Can Data Science Collaboration Be Secure? [New Datalore Case Study]
Working with financial data is not a trivial task, as you can’t just access a production database or a data lake, download the data, and work on it. You have to ensure secure access to the data and produce insights that are easy to share as well.
In the past, TrueLayer had a standalone AWS EC2 machine, which was hard to log into because of multiple VPNs and temporary personal credentials that would often expire. The team couldn’t easily upgrade the size of the instance to work with a larger volume of data. And of course onboarding was a pain for new team members.
“Datalore enabled our team to ergonomically access our data while meeting the security requirements, which was a game changer for us. As a result, we could collaborate much more easily both within our Machine Learning team and with our stakeholders.”
– Moreno Raimondo Vendra, Senior Machine Learning engineer, TrueLayer
Learn how Machine Learning teams organize projects, ergonomically access their data lake, flawlessly carry out live coding sessions, and share data stories, all while meeting the highest security standards of working with sensitive data.
The Datalore team
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