Finance teams face a persistent challenge: critical data remains locked in SAP while traditional approaches require weeks of IT involvement to extract data, build pipelines, and develop reports. This results in stale information that hampers decision-making and prevents deployment of AI-powered analytics.

This session demonstrates how Microsoft's Business Process Solutions transforms this paradigm by automatically deploying complete data infrastructure for modern financial reporting.

Attendees will experience Business Process Solutions connecting SAP to Microsoft Fabric, automatically creating lakehouses, data pipelines, and production-ready financial reports without manual development.

The session then explores how AI assistance through the Power BI MCP Server enables finance professionals to customize pre-built solutions to match organizational requirements. We'll demonstrate adapting hierarchical structures to tabular formats, incorporating reporting standards like IAS 1, and building custom calculations—compressing weeks of specialized development into hours.

Finally, we'll demonstrate deploying Fabric Data Agents into Microsoft Teams for conversational access to live SAP data, and integrating Finance Agents for Excel and custom agents built in Copilot Studio.

Participants will leave with a practical roadmap for transitioning from static, extract-based reporting to live, AI-augmented financial intelligence.

Full Day Agenda

Morning Session (09:00 - 12:30)

Module 1: Introduction and Environment Setup (09:00 - 10:30)

- The SAP data challenge: Why finance teams struggle with locked data and week-long IT dependencies
- Overview of Microsoft Business Process Solutions for SAP

-Hands-on Lab: Setting up SAP S/4HANA trial instance using SAP Cloud Appliance Library (cal.sap.com); Creating your SAP account Understanding key financial tables

Coffee break (10:30 - 10:45)

Module 2: Deploying Business Process Solutions (10:45 - 12:30)

-Architecture overview: How Business Process Solutions automates infrastructure deployment; Live Demo: Connecting Business Process Solutions to your SAP instance

-Hands-on Lab: Automated deployment of lakehouses (bronze, silver, gold layers), Data pipelines for SAP extraction, Pre-built financial semantic models, Production-ready Power BI reports (e.g. Financial Reporting, Order to Cash); Understanding what gets created automatically vs. what requires customization

- Lunch (12:30 - 13:30)

** Afternoon Session (13:30 - 17:00) **

Module 3: AI-Assisted Customization with MCP Servers (13:30 - 15:00)

- The customization challenge: Adapting pre-built solutions to your organization
- Introduction to Model Context Protocol (MCP) servers for Power BI and Fabric
- Hands-on Lab: Installing and configuring Claude Desktop with Power BI MCP server

- Hands-on Lab: Using AI agents to customize SAP financial reports: Converting hierarchical GL structures to tabular format for your chart of accounts; Incorporating IAS 1 presentation requirements; Building custom DAX measures for margin analysis and variance analysis; Creating calculation groups for time intelligence; Context engineering: Guiding AI to understand your specific requirements

- Coffee break (15:00 - 15:15)

Module 4: Deploying Conversational AI Agents (15:15 - 16:30)

- Making SAP data accessible through natural language

- Hands-on Lab: Deploying Fabric Data Agents into Microsoft Teams: Creating a Data Agent skill on top of your SAP financial semantic model and lakehouse tables with few shot examples and AI instructions (e.g. on how to use the model vs the lakehouse); Testing conversational queries ("What's our gross margin this quarter?"); Handling follow-up questions and context

- Live Demo: Integrating Finance Agents for Excel/Copilot Studio : A look at how the SAP data can be leveraged in Finance Agents for Excel (Reconciliation, Financial Variance Analysis agent etc) as well as a source for Copilot Studio Agents; Integrating approval workflows

Module 5: Q&A, Best Practices, and Next Steps (16:30 - 17:30)

- Security and governance considerations for SAP data in Fabric
- Performance optimization: Incremental refresh, aggregations
- Roadmap: From proof-of-concept to production deployment
-Common pitfalls and how to avoid them
- Resources: Documentation, community support
-Q&A