What you’ve learned
You now understand the fundamentals of Graph Data Science:
The GDS workflow
Project → Run → Write
Every GDS analysis follows this pattern. You create an in-memory projection, run algorithms on it, and write results back to your database or use them in queries.
Graph projections
You learned to create projections using Cypher queries:
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Monopartite - Same node type (actors ↔ actors)
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Bipartite - Different node types preserved (users ↔ movies)
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Multipartite - Multiple types and relationships
Projections let you shape your graph for specific analysis needs. The same database can be projected many different ways, each revealing different patterns.
Graph catalog operations
You can now manage graphs in memory:
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List - See all projections and their memory usage
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Exists - Check if a graph is available
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Drop - Remove graphs to free memory
These operations are essential for efficient workflow management, especially when working with large datasets.
The skills you have
You can now:
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Project graphs from your data in multiple ways
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Understand monopartite, bipartite, and multipartite structures
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Manage graphs in the catalog efficiently
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Run basic algorithms (degree centrality, PageRank, node similarity)
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Understand how projection structure affects algorithm results
What’s next: Algorithm fundamentals
You know how to create projections. Next you’ll dive into understanding and using GDS algorithms.
In the next module, Module 3: Algorithm fundamentals, you’ll learn:
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The five categories of GDS algorithms and when to use each
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Five execution modes: stats, stream, mutate, write, and estimate
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How to read and interpret GDS documentation
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How to configure algorithms for your specific needs
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How to design projections that match algorithm requirements
By the end of the next module, you’ll be able to independently learn and apply any GDS algorithm to solve analytical problems.
Summary
You’ve got GDS basics down: projections, graph types, and catalog management. You understand how to shape data for analysis and manage in-memory graphs efficiently.
Module 3 builds on these fundamentals, teaching you how to work with the full range of GDS algorithms—reading documentation, configuring settings, and modeling projections for specific questions.