05-10, 14:00–14:55 (Europe/Paris), Room 1
Dataflow graphs have become indispensable tools for data science, from ETL batch processes to live streaming data pipelines. A variety of tools exist for constructing and scheduling graphs, but few generic tools exist for visualizing them, and even fewer let you analyze and interact with them from inside a notebook.
Audience: Jupyter - Novice, familiarity with any graph engine recommended e.g. Apache Airflow, Dask, networkx, etc
I am a quantitative developer at Cubist Systematic Strategies and an adjunct professor in the Computer Science Department at Columbia University. My background is primarily in application development with a focus on streaming analytics. I have been involved in the formation of several corporate open source efforts, and am a proud member and maintainer of open source projects in the FINOS, JupyterLab, and Conda Forge organizations.