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Building governed agentic AI with Unity Catalog and Iceberg

By partnering with Databricks to build a universal data layer on Apache Iceberg™ — governed end-to-end by Unity Catalog — Workday transformed a multiplicative data-silo problem into an additive, scalable architecture that brings agents to the data rather than replicating data to agents. Each agent operating with its own independent data store created point-to-point connections that multiplied complexity exponentially.

Agent or tool
Databricks
Topic
Sales & Marketing
Reported on
Case study (Databricks)
Added
2026-11-11

Why it matters

Sales and marketing run on research, lists and follow-ups. Agents are starting to take on that groundwork, freeing people for the conversations that actually close deals. It is one of 613 sightings filed under Sales & Marketing on Agent Sightings (number 388 by interest), and one of 37 involving Databricks.

How you could try it

Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into Databricks or any similar agent and adjust the details to your situation.

I want an agent to do the research and drafting for this sales or marketing workflow, and stop for my approval before anything is sent. The tool in the source case was Databricks.

Saved

Tip: Start small: run it once on a low-stakes example, read what the agent did, and only then let it run on real work.

Source

Read the original first-hand account on Case study (Databricks): https://databricks.com/customers/workday/unitycatalog. Our summary is a paraphrase; details are in the source.

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