Modern Data Lakehouse & Audit-Driven ELT: Breaking Data Silos & Leveraging AI for Accounting Risk Analysis was a technical-business session focused on how modern data lakehouse architecture can improve analytics, governance, and auditability. The ACEC 2025 Finance Forum presentation explained the differences between data warehouses, data lakes, and lakehouses, then connected those concepts to practical finance and accounting use cases.

The session covered how ELT supports stronger audit trails by preserving raw data, improving lineage, and allowing transformations to be reviewed or re-run as needed. It also included a real-world case study showing how an LLM can be used to analyze timesheet comments and flag potential FAR compliance risks. The session balanced architecture, governance, AI implementation, and practical lessons learned from building audit-driven analytics workflows.

A practical session on using modern data lakehouse architecture and audit-driven ELT to improve data governance, traceability, and accounting risk analysis. The presentation included a real-world example of applying an LLM to review timesheet comments for potential FAR compliance concerns.