Technical requirements
You will need to be familiar with SQL and Cypher. We will be using SQLite and Neo4j to understand the various aspects of data modeling. We will use the following tools in this chapter:
- Neo4j Desktop (https://neo4j.com/docs/desktop-manual/current/) or Neo4j Aura (https://neo4j.com/docs/aura/)
- The H&M dataset to create the recommendation system: This dataset is available at https://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/overview (Carlos García Ling, ElizabethHMGroup, FridaRim, inversion, Jaime Ferrando, Maggie, neuraloverflow, and xlsrln. H&M Personalized Fashion Recommendations. 2022. Kaggle)
Remember from Chapter 3 that a good graph data model makes the retrieval part of RAG flow more effective. It makes retrieving relevant data faster and easier. You may revisit Chapter 3 for a quick recap of graph data modeling. In this chapter, we model the data with time as a dimension. The chain of transactions...
