AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are designing a knowledge mining solution that must extract tables from scanned invoices stored in Azure Blob Storage and make the table cells searchable. The invoices are in PDF and JPEG formats. Which Azure AI service should you use to extract the tables before loading the data into Azure AI Search?
⚠ Common exam trap
The trap here is assuming the Azure AI Search OCR skill can extract tables, when it only produces unstructured text and loses the row and column relationships.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Document Intelligence
Azure AI Document Intelligence provides prebuilt and custom models that detect tables and return structured cell data with row and column indices. It accepts PDF and image inputs, which matches the scanned invoice formats. The extracted table structure can then be shaped and indexed into Azure AI Search so that table cells are searchable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Language
Why it's wrong here
Azure AI Language provides text analytics such as entity recognition, key phrase extraction, and sentiment analysis. It operates on text that is already extracted and does not perform OCR or table detection from scanned documents. Using it alone cannot read the invoice images or reconstruct table structure.
- ✗
Azure AI Search OCR skill
Why it's wrong here
The OCR skill in Azure AI Search extracts text from images but does not detect or reconstruct tables. It produces plain text that loses row and column structure, making it impossible to map individual cells to fields. For structured table extraction from invoices, a document intelligence service is required instead.
- ✗
Azure AI Vision Image Analysis
Why it's wrong here
Image Analysis can extract text from images and describe visual content, but it does not provide structured table extraction with row and column relationships. It would return OCR text without the tabular structure needed to make individual cells searchable as fields. For invoices with tables, a document-oriented extraction service is required.
- ✓
Azure AI Document Intelligence
Why this is correct
Azure AI Document Intelligence is designed to extract structured data from documents, including tables with row and column relationships, using prebuilt or custom models. It supports PDF and image inputs such as JPEG, making it suitable for scanned invoices. Its output can be transformed and loaded into Azure AI Search for searchable table content.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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