Data Visualization in R and Python

Part IIIWeb Dashboards

A web dashboard represents the conclusion of a journey into data visualization projects being the final step of a pipeline started with static graphics and moved to interactive ones, which are clearly already web oriented.

Dashboards are actually true web applications, composed by several elements and functionalities, integrating different technologies and methodologies, whose complexity could easily grow fast. In short, web dashboards combine data science visualization with web applications in a coherent and usable way. That is great when effective, but it requires different skills, the necessary amount of practice, and a lot of attention to detail. However, with patience and method, everybody could learn to design and build good web dashboards, provided that the fundamental skills have been acquired. It may take some time, but it is feasible, be confident about this.

From data science, dashboards inherit data import, wrangling, and visualization to feed them with data-oriented informative content. From web applications, instead, dashboards make use of web technologies, remote connections and provision of pages, and web standards for interoperability and content layout. Dashboards should also be deployed into a production environment, be it on the open web or in corporate intranets, for the content provision to many simultaneous user accesses. This brings typical problems of scalability and reliability of web applications that web dashboards have to ...