Aspire     Graph Analytics     Graph Analytics Track 2: Graph Analytics with Neo4j

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This course delves into the fundamentals of graph data modeling from a theoretical standpoint before applying some of the principles to a Neo4j database.
Begin with an overview of data modeling in general and then graph modeling in particular. Learn to recognize the similarities in modeling for relational, document, and graph databases and identify how their approaches vary. Next, in the practical portion of the course, build a database with different entity types and multiple relationship types. Explore the use of properties, labels, and relationships to model your data correctly for efficient query execution.
Finally, delve into translating a CSV file containing a many-to-one relationship between entity types into a graph database and discover how to translate a tabular structure like a CSV file into a graph structure for Neo4j.

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Objectives

Graph Modeling with Neo4j: An Introduction to Modeling Graphs discover the key concepts covered in this course recognize the similarities and differences of data modeling approaches for relational, document, and graph data describe the different techniques used for representing entities and their interactions in a Neo4j graph database list the steps involved in mapping data in a relational database to a Neo4j graph database use labels and properties for Neo4j nodes in an optimal manner from the point of view of anticipated queries create relationships between nodes and set properties on such relationships use a variety of queries on a Neo4j database using the Cypher query language and recognize the role of various facets of a data model in such queries create nodes and relationships from the contents of a CSV file describe how data in a tabular structure containing many-to-one relationships can be modeled as a Neo4j graph summarize the key concepts covered in this course