Get to Know the Real World: Discovering Connected Data with a Graph Database

In this session, we will see how a graph database is different from other types of data stores and how it can transform your applications and data. Data science principles and tools can further aid in exploring and understanding complex data to expand possible uses and value.
We will see how to create, query, and display data in the graph and learn how to use simple tools to interact with the database. We will cover the whiteboard-friendly model and the basics of the Cypher query language. Live demos will show users the power of connected data and data science to understand data structure in the graph.

Transcript

1. Get to Know the Real World… Discovering Connected Data with a Graph Database Jennifer Reif Neo4j @JMHReif
2. Who Am I? • Developer Relations Engineer for Neo4j • Continuous learner • Conference speaker • Blogger • Hobbies: cats, coffee, traveling Email: jennifer.reif@neo4j.com Twitter: @JMHReif
3. What is a Graph Database?
4. Graph Chart
5. Database - specifically graph • Database: a structured set of data held in a computer, especially one that is accessible in various ways. • Relational? NoSQL? Graph? • Graph database: uses graph structures for semantic queries with nodes, edges and properties to represent and store data.
6. Why would I choose graph?
7. Graphs show how data is connected
8. Relational Graph
9. Other NoSQL Graph
11. Graphs add context and meaning
12. Graph use cases Social Network Fraud Detection Network & IT
 Operations Identity and
 Access Management Graph-based Search
13. Connected data adds meaning to analytics
15. Improves accuracy Machine Learning Pipeline
16. Graph Data Science Uses Financial
 Crimes Drug
 Discovery Recommendations Customer
 Segmentation Cybersecurity Churn Prediction Predictive
 Maintenance Search & MDM
18. Understanding the graph model
19. Whiteboard Friendliness Easy to design and model direct representation of the model
20. Whiteboard friendliness
21. Whiteboard friendliness title: The Lord of the Rings… released: 2003 Movie Cast name: Orlando Bloom name: Frodo Baggins Character PLAYED APPEARS_IN name: Elijah Wood Cast Character name: Legolas Character name: Aragorn name: Viggo Mortensen Cast PLAYED PLAYED APPEARS_IN APPEARS_IN
22. Whiteboard friendliness
23. How to construct a graph
24. Property Graph Data Model • 2 Main Components: • Nodes • Relationships • Additional Components: • Labels • Properties
25. Property Graph Data Model • Nodes: • Represent the objects in the graph • Can be categorized using Labels Person Technology Person Person Company Technology
26. Property Graph Data Model • Nodes: • Represent the objects in the graph • Can be categorized using Labels • Relationships: • Relate nodes by type and direction Person Person Company Technology :LIKES :IS_FRIENDS_WITH :WORKS_FOR
27. Property Graph Data Model • Nodes: • Represent the objects in the graph • Can be categorized using Labels • Relationships: • Relate nodes by type and direction • Properties: • Name-value pairs that can be applied to nodes or relationships :LIKES :IS_FRIENDS_WITH :WORKS_FOR Person name: Michael Person name: Jennifer Technology type: Graphs since: 2018 Company name: Neo4j
28. Cypher Query Language…. SQL for graphs
29. Cypher: Powerful and Expressive CREATE (:Person { name: ‘Jennifer’}) -[:WORKS_FOR]-> (:Company { name: ‘Neo4j’}) LABEL PROPERTY NODE NODE LABEL PROPERTY Jennifer Neo4j WORKS_FOR
30. Cypher: Powerful and Expressive MATCH (:Person { name: ‘Jennifer’} ) -[:WORKS_FOR]-> ( whom ) 
 RETURN whom Neo4j WORKS_FOR Jennifer
31. Demo Time!!
32. Resources • Neo4j download: https://neo4j.com/download/ • Neo4j sandbox: https://neo4j.com/sandbox-v2/ • Neo4j guides: https://neo4j.com/developer/get-started • Cypher: https://neo4j.com/developer/cypher/ • LOAD CSV: https://neo4j.com/developer/guide-import-csv/ • APOC: https://neo4j-contrib.github.io/neo4j-apoc-procedures/ • Neo4j Certification: https://neo4j.com/graphacademy/neo4j-certification/ @JMHReif jennifer.reif@neo4j.com