When collaborating remotely on sensitive data, their usually amazing interactivity and flexibility need safeguards, or whole datasets can be extracted

Jupyter Notebooks Are Not Made for Sensitive Data Science Collaboration

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2023-01-26 07:30:07

When collaborating remotely on sensitive data, their usually amazing interactivity and flexibility need safeguards, or whole datasets can be extracted in a few lines of code.

As data scientists, we adore Jupyter Notebooks. They are wonderful tools that allow us to explore datasets and produce models in a productive way. They are interactive and efficient… But are they the right tool for collaborating on confidential data?

Many real-world use cases involve the collaboration between multiple parties and the sharing of private datasets. Those might contain confidential or sensitive data and should be handled with great care. Which raises the question: are Jupyter Notebooks good tools for collaboration?

Picture this: we are in 2020. What is COVID-19? How deadly is it? How does it propagate? The whole world is expecting results while dissecting every news and misstep of the science community.

One morning, you’re sipping coffee while cleaning a dataset when you get an email: a hospital gathered data about the outcome of their COVID-19 patients. They want a veteran data scientist like you to find patterns between the various features of the data, such as the symptoms, age, and the chance of death, to understand COVID-19 better.