Abstract: 

This year, OpenAI and ChatGPT, have boomed as popular tools for data and idea generation. With the generative power of these tools, a critical inspection of the resulting data grows in importance. Is the data valid for the use case? What aspects of the data may be harmful or a poor fit for the problem to be solved? Exploring and answering these questions will drive greater adoption of notebooks to make this new technology accessible to larger groups of people.

Notebooks with an elegant combination of prose, visualization, and code open the door for greater understanding and introspection of data. The ability to explain the data through words and illustrative charts provides a foundation for anyone to understand and critically reason about data and its application. While other tools like an IDE or BI tool provide artifacts, the notebooks compose information in a way that is greater than the sum of individual parts and enable more people to experiment and take action. The future is notebooks.

Background Knowledge:

Audience should be familiar with data notebooks.

Bio: 

Carol Willing is the VP of Engineering at Noteable, a three-time Python Steering Council member, a Python Core Developer, PSF Fellow, and a Project Jupyter core contributor. In 2019, she was awarded the Frank Willison Award for technical and community contributions to Python. As part of the Jupyter core team, Carol was awarded the 2017 ACM Software System Award for Project Jupyter's lasting influence. She's also a leader in open science and open-source governance serving on Quansight Labs Advisory Board and the CZI Open Science Advisory Board. She's driven to make open science accessible through open tools and learning materials.