Turning Notebooks Into Collaborative And Dynamic Data Applications With Hex

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Notebooks have been a useful tool for analytics, exploratory programming, and shareable data science for years, and their popularity is continuing to grow. Despite their widespread use, there are still a number of challenges that inhibit collaboration and use by non-technical stakeholders. Barry McCardel and his team at Hex have built a platform to make collaboration on Jupyter notebooks a first class experience, as well as allowing notebooks to be parameterized and exposing the logic through interactive web applications. In this episode Barry shares his perspective on the state of the notebook ecosystem, why it is such as powerful tool for computing and analytics, and how he has built a successful business around improving the end to end experience of working with notebooks. This was a great conversation about an important piece of the toolkit for every analyst and data scientist.
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
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Introduction and Guest Introduction
Barry McCardell's Background and Introduction to Python
Early Career and Consulting Experience
Motivation Behind HEX
Challenges with Traditional Data Sharing Methods
Excel vs. Notebooks in Data Analysis
Primary Consumers of HEX
Evolution of Notebooks and Roadblocks
Popularity and Intuitiveness of Notebooks
Limitations and Innovations in Notebooks
HEX's Affiliation with Jupyter and Other Platforms
Implementation and Core Features of HEX
Workflow from Analysis to Interactive Web App
Parameterization in HEX vs. Papermill
Comparison with Streamlit
Dependency Management and Data Integration
Comparison with Other Notebook Platforms
Trends and Future Directions in Notebook Ecosystem
Interesting Use Cases of HEX
Lessons Learned in Building HEX
When HEX is Not the Right Choice
Future Plans for HEX
Contact Information and Picks
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