The Future of Data Science Notebooks Is Collaborative

Explore the evolution and future of data science notebooks in this 34-minute conference talk. Delve into the history of notebooks, from Mathematica's release over 30 years ago to their current status as essential tools for data scientists. Examine the challenges facing modern notebooks, including collaboration, reproducibility, versioning, interactivity, and integration with other systems. Discover how the expansion of data roles and the rise of remote work are driving the need for more collaborative data science tools. Learn about key trends in notebook development, the importance of cross-functional and real-time collaboration, and the potential of collaboration-native tooling. Gain insights into what the future holds for data scientists using these advanced collaborative platforms and the opportunities they present for enhancing productivity and innovation in the field.

Introduction
What is DeepNote
Understand exploratory programming
Extracting insights is messy
Exploratory programming
The perfect tool
literate programming
first notebooks
spreadsheets
Jupiter
Why are notebooks back
How does the future look
Graphic Design
Data Science
The Future
Best Data Driven Organizations