To design a scalable graph-based data processing system using Neo4j and Apache Spark to analyze relationships, detect communities, and extract insights from highly connected datasets such as social networks or recommendation systems.
Study graph database concepts.
Install and configure Neo4j.
Import relational datasets into graph format.
Design graph schemas and relationships.
Implement Cypher queries for analytics.
Integrate Spark for large-scale graph processing.
Perform community detection algorithms.
Optimize graph traversal queries.
Benchmark performance with large datasets.
Visualize graph analytics results.
Secure graph database access.
Document graph modeling decisions.
Conduct scalability testing.
Prepare final analytics demonstration.
