The document discusses using Neo4j graphs to analyze Army logistics data. It outlines requirements to identify all parts, track relationships between parts, find interchangeable parts, and generate comprehensive part explosions. It then demonstrates Neo4j implementation through sample queries to identify all components and systems related to a specific part. Resources for additional Neo4j information are also listed.

1. Big Data With Neo4j
Using the power of Neo4j graphs to navigate Army logistics data
Presented By: Preston Hendrickson, CALIBRE

2. Agenda
 Define The Requirement
 Data Analysis
 Data Modeling
 Neo4j Implementation
 Resources

3. Define The Requirement

4. Define The Requirement
• Identify list of all parts
• Track part relationships
• Identify interchangeable parts
• Produce comprehensive parts
explosions

5. Neo4j Implementation
MATCH p=(:Part)-[:FITS_ON*]->(:Component {PartNumber:"19A"}) RETURN p
19A
12
20
17
18
28D

6. Neo4j Implementation
MATCH p=(pt:Part)-[:FITS_ON]->(:Component)-[:FITS_ON]->(s:System) WHERE id(pt) = 10909 RETURN p LIMIT 1
Lens/Light Component System

7. Neo4j Implementation
MATCH p=(pt:Part)-[:FITS_ON*]->(s:System) WHERE id(pt) = 10909 RETURN p
Define The Requirement
• Identify list of all parts
• Track part relationships
• Identify interchangeable parts
• Produce comprehensive parts
explosions

8. Resources
 Neo4j Community: https://community.neo4j.com/
 Google Groups: https://groups.google.com/forum/#!forum/neo4j
 Neo4j Meetup Baltimore-Washington: https://www.meetup.com/graphdb-baltimore/
 Stack Overflow: https://stackoverflow.com/questions/tagged/neo4j
 YouTube: https://www.youtube.com/channel/UCvze3hU6OZBkB1vkhH2lH9Q