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Data Science vs Web Development

Difference between Data Science and Web Development

Investments are crucial for individuals and businesses. They lessen the risk in our lives and act as a cushion in times of need. When it comes to businesses, investments are not just financial but also the ones made of its employees i.e. building teams and image building. There is a quote by Warren Buffet which says-“Someone’s sitting in the shade today because someone planted a tree a long time ago.” True to this quote, businesses have to invest in today to reap the benefits tomorrow. Going by recent trends, we will be discussing two types of investment Data Science and Web Development.

Data Science is the interdisciplinary science if data analysis using statistics, algorithm building, and technology. With recent Data Science trends like Machine Learning and Artificial Intelligence, more companies want to invest in a Data Science team to understand their data better and make wise decisions. Web development is the creation of a website for the internet or intranet. Since a website is the face of a company, it is necessary for companies to invest in one. Also, Web Development companies need to match their skills with the coming trends as businesses have become more E-Based i.e. E-Commerce and E-Learning. This, in turn, is a driving factor for setting up Data Science teams in businesses

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Head to Head Comparison between Data Science and Web Development (Infographics)

Below is the Top 8 comparison between Data Science and Web Development:

Data Science vs Web Development Infographics

Key Differences between Data Science vs Web Development

  • Data Science is the process of analyzing data using specialized skills and technology whereas Web Development is the creation of a website for the internet or intranet using company details, client requirement, and technical skills.
  • Data Science is a relatively new concept having been introduced in 2008 whereas Web development has been around since 1999.
  • Python is used by both Data Scientists and Web Developers. However, in Data Science it is used for analyzing data whereas in web development it is used in creating a website.
  • Data Science uses coding widely but also includes other elements whereas the whole of Web Development is based on coding.
  • There is statistics involved in Data Science whereas in Web Development there is no use for statistics.
  • Data Scientists try to answer business related questions at the end of the analysis whereas Web Developers try to cater to the client requirement while building a website.
  • Data Science depends on the availability of data whereas Web Development depends on close interaction with the client to understand needs and to get the required information.
  • The budget for Data Science is steep but is fixed whereas the budget for Web Development keeps changing with the changing requirement and the additional features.
  • Data Scientists work for a shorter period of time on data to get results in comparison to Web Developers who take a long time to launch a website.
  • Data Scientists work with structured and unstructured data whereas Web Developers work with Company information.
  • With the coming of E-Commerce, Data Scientists have an understanding of websites whereas Web Developers do not possess the skills to work with data.
  • There are a lot of future trends in Data Science like Machine Learning and Artificial Intelligence whereas not many trends in Web Development.

Data Science and Web Development Comparison Table

The differences between Data Science and Web Development are explained in the points presented below:

Basis For Comparison Data Science Web Development
Coining of Term DJ Patil and Jeff Hammerbacher who were employees of LinkedIn and Facebook respectively gave the term Data Science in 2008. The term was popularized by Tim O’Reilly and Dale Dougherty in late 2004. It was initially coined by Darcy DiNucci in 1999.
Concept It is a combination of statistics, algorithms, and technology to analyze data. It is the creation of websites for the intranet which is a public platform or the intranet which is a private platform.
Coding Coding is used widely to feed the computer with commands to analyze data and give the end output. The entire process of web development involves coding.
Languages Recommendations C/C++/C#, Haskell, Java, Julia, Matlab, Python, R, SAS, Scala, SQL, Stata Photoshop, HTML, CSS, JavaScript, JQuery, PHP, Python, Ruby
Statistics Uses statistics to a certain extent. Uses no statistics
Work Challenges
  • Data Science results are not used in business decision making.
  • Inability to apply findings into organizations decision-making process.
  • Low clarity on the questions that need to be answered with the given data set.
  • Unavailability or difficult access to data.
  • Data Security is of top priority.
  • Need to coordinate with IT.
  • The client requirement is never clear and keeps changing till the end site is launched.
  • Need to work closely with a client for site content and requirement.
  • Need to coordinate with IT
  • The budget for the web site building keeps increasing with more features. So no set budget.
  • It takes time to launch a new website.
  • Security factors have to be considered before launching.
Data Needed Structured and unstructured data. No data is required. Only company details is required for web site.
Future Trends Machine Learning and Artificial Intelligence. E-Commerce and E-Learning

Conclusion

Careers are built based on the passion, drive, skills, and opportunities that a person has. In the case of the comparison between Data Science and Web Development, both are in trend and provide students, fresher and experienced professionals a lot of scopes to learn. Data Scientists need to have a sound understanding of statistics and computer science. Coupling this with the voluminous data at hand that the different verticals generate every day, Data Scientists have the opportunity to explore different data sets and help businesses forecast their data to get valuable insights.  Data Science openings are the most sought after openings of today. Web Development, on the other hand, is taking slow steps but the end product of creating a website is fascinating and thrills many. With websites acting as platforms for businesses i.e. E-Commerce, the latter has been a driving factor for the setting up of Data Science Teams. Data Scientists are experts at working with Internet-based data. The comparison of these Data Science and Web Development work areas cannot be done except for a few similarities. However, both Data Science and Web Development keep up with trends and offer great opportunities. 

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