Session
Panel: Reimagining Data Analytics with GenAI: Patterns, Platforms, and Pitfalls
Generative AI is redefining how organizations design, build, and consume analytics. This panel unpacks the patterns that matter—retrieval-augmented generation, vector search, agentic workflows, and NL-to-SQL—showing how they integrate with modern data platforms, semantic layers, and governance. Practitioners will share concrete case studies: accelerating data engineering, automating documentation and testing, enabling natural-language exploration, and embedding copilots into BI and operational decisioning. We will also examine the pitfalls: data quality and lineage in an LLM world, cost management, evaluation and observability, security and IP protection, and responsible-AI controls. Attendees will leave with actionable guidance: architecture blueprints, build-vs-buy criteria, and operating models to move from pilots to production while maintaining trust, scale, and ROI.

Mihail Mateev
Senior Solution Architect at EPAM Systems, Soft Project, Owner
Sofia, Bulgaria
Links
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