Most tales of troubled data science projects point to the same concern: the gaping chasm between design and production. While Jupyter Notebooks are great for data discovery and basic design, their solutions hit hurdles when traversing the final mile into production. Stability, data drift, scale, governance, security — all come into question when push comes to shove.

But what if your sandbox were built out of steel? What if the environment for discovery and design were the same environment for production-ready code? That’s the vision of a new trans-Atlantic partnership launched by veterans of Deloitte and DataRobot. Zerve.ai have built a data science platform designed for code-first data teams. How does it work?

Register for this Briefing Room to find out! Host @eric_kavanagh will explain how the chasm first appeared, and why a new solution is needed. He’ll be joined by Zerve co-founder Greg Michaelson, who will show how the separation of compute and storage was their first critical step. He’ll then dig into the details to demonstrate how this platform works:

* Why collaboration is baked in, not bolted on;
* How stability is addressed from the outset;
* What production-ready cloud infrastructure looks like; and,
* Why data scientists will finally get the credit they deserve!