📍 My Neo4j Certification Journey

Hey there! 👋

I recently earned my Neo4j Certified Professional badge — and what a fun ride it's been! From diving into graph data modeling to writing Cypher queries that actually *felt* like English, it was an eye-opener into how data can be visualized and connected. This blog highlights key learnings, practical examples, and how Neo4j is shaping my view of modern data systems.

🌐 Why Graph Databases?

Traditional databases are great at storing rows and columns, but they often fall short when you want to understand relationships — like which users follow each other or how entities are linked. That’s where Neo4j and graph databases shine.

Think of it like a web of knowledge: nodes are entities and relationships define how they connect.

📚 What the Certification Covers

• Concepts: Nodes, Relationships, Labels, and Properties
• Cypher syntax for querying and data manipulation
• Data modeling best practices using real-life scenarios
• Graph imports using CSV and Neo4j Desktop tools
• Visualizing data via Neo4j Browser and Bloom
• Python integration using the Neo4j Bolt Driver

🎓 My Neo4j Certification

I earned the Neo4j Certified Professional credential. You can view and verify it here:

✅ View / Verify My Certificate

🧠 Hands-On Examples

I built a movie database that allowed me to:

• Find co-actors using pattern matching
• Track actor-director collaborations
• Visualize genres and rating connections

// Find actors who worked with Keanu Reeves
MATCH (a:Actor)-[:ACTED_IN]->(:Movie)<-[:ACTED_IN]-(coActor:Actor {name: "Keanu Reeves"})
RETURN DISTINCT a.name

🔎 What Makes Neo4j Unique?

Some key differentiators:

• Cypher – the SQL-like query language that’s intuitive and readable
• Index-free adjacency – faster traversals with connected data
• Developer-first tools – great docs, sandbox environments, and integrations

🚀 Where Can You Use It?

Real-world applications of graph databases:

• Recommendation Systems – like Netflix or Spotify’s "You May Also Like"
• Fraud Detection – identifying suspicious connections in finance
• Knowledge Graphs – connecting unstructured data for enterprises
• Supply Chain Analysis – tracking dependencies and delays

🛠️ Tools I Used

• Neo4j Desktop
• Cypher Shell
• Python Jupyter Notebook + neo4j package
• GraphAcademy learning platform (highly recommended!)

🧪 Lab: Getting Started with Neo4J Enterprise on Google Cloud

I also completed a practical lab hosted on Google Cloud Skills Boost. This lab focused on deploying and working with Neo4j Enterprise on Google Cloud.

Overview

In this lab, I analyzed quarterly filings of asset managers with $100M+ assets under management (AUM) in a Neo4j Enterprise environment. The data comes from SEC’s EDGAR system and was loaded from a GCP Cloud Storage bucket into Neo4j. Then, I explored relationships of asset managers and their holdings using Cypher queries.

Objectives

• Connect to Neo4j Enterprise running on Google Cloud
• Load data from a Google Cloud Storage bucket
• Explore data using Cypher in Neo4j Browser

Key Steps Performed

1. Launched Neo4j Enterprise on Google Cloud via GCP Console
2. Connected using Neo4j Browser and Cypher Shell
3. Imported data from Google Cloud Storage into Neo4j
4. Ran queries to explore relationships between asset managers and holdings

Important Commands & Queries

• bin/cypher-shell -u neo4j -p password – Connect to Neo4j using Cypher Shell
• Used LOAD CSV command to bring data form bucket WITH HEADERS FROM 'gs://bucket/file.csv' AS row ... – Import CSV data from GCS
• MATCH (n) RETURN count(n); – Count all nodes in the graph
• MATCH (a:Manager)-[:OWNS]->(h:Holding) RETURN a,h LIMIT 25; – Explore manager-holding relationships

📸 Lab Screenshots

📈 What’s Next?

I plan to explore more advanced topics like Graph Data Science (GDS), Neo4j Bloom, and building a Flask-based web app powered by Neo4j.

Stay tuned—I'll post follow-ups on GitHub and LinkedIn!

🎓 Final Thoughts

Honestly, I went in just curious — and came out with a deeper appreciation for connected data. I highly recommend this certification for devs, analysts, or anyone working with relationships in data.