Basics of Graph Theory: Understanding graph theory concepts such as nodes, relationships, properties, and graph traversal.
Graph vs. Relational Databases: Differences between graph databases and traditional relational databases, including use cases and advantages.
Overview of Neo4j: Introduction to Neo4j, its architecture, and core components.
2. Getting Started with Neo4j
Installation and Setup: Steps to install Neo4j on various platforms (Windows, macOS, Linux) and initial setup.
Neo4j Desktop and Browser: Introduction to Neo4j Desktop and Neo4j Browser for database management and query execution.
Basic Concepts: Overview of key concepts such as nodes, relationships, labels, and properties.
3. Cypher Query Language
Introduction to Cypher: Basics of Cypher, the query language for Neo4j, and its syntax.
Basic Queries: Writing simple queries to match, create, update, and delete nodes and relationships.
Advanced Queries: Using complex queries, patterns, aggregations, and functions to analyze graph data.
Performance Optimization: Techniques to optimize Cypher queries for better performance.
4. Data Modeling and Schema Design
Graph Data Modeling: Designing effective graph schemas, including nodes, relationships, and properties.
Schema Constraints: Using constraints and indexes to enforce data integrity and improve query performance.
Data Import and Export: Techniques for importing and exporting data from various sources.
5. Graph Algorithms and Analysis
Graph Algorithms: Understanding and implementing common graph algorithms such as shortest path, centrality, and community detection.
Graph Analytics: Performing graph analytics to uncover insights and patterns in connected data.
6. Application Development with Neo4j
Integrating with Applications: Connecting Neo4j with applications using official drivers for various programming languages (Java, Python, JavaScript, etc.).
Building Graph-Based Applications: Developing applications that leverage graph data and Neo4j’s capabilities.
APIs and REST Interface: Using Neo4j’s REST API for interacting with the database programmatically.
7. Scaling and Performance
Scaling Neo4j: Techniques for scaling Neo4j to handle larger datasets and higher workloads.
High Availability: Configuring Neo4j for high availability and fault tolerance.
Backup and Recovery: Strategies for backing up and recovering Neo4j databases.
8. Security and Administration
User and Role Management: Managing users, roles, and permissions in Neo4j.
Security Best Practices: Implementing security measures to protect data and ensure secure access.
Monitoring and Maintenance: Tools and practices for monitoring database performance and maintaining Neo4j.
9. Advanced Features and Use Cases
Graph Data Science: Exploring advanced topics like graph data science and using Neo4j’s Graph Data Science Library.
Real-World Use Cases: Examining practical applications and case studies of Neo4j in various industries (e.g., social networks, recommendation systems, fraud detection).
10. New Developments and Future Trends
Latest Features: Keeping up with the latest features and updates in Neo4j.
Graph Database Trends: Understanding emerging trends and technologies in graph databases.
Course Format
Lectures and Readings: Comprehensive theoretical and practical lectures on Neo4j and graph databases.
Hands-On Labs: Practical exercises and labs to apply concepts in real-world scenarios.
Assignments and Projects: Individual or group projects to reinforce learning and practical skills.
Exams and Quizzes: Assessments to test knowledge and understanding of Neo4j.
Target Audience
Data Analysts and Scientists: Professionals analyzing connected data and seeking advanced analytics capabilities.
Software Developers: Developers building applications that leverage graph data.
Database Administrators: DBAs managing and optimizing graph databases.
IT Managers: Managers overseeing graph database systems and their implementation.
Prerequisites
Basic Database Knowledge: Understanding of fundamental database concepts and principles.
Basic Programming Skills: Familiarity with at least one programming language is often recommended.
Graph Theory Basics: An introduction to graph theory can be helpful, though not always required.
