Unlocking AI Value: Build AI Agents on SAP Data in Databricks

About this Video

• Video Title: Unlocking AI Value: Build AI Agents on SAP Data in Databricks
• Channel: Databricks
• Speakers: Chi Su
• Duration: 00:40:58

Introduction

This Databricks video discusses the value of building generative AI (GenAI) agents using data from SAP applications. The speaker, Chi Su, a solution architect at Databricks, highlights the partnership between Databricks and SAP's Business Data Cloud (BDC) and how it simplifies access to SAP data for AI/ML initiatives. The video demonstrates how to leverage this partnership to build more effective and efficient AI agents.

Key Takeaways

• Simplified Access to SAP Data: The partnership between Databricks and SAP's Business Data Cloud (BDC) provides streamlined access to SAP data, eliminating the complexities of traditional data extraction, loading, and transformation (ELT) processes. SAP provides pre-curated data products ready for AI/ML use.
• Delta Lake and Delta Sharing: Databricks' open-source Delta Lake and Delta Sharing protocols are adopted by SAP, enabling efficient and secure data sharing between SAP and Databricks environments. This reduces data proliferation and allows for bidirectional data exchange.
• GenAI Agent Development: The video demonstrates building GenAI agents using Databricks and SAP data. This involves using multiple agents working together to access diverse data sources, perform analyses, and generate actionable insights. The use of vector databases, large language models (LLMs), and evaluation frameworks are key components.
• Multi-Agent Systems: Building effective GenAI agents often requires a multi-agent system approach. This involves different agents collaborating to perform different tasks, such as data retrieval, analysis, and insight generation. This collaborative approach produces more accurate and comprehensive results.
• Enhanced Decision Making: Access to a wider range of data (SAP and non-SAP) leads to more accurate and reliable AI models, enabling enhanced decision-making processes within the enterprise.