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Extract Information with Azure AI Content Understanding

This section of the Microsoft AI-102: Designing and Implementing a Microsoft Azure AI Solution exam covers extracting structured information with Azure AI Content Understanding. Below are study notes for each sub-topic, with links to Microsoft documentation, exam tips, and key facts

Create an OCR Pipeline to Extract Text from Images and Documents

📖 Docs: OCR in Azure AI

Overview

  • OCR (Optical Character Recognition) extracts printed or handwritten text
  • Can be applied to:
    • Images
    • PDFs
    • Scanned documents

Key Points

  • OCR pipeline = ingest → detect regions → extract text → output structured format
  • Supports multiple languages
  • Can be combined with Document Intelligence for advanced parsing

Exam Tip

OCR extracts text only, not structure or semantics

Summarize, Classify, and Detect Attributes of Documents

📖 Docs: What is Azure AI Content Understanding

Overview

  • Azure AI Content Understanding applies NLP to documents
  • Capabilities:
    • Summarization (extractive and abstractive)
    • Classification (categorize documents by type)
    • Attribute detection (metadata, topics, sentiment)

Key Points

  • Uses Azure AI Language models
  • Custom classification available for domain-specific needs
  • Summarization reduces large documents into key points

Use Case

Summarizing legal contracts into executive briefs

Extract Entities, Tables, and Images from Documents

📖 Docs: Use Document Intelligence models

Overview

  • Beyond OCR, advanced extraction retrieves:
    • Entities (names, organizations, dates)
    • Tables (rows, columns, cell values)
    • Embedded images

Key Points

  • Structured outputs in JSON or tables
  • Requires Document Intelligence models
  • Entities align with AI Language recognition

Exam Tip

If scenario requires table or entity extraction → Document Intelligence, not OCR

Process and Ingest Documents, Images, Videos, and Audio with Azure AI Content Understanding

📖 Docs: Quickstart: Use Content Understanding with a single file

Overview

  • Azure AI Content Understanding = multimodal ingestion and enrichment
  • Supports:
    • Documents
    • Images
    • Video
    • Audio

Key Points

  • Provides a unified pipeline for enrichment
  • Can integrate OCR, NLP, entity extraction, summarization
  • Outputs structured insights for downstream apps or AI Search

Use Case

Processing compliance documents, extracting entities, and storing enriched data in Azure AI Search

Quick‑fire revision sheet

  • 📌 OCR extracts printed/handwritten text from images/docs
  • 📌 Summarization + classification provide condensed insights
  • 📌 Entities, tables, and images extracted via Document Intelligence
  • 📌 Content Understanding ingests docs, images, video, audio
  • 📌 Outputs structured data for search and AI pipelines