AI-102 Plan and manage an Azure AI solution Practice Question
Your Azure AI Document Intelligence model is failing to extract tables from scanned PDFs. The PDFs are low-quality images. What should you do first?
⚠ Common exam trap
The trap here is that candidates often jump to retraining or image enhancement without realizing that Document Intelligence's table extraction is entirely dependent on the quality of the OCR output, and the first diagnostic step must be to check that foundational layer.
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
✓
Verify that the Read OCR step is extracting text correctly.
The Read OCR step is the foundational layer for table extraction in Azure AI Document Intelligence. If the OCR cannot accurately recognize text from low-quality images, subsequent table extraction models will fail regardless of training or image enhancement. Verifying OCR output first isolates whether the issue is at the text recognition stage or the table parsing stage, following a systematic troubleshooting approach.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Verify that the Read OCR step is extracting text correctly.
Why this is correct
Read OCR is the foundation for table extraction.
- ✗
Use Azure AI Computer Vision to enhance the image.
Why it's wrong here
Image enhancement is separate from Document Intelligence pipeline.
- ✗
Retrain the model with more table examples.
Why it's wrong here
Training won't fix poor OCR quality.
- ✗
Use a higher resolution scanner for input PDFs.
Why it's wrong here
Helpful but not the first diagnostic step.
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Written by Johnson Ajibi, MSc IT Security
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