Neo4j for Data Scientists and Analysts: Analyze Relationships in Large Datasets to Gain Insights Faster

By ANSEL CORBYN

Unlock the hidden power of connected data with Neo4j and transform the way you analyze relationships in large datasets.

Traditional databases struggle to reveal insights hidden in complex networks of transactions, patients, supply chains, or customers. Neo4j for Data Scientists and Analysts shows you how to model, query, and scale graph databases to uncover patterns that SQL often misses.

This book bridges the gap between theory and practice, guiding you step by step through real-world applications in finance, healthcare, retail, and manufacturing. Whether you are building fraud detection pipelines, recommendation engines, or knowledge graphs, this guide equips you with the tools to deliver faster and smarter results.

What you will learn: Design effective graph data models using nodes, relationships, and propertiesQuery large datasets with Cypher and optimize performance for billions of relationshipsApply graph algorithms for fraud detection, recommendations, and network analysisIntegrate Neo4j with Python, Apache Spark, and Kafka for scalable analyticsBuild graph embeddings and neural networks for machine learning applicationsVisualize and interpret knowledge graphs for actionable business insights
Practical add-ons in every chapter: Key Takeaways that summarize core lessonsApplication Tips to put concepts into practice immediatelyCommon Mistakes to avoid costly pitfallsQuick Quiz flashcards for self-testing and active recall
Code you can use right away:
From Cypher queries to Python scripts, every chapter includes working examples that help you move from learning to doing. You will practice with hands-on projects across industries, reinforcing your skills through real-world scenarios.

Master the graph mindset and gain a competitive edge in data science.

Grab your copy today and start analyzing relationships at scale with Neo4j.

• Format: Paperback
• Language: English
• ISBN: B0FSHJ338M
• ISBN13: 9798266702080
• Release Date: September 2025
• Publisher: Independently Published
• Length: 196 Pages
• Weight: 0.59 lbs.
• Dimensions: 0.4" x 6.0" x 9.0"