• Online, Self-Paced
Course Description

This course will teach you to use operations that modify in-memory graphs built with the Graph Data Science (GDS) library, update the properties of the underlying database, and export their contents to a database or file.

You begin with a mutate operation to add new properties to an in-memory graph. You will learn how you can save the results of graph algorithms in such graphs for later reference. Next, you explore the write operation to update the underlying database with the results of graph algorithms on in-memory graphs. You will then move on to exporting your graph to a persistent store.

Finally, you cover the different ways you can remove GDS graphs from the graph catalog. While doing so, you will explore the degree centrality calculation, which measures how well-connected nodes are in a network.

After completing this course, you will have a fundamental understanding of how to administer in-memory graphs using the Graph Data Science library in Neo4j.

Learning Objectives

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Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.