Building a Fully Automated ETL Pipeline with Docker & Neo4j For a GraphRAG Chatbot

In our last video, we laid the groundwork by creating a basic data ingestion pipeline for Neo4j, manually inputting data into the database. While this method was great for learning, it's not ideal for larger, more complex datasets or real-world applications.

In this video, we take it up a notch by developing a fully automated Extraction, Transformation, and Load (ETL) pipeline. We'll harness the power of Docker and Docker Compose to streamline the entire process, ensuring scalability and efficiency in your data workflow.

By the end of this tutorial, you'll have a solid ETL pipeline that simplifies data processing and scales effortlessly with your needs. Whether you're dealing with big data or just looking to optimize your current setup, this video has got you covered. Let’s dive in and start building this essential component of your data infrastructure!

Git Repo:
https://github.com/Princekrampah/neo4j_graphrag_tutorial
Medium Articles:
First video's article:
https://medium.com/ai-advances/building-a-graphrag-from-scratch-neo4j-csv-integration-step-by-step-3a1e5b43c239
Second video's article:
https://medium.com/ai-advances/building-an-extract-transform-and-load-pipeline-etl-for-neo4j-graphrag-application-part-2-123be950946e
Third video's article:
https://medium.com/ai-advances/learning-the-basics-of-langchain-for-neo4j-graphrag-application-part-3-d32ad8d47fc5
Forth video article:
https://medium.com/ai-advances/natural-language-to-cypher-with-agentic-ai-part-04-a269a959bb8c
Fifth video's article:
https://medium.com/ai-advances/agentic-graphrag-with-neo4j-and-langchain-ce03b344149c
Sixth video's article:
https://medium.com/ai-advances/graphrag-with-neo4j-building-containerized-chatbot-backend-api-service-4855e6b66d46

Previous Video:
https://youtu.be/IqgsUwOnchE

💡 All Videos in Series:
https://www.youtube.com/playlist?list=PLU7aW4OZeUzxaHn6exh8aijLEf-src84S

Tags:
#DataIngestion #ETLPipeline #DockerTutorial #Neo4j #DataAutomation #TechTutorial #BigData #DataPipeline #PythonProgramming #BackendDev #DatabaseManagement #ScalableSolutions #SoftwareEngineering #DockerCompose #PythonTips #AdvancedETL #DataEngineering #TechTips #DataScience #Coding #CodeWithPrince

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Thank you for watching and see you in the next video!!