Databricks Data AI Summit is here.
Quest is on-site in San Francisco at booth #105, and this week we’re excited to be part of the Databricks Innovation Showcase.
We’ll be demonstrating how intelligent context for data products can help a business user move from plain-language intent to a fully governed, production-ready data product inside Databricks in minutes.
Unity Catalog governance.
Lakebase transactional tables.
AI/BI dashboards.
Genie conversational experience.
All from a single approved model.
Most Databricks projects don’t fail in the platform. They struggle before the data ever gets there.
Databricks runs the workloads. Quest makes the data usable.
If you’re at the Summit, come see us at booth #105.
Reach Out, Let’s Talk.
#Databricks#DataAISummit#QuestSoftware#AIReadyData#DataGovernance#DataProducts#UnityCatalog#Lakehouse
You can't govern what you can't see👀
Without visibility into your Power BI and Fabric estate, governance becomes reactive, costs increase, and risk goes unnoticed.
Visibility is the foundation of control✅️
#PowerBI#MicrosoftFabric#DataGovernance
Are you sitting on disparate data islands that don't talk to each other?
Most organizations are. And it's quietly sabotaging their AI.
Here's the chain reaction most leaders miss:
Disconnected data → partial picture.
Partial picture → partial truth.
Partial truth → partial answers.
Your AI is only as smart as the data it can actually see. Feed it fragments, and no matter how advanced the model is, it will confidently hand you fragmented answers.
That's the uncomfortable reality of enterprise AI right now:
Companies are deploying powerful models on top of data that lives in silos — different systems, different teams, different formats, none of it connected.
Then they wonder why the output feels generic, shallow, or wrong.
The model isn't the bottleneck. The connectivity is.
I've had the privilege of working with some of the world's most sophisticated data and AI organizations through my time at Microsoft. And I can tell you what the leaders all have in common:
They solved the connectivity problem first.
Before the models. Before the dashboards. Before the AI roadmap.
Because they understood something everyone else learns the hard way:
You can't build intelligent systems on disconnected data.
Is your data working as one system — or a dozen islands? 👇
#ArtificialIntelligence#DataStrategy#DataGovernance#EnterpriseAI#IntelligenceArchitecture
Executives often ask, "Is Copilot secure?"
The better question is, "Is our data ready for Copilot?"
Before organizations can scale AI responsibly, they need to govern the data AI depends on.
Enter: #MicrosoftPurview#AIGovernance#DataGovernance
"Garbage in, garbage out" means that AI is only as good as the data behind it. When data is incomplete, inconsistent, or outdated, AI outcomes become less reliable and business decisions suffer. Learn more: bit.ly/4ouDhw4#AI#DataGovernance#DataManagement
Deploying AI is easy.
That's not the problem. That's the problem.
There are more AI tools available today than any organization could ever implement. Most vendors offer point-and-click, template-based solutions. Any non-technical person can spin one up in an afternoon.
And that's exactly why so much enterprise AI fails.
When deployment is this easy, organizations skip the hard part.
They don't ask:
→ Is our data ready for this?
→ Who's accountable when it makes a wrong call?
→ Does this actually fit how we work — or are we bolting it onto a broken process?
They just… deploy. Because they can.
Easy deployment creates a dangerous illusion: that having AI is the same as winning with AI.
It isn't.
The click is easy. The architecture underneath it is not.
And the organizations confusing the two are the ones wondering why their AI investment isn't paying off.
Deployment was never the hard part.
The foundation was.
Is your organization confusing "we deployed AI" with "we're winning with AI"? 👇
#ArtificialIntelligence#AIStrategy#EnterpriseAI#DataGovernance#IntelligenceArchitecture
the enhanced games teach us that performance without governance is just theater. same with ai. companies chasing model performance while skipping data quality basics will hit a wall hard.
#DataStrategy#AI#FractionalCDO#DataGovernance