Chapter 4: Data Structures Every Network Engineer Should Know – Part 2

In the first part of this data structure types topic, we introduced fundamental data structures that every network engineer and programming beginner should feel comfortable with: arrays, dictionaries, stacks, queues, sets, and more. If you haven't read that one yet, it's highly recommended to start there to build a solid foundation before diving into the more complex structures covered here.

This second article picks up where we left off, expanding your understanding into hierarchical, graph-based, and spatial data structures, concepts that often appear in network topologies, graph traversal algorithms, coverage planning, and routing logic.

We'll explore:

• Trees and how they structure hierarchical data

• Hash tables and their blazing-fast lookups

• Deques for flexible insertions/removals

• Graphs that model real-world connectivity

• And even Voronoi Diagrams and Delaunay Triangulation, powerful tools for modeling network influence, territories, and geospatial logic

By the end of this post, you'll have a much broader toolkit to analyze and model complex data patterns, whether you're simulating BGP graphs or figuring out how to divide your infrastructure across regions.

Let’s continue building your practical fluency in data structures, one concept at a time.

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