AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Which TWO options are valid ways to index content from Azure SQL Database into Azure AI Search? (Select TWO.)
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 the Push API to send data directly to the search index.
Option A is correct because the Push API (the REST/SDK endpoint that accepts JSON documents directly into an index) lets an application read rows from Azure SQL Database and send them straight to Azure AI Search, bypassing any intermediate storage. Option E is correct because Azure AI Search provides a built-in Azure SQL indexer (created via the portal, REST, or the Azure.Search.Documents SDK) that connects to Azure SQL Database using a change-tracking column (or high-water mark) to pull and index rows on a schedule. Option B is not a direct indexing method for Azure SQL Database; it inserts an unnecessary Data Factory copy to Blob Storage and then relies on a Blob indexer, which is a different data source. Option C is wrong because Azure AI Document Intelligence extracts text from documents (PDFs, images, forms), not from relational Azure SQL tables. Option D is wrong because Event Hubs is a streaming ingestion service and Azure AI Search has no Event Hubs indexer; streaming into the index would still require the Push API.
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 the Push API to send data directly to the search index.
Why this is correct
The Push API lets your code serialise SQL rows into JSON documents and POST them to the index, giving full control over transformation and scheduling. It works without an indexer, satisfying the requirement for a valid SQL-to-search ingestion path.
- ✗
Use Azure Data Factory to copy data to Blob Storage, then index from Blob.
Why it's wrong here
Data Factory copying to Blob Storage then indexing adds a staging hop; the indexer can already pull directly from Azure SQL Database via its change-tracking integrated pipeline. It is tempting because Blob indexing is well documented, but that suits file-based sources, not direct SQL ingestion.
- ✗
Use Azure AI Document Intelligence to extract data and push to index.
Why it's wrong here
Document Intelligence parses unstructured documents such as PDFs and images; it cannot read Azure SQL Database tables. It is tempting because it extracts fields into an index, but that fits form and invoice processing, not indexing structured relational rows.
- ✗
Use Azure Event Hubs to stream data into the search index.
Why it's wrong here
Event Hubs ingests high-volume telemetry streams, not relational rows; it cannot query Azure SQL Database or populate a search index schema. It is tempting because Event Hubs plus a custom function can feed an index, but that suits streaming event pipelines, not scheduled SQL table indexing.
- ✓
Use the Azure AI Search SQL Server indexer.
Why this is correct
The SQL Server indexer connects to Azure SQL Database, reads a table or view, and populates the index automatically, honouring change tracking for incremental updates. It is a supported pull-based mechanism, directly satisfying the requirement for indexing SQL content.
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Same concept, more angles
1 more way this is tested on AI-102
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which TWO configurations are required to enable Azure AI Search to index content from an Azure SQL database?
medium- A.Create a custom skillset for data enrichment
- B.Configure semantic ranking on the index
- ✓ C.Enable change tracking on the Azure SQL table
- ✓ D.Define a data source connection to the Azure SQL database
- E.Enable high availability on the Azure SQL database
Why C: Option C is correct because Azure AI Search's SQL indexer relies on change tracking (or a rowversion/timestamp column) to detect which rows have been inserted, updated, or deleted since the last indexing run, so enabling change tracking on the Azure SQL table is required for incremental indexing. Option D is correct because the indexer must be given a data source object that specifies the connection string, table or view, and change-tracking policy for the Azure SQL database, which is the mandatory link between the search service and the SQL data. Option A is not required because a skillset is only needed for AI enrichment (for example OCR, key phrase extraction, or embedding generation), not for basic SQL-to-index ingestion. Option B is not required because semantic ranking is an optional query-time feature that improves relevance; it does not affect whether content can be indexed. Option E is not required because high availability is a resilience/uptime configuration for the SQL database and is unrelated to the indexer's ability to read and index data.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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