@ericka-lorenz , thanks for this helpful practitioner-oriented summary, I feel it important to add a couple of small footnotes.

Based on the public Databricks partner-program pages, certifications clearly matter, though partner tiering seems to run on a broader Partner Value Score model. Databricks lists a few other inputs alongside certifications, including:

• use cases
• joint customers
• sourced revenue
• CSAT
• public customer reference stories

The new Bronze, Silver, Gold, and Platinum structure is real. Databricks just tends to describe advancement through the tiers as a holistic, merit-based system tied to customer impact, consumption, commitment, strategic services adoption, and GTM readiness, so it might be worth reading tier as one signal among several.

On the credential side, the public learning pages draw a nice distinction between accreditations and certifications. Databricks presents them as separate credential types. The accreditation pages describe accreditations as non-proctored assessments, while the certification pages label certifications as proctored, in case that helps anyone sorting out which is which.

So if it's useful, I'd lean toward framing certifications as a major input rather than the whole story, and maybe soften any absolute wording around what tier alone can tell you about delivery quality. Either way, your core takeaway still holds for me: the logo matters, and so does the actual delivery team, their experience, and their relevant specializations.

Helpful sources:

• Partner Program | Databricks
• Introducing the new Databricks Partner Program and Well-Architected Framework for ISVs and Data Prov...
• Databricks Certification | Databricks

Regards, Louis