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This project involves migration from a traditional RDBMS to Neo4j for big data analytics. Using graph database technology, various business-critical questions are addressed, including identifying the employees who sold Tofu, the products sold with Tofu, the total number of products, top 5 products by sales, and the category with the highest sales.

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subhanjandas/RDBMS-to-GraphDB---Big-Data-Analytics-using-Neo4j

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RDBMS to GraphDB - Big Data Analytics using Neo4j

Introduction

The "RDBMS to GraphDB - Big Data Analytics using Neo4j" project aims to solve various business-critical questions using graph database technology. By migrating from a traditional relational database management system (RDBMS) to Neo4j, a graph database, the project provides a more efficient and effective way to analyze big data and drive product strategy.

Through this project, the following questions are addressed:

  • The employees who sold Tofu and the count of orders for each employee are listed.
  • The products that were sold along with Tofu are identified.
  • The total number of products in the dataset is determined.
  • The top 5 products by sales are ranked.
  • The category with the highest sales is identified and the products in that category are listed.

With the implementation of Neo4j, the project demonstrates the power of graph databases in managing big data and providing insights for decision making.

Tools Used

  • Neo4j
  • RDBMS

Project Screenshots

  • Screenshot 2023-01-31 at 12 43 42 PM
  • Screenshot 2023-01-31 at 12 44 57 PM
  • Screenshot 2023-01-31 at 12 45 34 PM
  • Screenshot 2023-01-31 at 12 46 21 PM
  • Screenshot 2023-01-31 at 12 46 37 PM

About

This project involves migration from a traditional RDBMS to Neo4j for big data analytics. Using graph database technology, various business-critical questions are addressed, including identifying the employees who sold Tofu, the products sold with Tofu, the total number of products, top 5 products by sales, and the category with the highest sales.

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