We present Pyrus, a domain-specific online modeling environment for building graphical processes for data analysis, machine learning and artificial intelligence. Pyrus aims at bridging the gap between de facto (often Python-based) standards as established by the Jupyter platform, and the tradition to model data analysis workflows in a dataflow-driven fashion. Technically, Pyrus integrates established online IDEs like Jupyter and allows users to graphically combine available functional components to dataflow-oriented workflows in a collaborative fashion without writing a single line of code. Following a controlflow/dataflow conversion and compilation, the execution is then delegated to the underlying platforms. Both the inputs to a modeled workflow and the results of its execution can be specified and viewed without leaving Pyrus which supports a seamless cooperation between data science experts and programmers. The paper illustrates the fundamental concepts, the employed domain-specific language, and, in particular, the role of the integrated IDE’s in an example-driven fashion which can be reproduced in the available online modeling environment.