In the simplest terms, data visualization refers to how we represent our data with visuals like charts, graphs, and so on. It is the representation of data in graphical format, usually a mapping or a relationship between data points and lines of a chart or graph. Generally, it entails designing the right visual interface for our data.
The form of the visualization usually depends on the relationship between the chosen graphical elements or types and the data points involved. The end goal is to communicate information derived from data sources clearly and effectively via visual or graphical means.
Data viz, as it is sometimes called, is particularly useful to help us tell stories about our data and, in the process, understand the representation of a large set of data point at a glance. Essentially, representing data in an aesthetically pleasing and easily consumable way are the major goals of data viz.
We’ll compare their pros and cons, key features and functionalities, philosophy, and so on. At the end of the day, the goal is to understand why we might pick one of these visualization libraries based on their available features and our particular use case.
Now let’s highlight these libraries in turn below
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
An extensively researched list of top microsoft big data analytics and solution with ratings & reviews to help find the best Microsoft big data solutions development companies around the world.