Graph Algorithms

Index

Graph Algorithms

Analyze networks with powerful graph algorithms

Graph algorithms unlock insights hidden in the structure of your data. This section covers foundational concepts, centrality measures, community detection, connected components, pathfinding, structural analysis, and practical applications. Start with the introduction to understand how algorithms work, then explore specific topics based on your analysis needs.

Introduction to Graph Algorithms

Overview of algorithm categories, execution engines, and when to use them

30 min · Beginner

Centrality

PageRank, betweenness, closeness, and degree centrality measures

35 min · Intermediate

Community Detection

Find clusters and groups of densely connected nodes

35 min · Intermediate

Connected Components

WCC and SCC for identifying isolated subgraphs

30 min · Intermediate

Pathfinding

Shortest paths, BFS, Dijkstra, and weighted pathfinding

35 min · Intermediate

Structural Analysis

Triangle counting, clustering coefficients, and network density

30 min · Intermediate

Combining Algorithms

Multi-algorithm workflows and ensemble approaches

40 min · Advanced

Real-World Case Studies

Fraud detection, social analysis, and recommendation engines

45 min · Advanced

Algorithm Discovery

Find, inspect, and run any algorithm by name

20 min · Intermediate

Next Steps

Admin & Operations

Platform administration, user management, and configuration

6 tutorials · ~3 hours

Advanced Topics

Instance lifecycle, export pipelines, and graph engine selection

6 tutorials · ~2.5 hours