When it comes to web development and data structuring, two acronyms frequently come into play: HTML and XML. Both are integral to the world of information exchange on the internet, but they serve distinct purposes and have fundamental differences. In this article, we'll dive into HTML (Hypertext Markup Language) and XML (eXtensible Markup Language) to explore their characteristics, use cases, and key disparities. What is HTML? HTML, or Hypertext Markup Language, is primarily used for creating web pages and defining the structure and content of a web document. It is the backbone of web development and is responsible for rendering the visual representation of a web page in a web browser. Here are some key characteristics of HTML: Semantic Markup: HTML is designed for structuring content and conveying its meaning. It provides tags like <h1>, <p>, <ul>, and <a> to format text, create lists, and hyperlink content. Predefined Tags: HTML has a predefined set of ta

Data Science, Data Analysis, and Data Engineering: What's the Difference? Data science, data analysis, and data engineering are all closely related fields that involve working with data. However, there are some key differences between these three disciplines. Data Science Data science is a broad field that encompasses the collection, analysis, interpretation, and presentation of data. Data scientists use a variety of tools and techniques to extract insights from data, including machine learning, statistical analysis, and visualization. Data scientists typically have a strong background in mathematics, statistics, and computer science. Data Analysis Data analysis is a more focused field than data science. Data analysts use data to answer specific questions or solve particular problems. They typically use a variety of tools and techniques, such as SQL, Excel, and Tableau. Data analysts typically have a strong background in mathematics, statistics, and business. Data Engineering Data