Graph

Graph data structure natively represents relationships between data. The two main parts of a graph are:

• Vertices (or nodes) that represent objects and their properties

• Edges (or connections) that represent links between two vertices

Some of the key benefits are:

• Enhanced Data Relationships & Insights

  • Unlike traditional tabular data analysis, graph analytics enables users to explore intricate relationships between data points, providing a holistic view of connections and dependencies.

• Identify unusual connections

  • Graph analytics is particularly effective in identifying fraudulent activities by detecting unusual patterns, anomalies, and suspicious connections in financial transactions, cybersecurity, and compliance monitoring.

• Faster query processing

  • Graph analytics fundamentally changes the way relationships are queried and analyzed. By eliminating the need for expensive join operations and enabling high-speed relationship traversal, graph databases significantly outperform relational databases for complex, connected data.

Dataiku features Visual Graph, a set of capabilities to:

• Build and edit graphs visually from datasets containing nodes and edges

• Explore the built graphs visually

• Perform Cypher queries on your graph, with an AI assistant for building the queries

• Use the graph as a knowledge tool for AI Agents

• Visual Graph
  • Prerequisites
  • Visual Graph Editor
  • Visual Graph Explorer
  • Recipes
  • Graph Search Agent Tool