This document provides an agenda and overview for a graph data science demo focusing on fraud analysis. The demo will review Neo4j's graph data science library and algorithms for pathfinding, centrality, community detection, and similarity. It will use sample bank transaction and customer data modeled as a graph to demonstrate PageRank, betweenness centrality, weakly connected components, Louvain modularity, and node similarity algorithms. The goal is to identify important nodes, communities, and similar entities to detect potential fraud.