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articles/search/cognitive-search-concept-intro.md

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## Next steps
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+ [Quickstart: Try AI enrichment in a portal walk-through](cognitive-search-quickstart-blob.md)
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+ [Quickstart: Create a text translation and entity skillset](cognitive-search-quickstart-blob.md)
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+ [Quickstart: Create an OCR image skillset](cognitive-search-quickstart-ocr.md)
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+ [Tutorial: Learn about the AI enrichment REST APIs](cognitive-search-tutorial-blob.md)
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+ [Skillset concepts](cognitive-search-working-with-skillsets.md)
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+ [Knowledge store concepts](knowledge-store-concept-intro.md)

articles/search/cognitive-search-concept-troubleshooting.md

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This article contains a list of tips and tricks to keep you moving as you get started with AI enrichment capabilities in Azure Cognitive Search.
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If you have not done so already, step through the [Tutorial: Learn how to call AI enrichment APIs](cognitive-search-quickstart-blob.md) for practice in applying AI enrichments to a blob data source.
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If you haven't already, step through either the [Create a text translation and entity skillset](cognitive-search-quickstart-blob.md) or [Create an OCR image skillset](cognitive-search-quickstart-ocr.md) quickstarts for an introduction to enrichment of blob data.
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## Tip 1: Start with a small dataset
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The best way to find issues quickly is to increase the speed at which you can fix issues. The best way to reduce the indexing time is by reducing the number of documents to be indexed.

articles/search/cognitive-search-resources-documentation.md

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## Hands on walkthroughs
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+ [Quickstart: Create a cognitive skillset in the Azure portal](cognitive-search-quickstart-blob.md)
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+ [Quickstart: Create a text translation and entity skillset](cognitive-search-quickstart-blob.md)
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+ [Quickstart: Create an OCR image skillset](cognitive-search-quickstart-ocr.md)
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+ [Tutorial: Enriched indexing with AI](cognitive-search-tutorial-blob.md)
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+ [Tutorial: Diagnose, repair, and commit changes to your skillset with Debug Sessions](cognitive-search-tutorial-debug-sessions.md)
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articles/search/search-get-started-portal.md

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Create your first search index using the **Import data** wizard and a built-in sample data source consisting of fictitious hotel data. The wizard guides you through the creation of a search index (hotels-sample-index) so that you can write interesting queries within minutes.
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Although you won't use the options in this quickstart, the wizard includes a page for AI enrichment so that you can extract text and structure from image files and unstructured text. For a similar walkthrough that includes AI enrichment, see [Quickstart: Create a cognitive skillset](cognitive-search-quickstart-blob.md).
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Although you won't use the options in this quickstart, the wizard includes a page for AI enrichment so that you can extract text and structure from image files and unstructured text. For a similar walkthrough that includes AI enrichment, see [text translation and entity skillset](cognitive-search-quickstart-blob.md) or [OCR image skillset](cognitive-search-quickstart-ocr.md) quickstarts.
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## Prerequisites
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articles/search/search-import-data-portal.md

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If you're using the wizard for proof-of-concept testing, this article explains the internal workings of the wizard so that you can use it more effectively.
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This article is not a step by step. For help using the wizard with built-in sample data, see the [Quickstart: Create a search index](search-get-started-portal.md) or [Quickstart: Create a skillset](cognitive-search-quickstart-blob.md).
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This article is not a step by step. For help using the wizard with built-in sample data, see the [Quickstart: Create a search index](search-get-started-portal.md) or [Quickstart: Create a text translation and entity skillset](cognitive-search-quickstart-blob.md).
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## Starting the wizard
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