Knowlege Graphs in Theory & Practice [2025]

Name: Knowlege Graphs in Theory & Practice [2025]
Rating: 3.3 (6 reviews)

Unlocking the Power of Data Connections - Visualize your own knowledge graph with janusgraph and react

Created byLuca D

Last updated 1/2025

English

English [Auto],

What you'll learn

Become familiar with the field of knowledge graph, ontologies and semantics
Identify opportunities for applying 'graph thinking'
Get to know the importance of knowledge graphs and their architecture
Be able to build your own scalable knowledge graphs and visualize data with it
Know several areas where knowledge graphs can be put in practice
Visualize graph data from beginner to advance

Course content

8 sections • 27 lectures • 2h 49m total length

Welcome1:06
Welcome to this Udemy Course that is all about knowledge graphs!
What you need for this course2:34
Structure of this course2:38
Learn to build and visualize a knowledge graph using RDF and semantic models, with Janusgraph, a Spring Boot API, and a React frontend showing nodes, edges, and clusters.
What we learn

Definition of a knowledge graph and main components4:18
Knowledge graphs are structured representations with nodes for entities and edges for relationships, creating a map of how information connects and enabling AI, search, and predictive analytics.
Main Components of a knowledge graph in detail3:47
Where knowledge graphs are used8:04
Challenges for building a knowledge graph5:26
Uncover the key challenges in building knowledge graphs, including data quality and data integration from multiple sources. Explore strategies for automated validation, entity linking, and scalable graph maintenance.
How you start building a knowledge graph4:35
Undirected vs directed graphs, graph algorithms6:52
RDF, Web Semantics, Ontologies and Knowledge Graphs9:52

Docker Getting Started3:43
Setting up Janusgraph - Docker8:06
Setting up Janusgraph - Cassandra6:14
Set up Cassandra as a storage backend for Janusgraph using docker compose, configure services, networks, and ports, and connect Janusgraph to one or more Cassandra instances.
Setting up Janusgraph - Elasticsearch10:35
Learn how to configure Janusgraph to use Elasticsearch as a mixed index alongside Cassandra, enabling direct index queries and faster fuzzy searches, via Docker Compose setup and configuration tuning.
Set up Spring Project3:48
Set up a spring boot project with maven and kotlin, import data into janusgraph, fetch data via an api, and build a react application in intellij.
Build your data importer22:41
Build your data importer for Janusgraph by wiring a faker-based data generator, configuring Maven dependencies, and importing networks of persons with names and emails via Gremlin queries.
Start Importing Data1:32
Using Gremlin Console to query data4:35
Verify data imports with the Gremlin console by connecting to JanusGraph, running basic queries on localhost:8182, counting vertices, and using the value map function to inspect names and emails.

Requirements

[Nice to have] Familiarity working with data
[Nice to have] Spring Boot Knowledge
[Nice to have] Software development basics

Description

This course teaches how to build, manage, and visualize a knowledge graph using JanusGraph, Cassandra, and Elasticsearch. You will learn how to leverage the power of graph databases to model and query complex relationships in your data, while also utilizing Cassandra as a scalable backend for storing graph data and Elasticsearch for efficient full-text search capabilities.

Through hands-on tutorials and a real-world examples, you will gain practical knowledge of setting up and configuring a graph database using JanusGraph integrated with Cassandra and Elasticsearch. The course will also cover how to expose your knowledge graph data via a Spring-based REST API and visualize it seamlessly in a React application.

Key Learning Objectives:

Introduction to Knowledge Graphs: Understand the fundamentals of knowledge graphs, including how to represent entities and their relationships as a graph.
Setting up JanusGraph with Cassandra: Learn how to configure and deploy JanusGraph with Cassandra as the storage backend to handle large-scale graph data.
Graph Data Modeling: Learn best practices for modeling your data as a graph, including defining vertices, edges, and properties.
Building a REST API with Spring: Understand how to expose your graph data through a Spring Boot application with RESTful APIs that can be consumed by front-end applications.
Visualizing the Knowledge Graph in React: Learn how to visualize and interact with your knowledge graph using a React-based front-end, allowing users to explore the graph and its relationships in an intuitive way.

Who Should Take This Course?

This course is ideal for developers, data engineers, and architects who want to build sophisticated knowledge graph applications. Whether you're working on a recommendation system, semantic search, or complex data relationships, this course will equip you with the tools to design and deploy a graph-based solution using JanusGraph, Cassandra, Elasticsearch, Spring, and React.

Prerequisites:

Basic understanding of databases and web development.
Familiarity with Java and Spring Boot is helpful, but not required.
Basic knowledge of React is recommended.

Who this course is for:

Anyone with an interest in information modelling, data architecture and knowledge management
Data-focused professionals with no prior exposure to knowledge graph technologies
Developers at the start of their journey in knowlege graphs
Developers with advanced knowledge in knowledge graphs

Knowlege Graphs in Theory & Practice [2025]

What you'll learn

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Course content

Introduction3 lectures • 6min

Theoretical Foundations7 lectures • 43min

Graph Databases3 lectures • 10min

Introduction to Janusgraph2 lectures • 14min

Build and Visualize your own first knowledge graph - Janusgraph8 lectures • 1hr 1min

Build and Visualize your own first knowledge graph - Spring Service2 lectures • 21min

Build and Visualize your own first knowledge graph - React Application1 lecture • 13min

Conclusion and Summary1 lecture • 1min

Requirements

Description

Who this course is for: