💻 Generative AI for Decision Intelligence: Building Agentic Analytics Systems from Business Data

AI is changing the interface to enterprise data—and with it, what analytics engineers need to design. Reliable data models and metrics still matter, but AI systems also need business context, tools, orchestration, validation, and clear boundaries around what the model can decide.

In this hands-on workshop, participants will extend a traditional analytics workflow into a small decision-intelligence system. Using a realistic business scenario, we’ll connect an LLM to structured data and tools, separate deterministic logic from model reasoning, and progressively build the surrounding components needed to move from a business question to useful decision support.

Key takeaways:

1. Understand how analytics architecture changes when AI becomes a consumer of enterprise data.
2. Design the boundary between data logic, business rules, tools, and LLM reasoning.
3. Build the surrounding AI layer—context, orchestration, validation, and human checkpoints—that connects analytics to decisions.