Chunking Strategies for Structured Data in RAG Systems
While developing RAG pipelines across various enterprise use cases, a stakeholder asked me a question that stopped me mid conversation: "Can our database become a source for our knowledge base, just like our SharePoint documents? Can RAG give us answers by querying the database directly?"
The honest answer is yes, but only if you rethink how you chunk the data before it enters the knowledge base.
Most RAG chunking strategies are optimized for prose, i.e. documentation, articles, support tickets, web content, etc. The moment you ingest a CSV or metadata catalog export, they break down.
Here's why: a table with 50 rows becomes a single chunk whose embedding captures a blurred average of all rows. When a user asks "What is the city with ID=5?", the retriever can't isolate that specific row because the chunk represents everything and nothing at once.
This article covers six chunking strategies for...
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