Marius Moscovici

Every organization that wants to talk to its data hits the same wall: the AI needs semantics, and the default plan is to build a universal semantic layer from scratch.

Implementing conversational analytics shouldn't be a gamble. This session replaces theory with tactics, offering a roadmap to turn AI into enterprise-grade solutions. We will walk through a production-ready project plan, a proven reference architecture, and a demo of the capabilities that separate enterprise-grade solutions from prototypes. Leave with the exact framework you need to launch and prove the ROI of your AI for BI investment.

Every BI platform now includes AI—from Microsoft Fabric CoPilot to standalone chatbots. Yet without a unified strategy, these tools create fragmented user experiences and governance risks.

Implementing conversational analytics shouldn't be a gamble. This session replaces theory with tactics, offering a roadmap to turn AI into enterprise-grade solutions. We will walk through a production-ready project plan, a proven reference architecture, and a demo of the capabilities that separate enterprise-grade solutions from prototypes. Leave with the exact framework you need to launch and prove the ROI of your AI for BI investment.

Most “ask your data” initiatives fail to move beyond impressive demos. The gap between proof-of-concept and production-ready AI analytics solutions is littered with broken promises and burned stakeholder relationships.

When it comes to BI Governance, everyone talks a good game, but very few deliver the goods. Instead, most organizations present their users with reporting systems that are littered with obsolete, duplicative, and unused reports.

Poor governance of reports, data, and ETL leads to significant hidden costs in most organizations. Companies are spending excessive amounts on database and BI usage, while at the same time BI end-user experience is suffering, and engagement is low.