Low Code Data Science: Myth, Reality, and How Organizations Really Use Tools Like KNIME

​Please join Charlottesville Data Science for our March event on the evening of Thursday, March 26. Michael Powers will kick us off with a demo of marimo, a next-generation computational notebook for Python and SQL. Keith McCormick will follow with his talk Low Code Data Science: Myth, Reality, and How Organizations Really Use Tools Like KNIME.

​We'll be gathering in person at UVA's Darden School of Business.

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​About Michael's demo

​Michael will introduce marimo, a next-generation computational notebook and data analysis environment for Python and SQL. marimo addresses many of the perceived shortcomings of Jupyter and similar tools. marimo feels like a notebook, but is stored as a pure Python program that's Git-friendly, reusable as a module, executable as a script, shareable as an app, reproducible in execution and packaging, and designed for data.

​About Keith's talk

​Low-code and no-code tools have been around since the early 1990s. These platforms allow analysts and data scientists to build end-to-end workflows—data access, preparation, modeling, and deployment—using visual pipelines rather than writing code for every step.

​But do data scientists actually embrace them? How are organizations really using these tools? And are they meant for experts—or for “citizen” data scientists?

​In this talk, we’ll step back and look at the current low-code data science ecosystem: what these tools promise, how they work in practice, and the kinds of goals organizations are achieving with them today.

​We’ll spend a few minutes looking at KNIME Analytics Platform as an example—an open-source analytics platform built around visual workflows that integrates machine learning, ETL, and visualization in a single environment, while still allowing Python or R when needed. We’ll also take a quick look at K-AI, which can generate workflows using natural language, and contrast it with other emerging forms of “vibe coding.”

​The goal is to share lessons from real-world use and spark a conversation about where the data science tooling ecosystem may be heading. There will be plenty of time for discussion and questions.

​About Keith McCormick

​Keith McCormick is a data science consultant, author, and instructor with more than 30 years of experience in predictive analytics and machine learning. He currently serves as the Bodily Bicentennial Professor of Analytics at the University of Virginia’s Darden School of Business. Keith has authored books on predictive analytics and created numerous courses on machine learning and AI for LinkedIn Learning. He works with organizations across industries to help teams effectively adopt data science and AI.

​Keith has no affiliation with KNIME beyond being a long-time user of low-code tools.

​Come early for Keith's capstone talk

​The Bodily Professorship in Analytics is a one-year visiting scholar role at the Darden School of Business. Keith will be giving his capstone talk in the same classroom as our event at 4:30 pm.

​Members of the Charlottesville Data Science Community are invited to arrive early to attend the capstone talk. Keith will discuss his experiences at Darden during the academic year and the projects he has been working on.