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Data science vs web development: What’s the difference?


If you’ve spent any time in the tech community in the last few years, you’ll have noticed the recent explosion in interest in both data science and web development. Young people interested in a career in tech are increasingly turning to careers as data scientists or web developers. 

The importance of web development should be obvious – companies have never been more reliant on their websites and therefore the skills that allow functional, effective, and engaging websites to be built are in high demand. 

Similarly, data has started to become the foundation of the modern digital economy. 98% of organizations say that it’s important to increase their data analysis over the next few years, meaning that more and more people who are able to sort through large amounts of data will be needed. 

However – with both fields growing at the same time – some people get confused between data science and web development. Although there are some similarities, they require different basic skills and involve different duties. Read on to find out the differences between data scientists and web developers – and discover which career suits you more.

What is Web Development?

Web development is all about using your abilities to design websites that perfectly suit the requirements of a business and its users. This will involve technical skills such as programming – if you’ve ever had to ask ‘what is a .env file’, then it’s likely that you’ve had some experience in web development. 

This is called back-end development, which includes using server-side programming languages to manage servers, ensure that data is properly processed, and integrate the right databases for the website – basically, the really technical stuff that makes sure that websites are able to function effectively.

Additionally, web developers often use infographic templates to visually present complex information and data on websites, making it easier for users to understand and navigate.

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Web developers also have to use a range of creative skills to make sure that their websites are visually appealing and engaging. This combines with a knowledge of programming languages such as HTML to produce front-end development, which is the term for any website development that deals with the elements of a website that users interact with. 

Front-end development will also require you to use programming languages such as CSS to style the website, as well as JavaScript to design the user experience. It isn’t all about technical expertise, however, as you’ll have to work together with designers and marketers to make sure that the website is visually effective and appealing. 

Web development is a critical part of bringing websites to life, utilizing technical knowledge, such as the ability to use Python, as well as an awareness of what makes a website appealing to users.

What is Data Science?

While web development has a fairly straightforward definition – it’s anything to do with building a website – data science is a much broader field. Basically, data science is all about collecting and analyzing large datasets in order to allow businesses to make well-informed decisions. 

Think of data science like cooking. Raw data is the equivalent of uncooked ingredients – you can’t do much with a load of raw meat, for instance. It’s the data scientist’s job to turn the ingredients into a delicious meal – or transform a load of complex numbers and information into models and simplified datasets that non-specialists can understand and use. 

As a data scientist, you’ll have to be comfortable with numbers: a strong understanding of statistics and math will allow you to be able to get to grips effectively with variables such as data distribution. You’ll also use software such as a data integration platform to produce analyses of data for your organization. 

Data science vs web development: What’s the difference?

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A lot of the time, data science also involves using programming skills to produce algorithms and models that can interpret and transform data effectively. However, it’s not all about numbers and coding – data scientists have to know how to communicate well with people who have no clue how to work with raw data, as well as present information in an engaging and easy-to-understand way. 

Just like with web development, data scientists are needed across almost all industries – while you’ll need to have a good understanding of tech and statistics, companies in fields as diverse as marketing, healthcare, and finance are becoming increasingly dependent on leveraging data. 

Data science vs web development: Key duties 

Now that you can define both data science and web development, it’s time to build a deeper understanding of what these fields look like in practice. Here are the most important duties of a web developer: 

  1. Website design

It should be obvious that organizations primarily use web developers in order to design websites for their business. Companies will usually have an idea about what they want their site to look like, as well as what functions they want it to perform, and it would be your job as a web developer to make those wishes come true. 

This will mean that you’ll spend a lot of your time programming websites with languages such as HTML, on top of working with designers to ensure that the site looks exactly how your organization wants it to. You might also work on creating content for website alternatives, as these will often require similar skills to website design.

  1. Back-end functionality

Web developers don’t just focus on the parts of a site that users can see – they also make sure that everything is working as it should under the hood. You’ll use your coding abilities to build databases and containers, while also making sure that your websites handle user information safely and securely.

  1. Operational maintenance
Data science vs web development: What’s the difference?

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Once a website is operational, it’s up to the web developers to make sure that it continues to perform as it should. You’ll have to respond to feedback and fix any bugs or errors that are affecting user experience. This will include performing regular tests, using a tool such as exploratory testing by Global App Testing.

While the main duties of a web developer are all related to producing an effective website, data scientists have a slightly wider range of responsibilities:

  1. Data analysis and visualization

Regardless of the specific requirements of your organization or industry, if you’re a data scientist you’re going to have to be able to find patterns and trends in large and often complex datasets. You’ll achieve this by using a mixture of statistical techniques, machine learning, and coding.

As well as using analytics to produce insights into your data, you’ll have to be able to transform these numbers – as well as your findings – into an accessible format through the use of visualization techniques. 

  1. Predictive modeling

When it comes to some of the more specific responsibilities of data scientists, one of the most common is the development of predictive models. These use data to forecast future trends, allowing businesses to stay one step ahead of the curve. 

An example of this might be a marketing company that collects data on how customers interact with their online advertisements. It would be your job to analyze this data and predict how customers with similar profiles will respond to future advertisements.  

  1. Communication and collaboration

One of the most important parts of working in data science is the ability to communicate with members of your organization that aren’t able to analyze and interpret data on their own. This means that you’ll have to create different types of data mart for the different departments in your company, allowing them to visualize the data that is relevant to them.

A lot of the time, you’ll have to use reports and presentations to present some really difficult technical concepts to managers or clients with different skill sets – so effective communication is a crucial part of being a data scientist. 

Important skills for web developers and data scientists

Data science vs web development: What’s the difference?

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If you’re still unsure whether you’d prefer to work in web development or data science, you should consider which set of skills best suit your abilities. Here are the most important skills that employers look for when hiring web developers:

  • Programming proficiency
  • Understanding of web technologies 
  • Database knowledge
  • Troubleshooting and resilience
  • Testing skills and experience

Some of these – such as having a strong database knowledge so that you can answer the question “what is a CDN server?” – are specific to web development, while others, such as the ability to troubleshoot effectively, are also applicable to data scientists. However, employers also look for a specific set of skills when hiring data scientists: 

  • Statistical ability
  • Communication and presentation skills
  • Data wrangling
  • Data visualization
  • Understanding of different programming languages
  • Experience with machine learning and artificial intelligence

Data science and web development – What’s right for you?

There’s no doubt that both data science and web development are incredibly important and exciting fields for anyone with an interest in a career in tech. More and more organizations are investing in these two fields and hiring more data scientists and web developers.

However, there are clear differences between data science and web development. If you’re a data scientist, you’ll have to analyze and visualize large datasets and communicate these findings to non-specialists. Alternatively, web development is all about using creative thinking and programming skills to build websites for your organization. 

You know your skills and abilities better than anyone – using the information in this article, you should now be certain which path is best suited for you.