(IN-PERSON) MCP ❤️ Azure & Conversational BI

This is an In-Person Evening Session

Detailed information and registration can be found here :
https://dataminds.be/mcp-❤%ef%b8%8f-azure-the-real-story-conversational-bi-a-comparison-between-environments-and-key-decisions-to-be-made-in-person-element61/

### MCP ❤️ Azure: The Real Story

Speaker: Chidi Nweke & Konstantin Lazarov

MCP is everywhere right now, but much of the discussion is hype-heavy and light on real engineering. In this session, we’ll focus on what actually changes, what doesn’t, and what MCP genuinely enables in a Microsoft stack.

We’ll look at how MCP on Azure and Microsoft 365 has helped us deliver more with less. You’ll see practical examples of how MCP connects with AI agents with the broader M365 ecosystem. We’ll then dive into how Azure-native tools like API Management can be used to quickly build MCP servers, along with the trade-offs such as cost and flexibility versus creating them from scratch.

Expect architecture patterns, lessons from the field, and a clear-eyed view of what MCP means for AI agents today (and what it absolutely does not magically fix).

### Conversational BI: A comparison between environments and key decisions to be made

Speakers: Artur Tyvaert

Conversational BI is gaining traction as the next big step in analytics. It promises to bridge gaps left by traditional BI by answering one-off questions in a natural Q&A format and adapting to changing business needs. But how should its architecture look, and when do we choose Databricks Genie, Microsoft Copilot, or a custom solution?

In this session, we’ll compare scenarios across key dimensions to answer: “Which conversational BI setup fits which use case?”

• Semantic layers: Power BI vs. Databricks—how they’re built, the role of metric views, and whether YAML-based definitions offer advantages over TMDL.
• Governance: Permissions and security—RLS in Power BI vs. role-based access and data masking in Unity Catalog.
• Environment: Does Genie’s Lakehouse integration give it an edge? What if you already invested in Power BI? How is conversation history handled for user insights?

If you’re new to conversational BI or planning your first implementation, join us to gain clarity on building reliable, scalable conversational analytics.