- Lab
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Libraries: If you want this lab, consider one of these libraries.
- Cloud
Implement a Basic Azure AI Search Solution
In this lab, you will create and validate a basic Azure AI Search solution for a small product catalogue. You will inspect a packaged dataset, define a searchable index, load the documents through an Azure AI Search indexer, and use Search Explorer to run keyword, filter, and sorting queries. By the end of the lab, you will have a working search index and evidence that the expected documents can be retrieved.
Lab Info
Table of Contents
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Challenge
Access the Azure AI Search service and review the source dataset
- Open the pre-created Azure AI Search service and confirm that it is available.
- Review the packaged product dataset and identify the fields that should be included in the search index.
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Challenge
Create a search index for the product dataset
- Create an index that represents the fields in the packaged product dataset.
- Configure the document key and the required searchable, filterable, sortable, facetable, and retrievable attributes.
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Challenge
Load documents into the search index
- Configure a data source and indexer that connect the packaged dataset to the search index.
- Run the indexer and confirm that the expected documents are processed without failures.
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Challenge
Query and validate the search index
- Use Search Explorer to run keyword, filter, and sorting queries against the index.
- Confirm that the expected documents and document count are returned.
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