Converting CSV Data to a Neo4j Graph Database To RAG system | GraphRAG from Scratch #demo

I recently embarked on a data adventure with the Northwind Traders Sales Dataset that I discovered on GitHub in CSV format. My goal was to convert this dataset into a Neo4j graph database to explore the power of graph databases for data analysis.

Here's a glimpse of my journey:

Data Cleaning with Pandas: I used Python's pandas library to clean the data, merge tables, drop unwanted columns, and perform various data transformations. Pandas made it easy to handle and manipulate the data efficiently.

Cypher Code for Data Insertion: After preparing the data, I wrote Cypher code to insert the cleaned data into a Neo4j graph database. This involved creating nodes and relationships to represent the data structure accurately.

Neo4j Cloud Instance: I utilized a free Neo4j cloud instance to host my graph database. The cloud platform provided an easy-to-use interface and powerful features to manage and query my data.

The combination of pandas for data preprocessing and Neo4j for graph representation has been incredibly powerful. It has opened up new possibilities for visualizing and analyzing the data relationships in ways that were not possible with traditional databases.

If you're interested in data analysis, graph databases, or just love exploring new technologies, I highly recommend giving this a try. Feel free to reach out if you have any questions or want to share your own experiences!

#DataScience #GraphDatabases #Neo4j #Python #Pandas #DataCleaning #Cypher #DataAnalysis #TechJourney #pandas #programming #knowledgegraph #rag #RetrievalAugementedGeneration
#GraphRAG

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[allanbakwanamaha]

Thanks for the awesome content, my humble request is for you to make a series of how you implemented this and also use Langchain