Data Engineering
Information Retrieval
Finding the most relevant documents or data from a large collection based on a query, like a smarter search engine.
Definition
The science of searching for relevant information within large collections of data. Modern approaches combine keyword search with semantic vector search for better results. Core component of RAG systems.
Why it matters
The quality of retrieval directly determines the quality of RAG-powered AI responses, garbage retrieval, garbage answers.
Related terms in Data Engineering
Batch Processing
Processing a large group of data all at once on a schedule, rather than one piece at a time in real-time.
Chunking Strategies
Chopping up long documents into small, bite-sized pieces so an AI can search and read them easily.
Data Augmentation
Creating fake but realistic training examples (like flipping or rotating images) to give the AI more data to learn from.
Data Labeling
The human work of tagging data with correct answers so an AI can learn from it, like marking photos as "cat" or "dog."
From vocabulary to outcomes
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