Hands-On Industrial Internet of Things

Interactive analytics

Interactive analytics represents a combination of queries, a user interface, and a core for the analytics. It is not possible to define the best method or technology to implement interactive analytics. The best suggestion is to keep the core of the analytics in a shared library and to develop the user interface with a small micro-app that uses a common framework such as Power BI, Google Data Studio, Python-based libraries such as Dash, Bokeh, or D3.js (https://d3js.org/), or R-based libraries such as R shiny (https://shiny.rstudio.com/). Alternatively, we can use more advanced tools such as Jupyter (http://jupyter.org/) or Apache Zeppelin (https://zeppelin.apache.org/).