As organizations increasingly rely on connected data to power recommendation engines, fraud detection, knowledge graphs, and supply chain optimization, the demand for graph-based systems has surged. This Graph Data Engineering with Neo4j course is designed to equip data professionals with the skills to model, store, query, and manage graph data at scale using Neo4j, the world’s leading graph database. Participants will gain hands-on expertise in Cypher query language, graph modeling principles, integration with data pipelines, and advanced graph analytics to drive meaningful business insights from complex relationships within their datasets.

Duration: 10 Days

Target Audience

• Data Engineers and Architects
• Database Developers and Administrators
• Business Intelligence Analysts
• Software Engineers handling relational complexity
• Data Scientists exploring graph-based machine learning
• Enterprise Architects
• Technical Product Managers
• Professionals working on recommendation engines, fraud detection, or social graphs

Course Objectives

• Understand the fundamentals of graph data modeling and database architecture
• Learn to query graph databases effectively using Cypher
• Design and implement scalable graph-based data systems
• Integrate Neo4j into modern data engineering pipelines
• Perform graph analytics and visualization for business insights
• Optimize graph storage and performance for production environments
• Apply graph techniques in real-world domains such as fraud detection and logistics
• Enable data lineage, master data management, and network analysis
• Utilize Neo4j’s advanced features including indexes and procedures
• Deploy and secure Neo4j in cloud-native architectures
• Develop graph-centric applications that go beyond traditional SQL-based solutions

Module 1: Introduction to Graph Data Engineering

• Differences between graph and relational data models
• Use cases for graph databases in modern data systems
• Overview of Neo4j architecture and capabilities
• Comparison of property graph vs. RDF graphs
• Installing and setting up Neo4j Desktop or Aura

Module 2: Graph Data Modeling Concepts

• Nodes, relationships, properties, and labels
• Modeling real-world scenarios: users, transactions, entities
• Avoiding overmodeling and redundancy
• Designing graph schemas for performance and readability
• Refactoring and evolving a graph data model

Module 3: Cypher Query Language Essentials

• Writing basic read and write Cypher queries
• Pattern matching with variables and paths
• Filtering, sorting, and aggregating graph data
• Merging and deleting nodes and relationships
• Using parameters and best practices

Module 4: Advanced Cypher Techniques

• Subqueries and conditional logic
• Path querying with variable lengths
• Unwinding lists and working with collections
• Using APOC procedures for powerful operations
• Creating reusable queries and scripts

Module 5: Importing Data into Neo4j

• Bulk data import using CSV and JSON
• Using Neo4j Data Importer and ETL tools
• Building connectors with Python, Kafka, and Spark
• Integrating with cloud storage and APIs
• Handling data cleansing during ingestion

Module 6: Graph Algorithms and Analytics

• PageRank, community detection, similarity, and shortest path
• Using Neo4j Graph Data Science (GDS) Library
• Applying graph algorithms in marketing, security, and logistics
• Writing projections and pipelines in GDS
• Analyzing and interpreting graph metrics

Module 7: Visualization and Exploration

• Neo4j Browser and Bloom for visual graph exploration
• Designing visual patterns to uncover insights
• Embedding graph visualizations into applications
• Filtering and styling graph elements
• Working with external tools like Gephi and D3.js

Module 8: Integrating Neo4j with Data Pipelines

• Connecting Neo4j to Apache Kafka and Airflow
• Writing custom data loaders and transformers
• Building ELT processes with graph sinks
• Maintaining real-time graph updates
• Monitoring data consistency across sources

Module 9: Performance Tuning and Indexing

• Profiling and debugging Cypher queries
• Creating and optimizing indexes and constraints
• Handling large graphs with memory configurations
• Monitoring slow queries and optimizing path traversal
• Caching strategies and pagination

Module 10: Security and Access Control

• Authentication and role-based access control
• Managing user privileges and admin rights
• Securing data in transit and at rest
• Auditing user access and activities
• Integrating with LDAP or single sign-on

Module 11: Building Graph-Powered Applications

• Using Neo4j drivers (Python, JavaScript, Java)
• Constructing APIs to serve graph data
• Leveraging Neo4j Aura for serverless deployment
• Handling transactions and error management
• Embedding graph intelligence in mobile and web apps

Module 12: Data Governance and Lineage in Graphs

• Modeling data lineage using relationships
• Enabling traceability across pipeline steps
• Auditing data ownership and transformations
• Supporting metadata management with graphs
• Using graphs for MDM and knowledge graphs

Module 13: Graph Machine Learning Foundations

• Basics of graph embeddings and neural networks
• Node classification and link prediction use cases
• Integrating Neo4j with ML platforms like TensorFlow and PyTorch
• Building features from graph structures
• Training and evaluating graph ML models

Module 14: Cloud Deployment and High Availability

• Deploying Neo4j on AWS, GCP, or Azure
• Using Kubernetes and Docker for orchestration
• Setting up Neo4j clusters and backups
• Monitoring system health and metrics
• Scaling Neo4j in distributed environments

Module 15: Capstone Project and Real-World Scenarios

• Design a graph model for a real business case
• Ingest and query complex relationship data
• Run algorithms to generate insights
• Visualize and present findings
• Receive feedback and guidance for production readiness

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.