Most enterprise data projects don't stall because of the technology. They stall because of the foundation underneath it.
A pilot on Databricks can be running in weeks. Then the questions start. Who has access, and why? Which team owns what? What does it cost, and who decides? Can a mistake in development reach production? Without clear answers, promising pilots stall at scale.
In this series we walk through what a production-ready Databricks deployment looks like. It is written for the people who sign it off, not only the people who build it. One phase per article, in the order you would actually build.
The roadmap: 10 phases, in build order
- Identity: who gets in.
- Workspaces: how teams stay separated.
- Unity Catalog: who sees what.
- Network: how data travels.
- Storage: where your data lives.
- Delta Lake: why you can trust it.
- Infrastructure as Code: how it stays repeatable.
- Compute and cost: what it costs to run.
- Observability: know before your users do.
- High availability and disaster recovery: what happens when things break.
How each article works
Every phase comes down to one question an executive team should be able to ask, and get a clear answer to. Each article follows the same structure:
- The question for leadership: the one thing to ask your team.
- Where it goes wrong: the patterns we see most often in practice.
- The building blocks: what a solid setup looks like, based on Databricks' own guidance and our project experience.
- Four checks: a short list you can tick off without opening the platform.
New phases are added to this page as they are published.
Which phase is your blind spot?
Start with the phase you have the least clarity on today. Want an outside view on where your platform stands? Get in touch with Ferdinand on LinkedIn.