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How can we create small data teams that do extraordinarily great work amongst themselves? Can they have tight peer review amongst themselves, but also the ability to peer review across the organization? Can we make sure they’re able to show their work off to stakeholders in extremely high fidelity?
These are the challenges that I think about solving as the leader of a data org, and I’m so extraordinarily happy that Hex is helping me tackle them.
I can suddenly have an analyst sitting in a room and facilitating an interactive conversation with a stakeholder. I can have a data scientist updating and iterating things in real time, and not getting lost in the complexity of a platform or deployment pipeline.
And they’re not just talking through slides, where there’s a painfully slow feedback loop to explore deeper or change anything about an analysis. Our work becomes interactive assets that people are actually able to look at, and able to look at together.
Hex lets us easily create these assets and publish them out to the entire organization so folks can actually benefit from our research.
The best part about Hex for me is what it enables within the data team.
Hex makes it so easy to have constructive conversations about the data work we're doing. There’s commenting, versioning, and document management built right into where we’re working, so we can do peer review the right way. We can leverage software engineering best practices, and still have the live document right in front of us the whole time.
Giving the data team a better tool to work in that can increase the fidelity of the conversations they’re having has improved their work immeasurably.
Because Hex projects are discoverable, reproducible, and accessible, there’s a positive feedback loop that emerges. Someone sees an extraordinary piece of work that was done, and thinks “wow, I really want to do that”— and then they can!
That ability is the “Oh My God” moment of Hex for me.
The reproducibility and self documenting nature of Hex projects gives people the ability to not just have traceability of their own projects as a way to know that the work is right, but to see others artifacts and learn how to do their own work even better.
And to be inspired to build new extraordinary things.
David Riordan, VP of Data and Insights