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Exploring Graphs with Elixir

Name: Exploring Graphs with Elixir
Price: 59 USD
Author: The Pragmatic Programmers

Explore graph data structures with Elixir, including native vs. external databases, querying with Cypher, Gremlin, and SPARQL, and transforming data between graph models for efficient data management.

120 lessons

35h

Created by The Pragmatic Programmers

What's included

120 lessons across 14 modules
10 quizzes with instant feedback
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

An understanding of the basic graph data structures
Hands-on experience building native graph structures in Elixir
Ability to use graph-aware packages in the Elixir ecosystem
Ability to harness the concurrency of Elixir for distributed data across data networks
Ability to generate queries for graph databases with Cypher, Gremlin, and GraphQL
Ability to perform queries for linked open data with SPARQL
Ability to process and transform data from one graph model to another

Learning Roadmap

120 Lessons10 Quizzes

Getting Started

Get familiar with graph data structures in Elixir, their applications, and query optimization.

Introduction

Approach

Part I - Graphs Everywhere

Get started with graph data structures in Elixir, creating and querying versatile networks.

Engage with Graphs

First Contact

Code a “Hello World” Graph

Model a Book Graph

Our Plan of Action

Wrap Up Graphs Everywhere

Getting Started with the Project

11 Lessons

Work your way through setting up an Elixir umbrella project, graph store, and service API.

Part II - Getting to Grips with Graphs

12 Lessons

Break down complex ideas using libgraph for native graph management and visualization in Elixir.

Exploring Graph Structures

7 Lessons

Deepen your knowledge of creating, modeling, and querying graphs with Elixir's libgraph.

Navigating Graphs with Neo4j

10 Lessons

Follow the process of managing Neo4j property graphs, including Cypher queries and bolt_sips integration.

Querying Neo4j with Cypher

11 Lessons

Master querying Neo4j with Cypher for property graphs, book/ARPANET graphs, parameters, and schemas.

Graphing Globally with RDF

14 Lessons

Step through RDF for global data integration, modeling, vocabulary, API services, and querying.

Querying RDF with SPARQL

9 Lessons

Discover querying RDF graphs with SPARQL using various forms and practical applications.

10.

Traversing Graphs with Gremlin

8 Lessons

Master Gremlin in Elixir for efficient graph querying and service setup.

11.

Delivering Data with Dgraph

10 Lessons

Grasp the fundamentals of leveraging Dgraph for efficient data querying using GraphQL and DQL.

12.

Part III - Graph to Graph

12 Lessons

Map out the steps for transforming graph models, importing RDF, and federated querying.

13.

Processing the Graph

7 Lessons

Tackle Elixir's process management in graphs, building supervised nodes, preserving state, and simulating network resilience.

14.

Wrap Up

Build on effective graph handling and Elixir tools for complex data relationship management.

Conclusion

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

Graph data structures are quite intuitive and highly flexible. They’re used to conduct queries in databases and interconnect entities in data networks. Elixir, with its power of concurrency and data- and graph-aware packages, is the perfect language to explore graph data structures. In this course, you’ll learn basic graph data structures and build a simple graph model. Next, you’ll build a testbed umbrella application to compare native graph structures with external databases. You’ll also learn to query graph database systems using Elixir packages Cypher and Gremlin with property graphs and SPARQL with RDF graphs. Next, you’ll learn how to transform data from one graph model to another. Finally, you’ll learn why property graphs are especially good at graph traversal problems while RDF graphs shine at integrating different semantic models and can scale up to web proportions. After this course, you’ll be able to work with distributed graph datasets and manage data at scale.

ABOUT THE AUTHOR

The Pragmatic Programmers

We create timely, practical books and learning resources on classic and cutting-edge topics to help you practice your craft and accelerate your career.

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