Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are building an enrichment pipeline with Azure AI Search. A skillset detects entities and outputs bounding-box coordinates, and another skill generates thumbnail images of embedded pictures. You must persist the bounding-box data in Azure Table Storage and store the thumbnails as individual blobs by using a knowledge store. Which projection configuration meets the requirements?
Add a table projection for the bounding-box output and an object projection for the thumbnail output.
Add two object projections, one for bounding boxes and one for thumbnails.
Add an object projection for the bounding-box output and a file projection for the thumbnail output.
Add a table projection for the bounding-box output and a file projection for the thumbnail output.
Table projections are intended for structured, tabular data and write records to Azure Table Storage. Bounding-box coordinates are structured name-value pairs, so a table projection is appropriate. Thumbnails are binary image files, which knowledge stores persist through file projections that place each file in Azure Blob Storage. Object projections store JSON documents, not binary files, so they are unsuitable for thumbnails. Using object or duplicate object projections would not satisfy both storage requirements.
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Microsoft Azure AI Engineer Associate AI-102
Implement knowledge mining and information extraction solutions
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