---
title: "Business Context for Your Lakehouse: A Databricks + TQ Deep Dive · Live Webinar · TQ"
description: How do you cultivate a governed layer on top of Databricks using the metadata you already have in Unity Catalog to quick-start your next context management or ontology use case?
---

![tq-logo-tq-ink](https://learn.topquadrant.com/hubfs/tq-logo-tq-ink.svg)

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On-demand webinar

# Business Context for Your Lakehouse

A Databricks + TQ Deep Dive

If your metadata tools still don't stop two departments from arguing whose number or term is right, you're not alone. That gap is common among customers building AI governance on top of their storage layer. 

Databricks is where your data lives--catalogs, schemas, and lineage, all governed well. But lakehouses and catalogs were not purpose-built for managing the lifecycle of evolving business context--the semantic control center that decides whether an answer built on that data is correct. Which is why AI is still sidelined by questions like which definition applies when, what hierarchy does this number roll up through, or who approved the last change?

This session will address how to cultivate a governed layer on top of Databricks with TopQuadrant to quick-start true business context for AI, using the metadata you already have in Unity Catalog.

Watch now. 

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**76+** data leaders registered

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20-40%

More content discovered, from consistent classification

What you'll learn

## Built for industries that can't be wrong. Scaled for those that choose to be right.

This session will review areas where Databricks customers are layering in a context management platform built for the job.

How to turn the metadata already sitting in your Unity Catalog into a quick-start for context management or ontology work, no rip-and-replace required

Two real-world patterns from finance and pharma showing how enterprise teams close the gap between "the data is governed" and "the data means the right thing"

What changes when business context (definitions, hierarchies, code sets, approvals) is authored once and consumed everywhere, instead of reconciled by hand downstream

Where Databricks and TQ Data Foundation each carry the weight and why regulated industries treat that division as non-negotiable

Speakers

## Meet your speakers

![team-amar](https://learn.topquadrant.com/hubfs/team-amar.webp)

### Amar Doshi

Head of Product

Amar Doshi leads the Product and Delivery teams at TopQuadrant, where he is focused on helping enterprises establish governed semantic foundations for AI-ready data. With deep expertise in enterprise data governance and industry experience honed at Deloitte Consulting, Amar works closely with customers operating in highly regulated industries such as pharma, financial services, and government, navigating the shift from fragmented reference data to authoritative, reusable enterprise context. He is a frequent voice on the intersection of knowledge graphs, AI readiness, and the evolving role of semantic infrastructure in modern data architectures.

![Brenda Cass](https://learn.topquadrant.com/hubfs/Brenda%20Cass.jpeg)

### Brenda Cass

Product Manager

Brenda is a Product Manager at TopQuadrant, working on the company's context management platform across ontology-backed solutions. Brenda's role focuses on helping organizations turn fragmented semantic assets into a governed data foundation that human and AI systems can depend on to provide authoritative context.

Brenda holds an MS in Information Technology from Rensselaer Polytechnic Institute, a hub for semantic research. Before TopQuadrant, Brenda held roles at GE and EBSCO, building hands-on experience with the commercial applications of data science, architecture, and engineering.

![steve-hedden](https://learn.topquadrant.com/hubfs/steve-hedden.jpg)

### Steve Hedden

Solutions Engineer

Steve’s expertise is at the intersection of developing products and demonstrating technical value for the TopQuadrant Data Foundation platform, focusing on practical applications of semantic context for AI using knowledge graphs. Steve previously led product initiatives at S&P Global, where he built ontology-backed systems at Fortune 50 scale. Steve is a member of the W3C Advisory Committee, helping to champion open standards and interoperability so that customers can own their own context and future-proof their data and AI architecture.

![Laurie-Nelsen-topquadrant-solutions-engineer-mayo-clinic](https://learn.topquadrant.com/hubfs/Laurie%20Nelsen%20Headshot.jpeg)

### Laurie Nelsen

Sr. Solutions Engineer

Laurie helps customers build technical and business solutions to enable enterprise context. She has a background in library science and information architecture. Before joining TopQuadrant, Laurie was a Sr. Ontologist at Mayo Clinic, and brings her practical expertise in life sciences (early adopters of semantic data systems) to enterprises building their ontologies, taxonomies, knowledge graphs and semantic layers.

Agenda

## 60 minutes. No filler.

Cultivate a governed layer on top of Databricks using the metadata you already have in Unity Catalog to quick-start your next context management or ontology use case.

0:00

### Welcome + speaker intros

6:00

### What Databricks governs well vs. the business-context gap it leaves open

18:00

### How TQ Data Foundation adds authored, versioned, audit-ready context on top of Unity Catalog metadata

30:00

### Two real-world patterns: finance and pharma

42:00

### Live Q&A

Why TQ

## Why organizations trust TQ

Two decades of enterprise semantic infrastructure, built before "knowledge graph" was a buzzword.

53+

Enterprise customers, including Fortune 500 life sciences, financial services & media

20yrs

Building enterprise semantic infrastructure

50%

Average reduction in data-wrangling time reported by pharma customers

3×

Improvement in terminology-management efficiency at a leading healthcare org

Testimonials

## From teams who've done it

The people who turned scattered semantic assets into governed, AI-ready context.

> "We had ontologies, terminology files, and metadata standards scattered across 12 teams. TQ turned it into something we could actually govern and build on."

David A.

Corporate Data Architect, Fortune 100

> "This went far beyond the usual webinar. No fluff, just the real questions answered directly. It reshaped how we think about our data assets."

Sarah B.

Head of Data Governance, Major Bank

> "Within six months, our AI teams stopped asking where the authoritative definitions lived. That alone was worth it."

Marcus A.

VP, Data Infrastructure, Global Enterprise

Live · Sept 17 · 12:00 PM ET

On-demand · 60 min

## Build Business Context for Your Lakehouse

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