What's changed: Deepened AI-102 Chapter 4 (ja figures; comparison tables/scenarios/FAQ/traps/deep paragraphs in all sections)
4.1Knowledge Mining with Azure AI Search
Understand Azure AI Search, which builds a searchable index from large document sets. Learn indexers, skillsets (AI enrichment), indexes, and the basics of vector search / RAG that pair with generative AI.
Azure AI Search turns large, scattered documents into searchable knowledge: ingest data, enrich it with AI, index it, and use it for search or chat.
4.1.1Building a search index
For information extraction, Azure AI Content Understanding (Foundry Tools) summarizes, classifies, and extracts attributes/entities across documents, images, audio, and video. For insights from video, use Azure AI Video Indexer.
- Indexer: automatically ingests data from a data source (Blob/SQL/Cosmos, etc.).
- Skillset (AI enrichment): enrich content with OCR, key phrases, entities, translation, and vector embeddings.
- Index: a set of searchable fields supporting full-text, semantic, and vector search.
- RAG: combine with generative AI for retrieval-augmented generation, grounding answers in retrieved content.
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