a more generalized opinion. The criteria particular recruiters follow for hiring their employees and the skills that they prioritize are both subjective.
Compared to data scientists, job opportunities are less stringent in the web development field. Large companies, medium-sized firms, and small businesses all need web developers.
The creation of web apps and sites is a high priority for every entrepreneur in the business sector. Thus, you would have chances of getting a job in this field, even with a limited experience level.
4.) Salary Scope
Keep in mind that the figures mentioned here are average cost estimations, with bonuses, overtime pay, and tips included.
The salary opportunities for data scientists are quite high, especially in comparison to web developers. The following are the annual salaries of these professionals, based on their experience level.
- Entry-level data scientists that have worked for less than one year can earn around $85,312 per year.
- Early-level data scientists holding 1 to 4 years of experience can earn $95,033 per year.
- The average salary for mid-level data scientists with 5 to 9 years in the field can earn is $109,696 per year.
- Experienced data scientists are those with 10-19 years of experience; they can earn $122,085 per year.
- Expert data scientists with more than 20 years of experience can earn approximately $136,051 per year.
The following is the average salary structure for web developers, in the context of experience level.
- Entry-level web developers that have worked for less than one year can earn around $50,687 per year.
- Early-level web developers holding 1 to 4 years of experience can earn $58,375 per year.
- The average salary for Mid-level web developers with 5 to 9 years in the field can earn is $67,527 per year.
- Experienced web developers are those with 10-19 years of experience; they can earn $72,913 per year.
- Expert web developers with more than 20 years of experience can earn approximately $81,682 per year.
All things considered, web development and data science are both high-grade fields to pursue professionally. Businesses need and hire both types of specialists. Whether you planning to work in this field or hiring a web developer/data scientist for your company, research further on both routes first.