Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are a solution architect at a financial services company. You need to implement a knowledge mining solution that extracts information from annual reports (PDF) of publicly traded companies. The reports contain financial tables, executive summaries, and legal disclaimers. The solution must: (1) extract the company name, fiscal year, revenue, net income, and CEO name; (2) redact any personally identifiable information (PII) like email addresses and phone numbers before indexing; (3) index the extracted data in Azure AI Search; (4) allow users to query using natural language (e.g., 'Which company had the highest revenue in 2023?'). The reports are uploaded to an Azure Blob Storage container. You have access to Azure AI Services and Azure OpenAI. Which combination of services and configurations should you use?
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
✓
Use Azure AI Document Intelligence custom extraction model trained on annual reports to extract fields. In the Azure AI Search pipeline, add a PII detection skill to redact PII. Enable semantic search for natural language queries.
Azure AI Document Intelligence can be trained with a custom extraction model to accurately extract specific financial fields like company name, fiscal year, revenue, net income, and CEO name from annual report PDFs. The PII detection skill in the Azure AI Search enrichment pipeline redacts sensitive information such as email addresses and phone numbers before indexing. Enabling semantic search allows users to query using natural language. Option B relies on Azure AI Vision OCR and Azure AI Language entity extraction, which are less precise for structured table extraction and cannot guarantee the specific fields needed. Option C uses generic skills like Document Layout and Entity Recognition, which are not tailored for financial data extraction and may miss critical fields. Option D uses GPT-4, which can be inconsistent for structured data extraction from tables and does not include built-in PII redaction within the search pipeline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Azure AI Document Intelligence custom extraction model trained on annual reports to extract fields. In the Azure AI Search pipeline, add a PII detection skill to redact PII. Enable semantic search for natural language queries.
Why this is correct
Best approach for structured extraction, PII redaction, and natural language query.
- ✗
Use Azure AI Vision OCR to extract text from PDFs, then use Azure AI Language to extract entities and key phrases. Index in Azure AI Search with semantic search.
Why it's wrong here
OCR is not ideal for digital PDFs; no PII redaction.
- ✗
Use Azure AI Search with blob indexer, include a skillset with Document Layout skill, Entity Recognition skill (for financial entities), and Key Phrase Extraction. Enable semantic search.
Why it's wrong here
No PII redaction; Entity Recognition may not extract custom financial data accurately.
- ✗
Use Azure OpenAI GPT-4 to process each report via a custom extraction prompt, then send extracted JSON to Azure AI Search. Enable semantic search.
Why it's wrong here
GPT-4 may be costly and inconsistent for table extraction; lacks PII redaction.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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