Data Science vs Web Development

1. Web development vs. data science: a comparison On the surface, data science and web development look like an unlikely pair to draw comparisons to one another. After all, what has the science of analyzing and interpreting data got to do with developing images and content on websites, based on the client’s requirements? Yes, data science and web development are far from congenital twins. They can be likened to not even siblings or cousins, but more to neighbors. This is where one understands how different, yet close, one is to the other. They are not related to each other in terms of their nature or their applications, but are closely so in terms of the fact that they are both important players in the technology arena. And yes, being neighbors, they blend into each other at some point, which we will explain later. So, this is the basis on which we should be making a comparison between data science and web development. Just before we go about a little on this area, I would request you to take a look at Simpliv, a learning platform on which you are very likely to explore courses of any technological or non-technological area for your understanding and career enhancement. Let us get going then, on how data science is different from web development: Characteristics: A combination of technology, algorithms and statistics make up data science, which is all used to analyze data. On the other hand, web development is mainly about putting in the right design elements through tools and technologies such as html, CSS, etc. to make the website carry out its functions as the face of the organization. We talked about the convergence between the two. Now, here is where this happens: once an organization’s creative and technological brains create a functional and well- designed website, data science takes over. As businesses become more E-based, data science comes in to analyze the various aspects of the website to help deliver results for the organization. Nature of work: A web developer uses languages such as html, JavaScript, CSS, etc. to develop websites. All the elements of a website, such as UI, user friendliness, layouts, frameworks, etc., have to be made to work together in the right fashion and proportion. So, this involves not only the use of technology, but also a lot of creativity. It also involves coordinating closely with copywriters, content writers, coders, marketers, and so on, so that the website drives business and is very effective from all perspectives. On the other hand, the data scientist is involved in collecting, organizing and analyzing data to see which of it can be useful for the business. The data scientist uses

2. technologies and tools such as Python, R, Hadoop, MATLAB, Hive, and so on. Data visualization, which is mainly about presenting data from an aesthetic and insightful perspective, is a very major component of data science. Prospects: Seen from the perspective of what these two technologies hold for businesses, they are both useful in their own way. While Machine Learning and Artificial Intelligence, both gigantic emerging areas are the mainstay of data science, eLearning and ecommerce, almost equally potential areas for the future, are what the future of web development will look into. Happy reading this article? What do you think of this blog? Feel free to tell us what you think by posting your comments. You could also take a look at some of our courses on data science and web development. Hope this helps!