How can you use Java effectively for real-time data visualization?

Java is a powerful programming language since it has fast compiling capabilities as opposed to python which is an interpreted language and this characteristic makes Java particularly relevant for real-time data processing and visualization, there are many libraries in Java which can be used to visualize data and they are absolutely stunning in terms of aesthetics and functionality like JFreeChart which is an open-sourced library for creating a wide variety of charts ,JavaFX charts is a part of JavaFX library providing a rich set of charting components to create interactive and responsive charts , XChart is light weight easy to use library to create interactive charts, so Java has efficient data visualization capabilities for real time data

Java is a very powerful programming language which can be written for one platform and can be executed on multiple other platforms with minor tweaks. Portability of the code and logic from Windows to Linux. Jave provides a rich set of UI libraries for data presentation for data visualization.

Writing applets with not many rich controls is a major road block for java in terms of data visualization. It can drastically lower the performance of the reports and the data load times.

Java is actually an excellent means to scrape your data from the web. I use Selenium, which is an open source browser automation library. Here's what you can you do with Selenium: - You can go to any number of URLs, scrape the data and dump it into an excel (using Apache POI). You can later use this data to create a live or extract connection to your dashboard. - If your dashboard is hosted as a web page, or embedded on a web UI, you can create test suites in Selenium to perform smoke test or any kind of automated UI validation. For both of the above examples, you can setup a Jenkins pipeline which will schedule a job that runs your java code as frequently as you like.

Java has awesome capabilities of parallel processing, which has greatly evolved since its birth around 27 years ago. It started from Threads and Runnables, then arrived Callables and ExecutorService, then parallel streams made it very quick to convert sequential processing to parallel processing, and now the recent addition of Virtual Threads has made parallel processing highly optimized and fast. So you can easily read from multiple data streams simultaneously, transform them simultaneously, and write to multiple data streams simultaneously. From where the frontend tools, developed in any technology, can read and show them in the form of visualizations according to different business needs.