PreCon: Governed Finance AI on Databricks - From Data to Variance Agents

This full-day pre-conference workshop shows how to build an end-to-end financial intelligence solution on Databricks using a realistic financial variance-analysis use case. Participants will begin with ingestion of source financial and operational data, then build a medallion architecture that produces trusted, reusable finance data products for reporting, analytics, and AI workloads. The session will cover Delta Lake design patterns, Delta Uniform for broader data interoperability, and Unity Catalog controls that protect sensitive financial information through attribute-based access control (ABAC).

From there, the workshop moves beyond the platform foundation. Participants will create governed business metrics for actual-versus-budget and period-over-period variance analysis, expose those metrics through Genie Spaces for natural-language exploration, and build AI agents that can investigate material variances, retrieve supporting evidence, and prepare analyst-ready explanations. The session will also cover how to maintain traceability, apply approval boundaries, and ensure that AI-generated insights remain tied to authorized data and approved financial definitions.

Attendees will leave with an implementation blueprint and practical patterns for moving from fragmented finance data to governed, AI-assisted variance analysis on Databricks.

Mou Rakshit

Avanade, Intelligent Data Platform Data Engineering Thought leadership

Mou Rakshit is a Senior Manager of Data, AI & Analytics Engineering at Accenture/Avanade and a Principal Data & AI Solution Architect specializing in building modern, unified, AI-ready data platforms using Microsoft Fabric and Databricks. She leads enterprise-scale data strategy and platform architecture initiatives that enable organizations to move from fragmented analytics environments to governed, high-performance lakehouse ecosystems.

Her work focuses on designing scalable medallion architectures, implementing robust governance models, enabling real-time intelligence, and operationalizing AI and advanced analytics across the enterprise. Mou bridges executive strategy with hands-on technical execution, ensuring that modern data platforms are production-ready, resilient, and aligned to business outcomes.

She holds a Master of Science in Computer Science from Wayne State University and a Master’s in Health Services Administration from the University of Michigan.

A Databricks Champion and frequent industry speaker, Mou shares practical frameworks and real-world lessons on architecting unified data foundations that power AI at scale.
https://www.linkedin.com/in/mourakshit/
https://credentials.databricks.com/profile/mourakshit34507/wallet

Please drive thru Marshall Ave to park in Lot B and use the West Entrance - both circled in green in referenced parking diagram. A complimentary parking voucher will be provided to event attendees.