Table storage updates, wizards supported data sources

Author: HeidiSteen

articles/search/search-how-to-index-sql-database.md

@@ -42,7 +42,7 @@ To work through the examples in this article, you need the Azure portal or a [RE
 
 ## Try with sample data
 
-Use these instructions to create a table in Azure SQL that you can use with an indexer on Azure AI Search. The portal approach, using either import data wizard, is the quickest way to create and load an index from a table in a SQL database.
+Use these instructions to create and load a table in Azure SQL Database.
 
 1. [Download hotels-azure-sql.sql](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-sql) from GitHub to create a table on Azure SQL Database that contains a subset of the sample hotels data set.
 
@@ -95,6 +95,8 @@ Use these instructions to create a table in Azure SQL that you can use with an i
 
 The Description field provides the most verbose content. You should target this field for full text search and optional vector queries.
 
+Now that you have a database table, you can use the Azure portal, REST client, or an Azure SDK to index your data.
+
 > [!TIP]
 > Another resource that provides sample content and code can be found on [Azure-Samples/SQL-AI-samples](https://github.com/Azure-Samples/SQL-AI-samples/tree/main/AzureSQLACSSamples/src).
 

articles/search/search-howto-index-cosmosdb.md

@@ -1,8 +1,9 @@
 ---
 title: Azure Cosmos DB NoSQL indexer
 titleSuffix: Azure AI Search
-description: Set up a search indexer to index data stored in Azure Cosmos DB for full text search in Azure AI Search. This article explains how index data using the NoSQL API protocol.
+description: Set up a search indexer to index data stored in Azure Cosmos DB for vector and full text search in Azure AI Search. This article explains how index data using the NoSQL API protocol.
 
+manager: nitinme
 author: mgottein
 ms.author: magottei
 ms.service: azure-ai-search
@@ -29,11 +30,11 @@ Because terminology can be confusing, it's worth noting that [Azure Cosmos DB in
 
 + Read permissions. A "full access" connection string includes a key that grants access to the content, but if you're using identities (Microsoft Entra ID), make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) is assigned both **Cosmos DB Account Reader Role** and [**Cosmos DB Built-in Data Reader Role**](/azure/cosmos-db/how-to-setup-rbac#built-in-role-definitions).
 
-To work through the examples in this article, you need the Azure portal or a [REST client](search-get-started-rest.md). If you're using Azure portal, make sure that access to all public networks is enabled in Cosmos DB and that the client has access via an inbound rule. For a REST client that runs locally, configure the network firewall to allow inbound access from your device IP address. Other approaches for creating a Cosmos DB indexer include Azure SDKs.
+To work through the examples in this article, you need the Azure portal or a [REST client](search-get-started-rest.md). If you're using Azure portal, make sure that access to all public networks is enabled. Other approaches for creating a Cosmos DB indexer include Azure SDKs.
 
 ## Try with sample data
 
-Use these instructions to create a container and database in Cosmos DB that you can use with an indexer on Azure AI Search. The portal approach, using either import data wizard, is the quickest way to create and load an index from a container in Cosmos DB.
+Use these instructions to create a container and database in Cosmos DB.
 
 1. [Download HotelsData_toCosmosDB.JSON](https://github.com/HeidiSteen/azure-search-sample-data/blob/main/hotels/HotelsData_toCosmosDB.JSON) from GitHub to create a container in Cosmos DB that contains a subset of the sample hotels data set.
 
@@ -59,7 +60,7 @@ Use these instructions to create a container and database in Cosmos DB that you
 
 1. Select **Execute query** to run the query and view results. You should have 50 hotel documents.
 
-You can now use this content for indexing in the Azure portal, REST client, or an Azure SDK.
+Now that you have a container, you can use the Azure portal, REST client, or an Azure SDK to index your data.
 
 ## Use the Azure portal
 
@@ -81,7 +82,7 @@ You can use either the **Import data** wizard or **Import and vectorize data** w
 
    [Change detection](#incremental-indexing-and-custom-queries) is supported by default through a `_ts` field (timestamp). If you upload content using the approach described in [Try with sample data](#try-with-sample-data), the collection is created with a `_ts` field.
 
-   [Deletion detection](#indexing-deleted-documents) requires that you have a pre-existing top-level field in the index that can be used as a soft-delete flag. It should be a Boolean field (you could name it IsDeleted). In the search index, add a corresponding search field called *IsDeleted* set to retrievable and filterable. Specify `true` as the soft-delete value.
+   [Deletion detection](#indexing-deleted-documents) requires that you have a pre-existing top-level field in the collection that can be used as a soft-delete flag. It should be a Boolean field (you could name it IsDeleted). Specify `true` as the soft-delete value. In the search index, add a corresponding search field called *IsDeleted* set to retrievable and filterable. 
 
 1. Continue with the remaining steps to complete the wizard:
 

articles/search/search-howto-indexing-azure-tables.md

@@ -1,17 +1,17 @@
 ---
 title: Azure table indexer
 titleSuffix: Azure AI Search
-description: Set up a search indexer to index data stored in Azure Table Storage for full text search in Azure AI Search.
+description: Set up a search indexer to index data stored in Azure Table Storage for vector and full text search in Azure AI Search.
 
-manager: vinodva
+manager: nitinme
 author: mgottein
 ms.author: magottei
 
 ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 08/23/2024
+ms.date: 11/20/2024
 ---
 
 # Index data from Azure Table Storage
@@ -26,11 +26,61 @@ This article supplements [**Create an indexer**](search-howto-create-indexers.md
 
 + Tables containing text. If you have binary data, consider [AI enrichment](cognitive-search-concept-intro.md) for image analysis.
 
-+ Read permissions on Azure Storage. A "full access" connection string includes a key that gives access to the content, but if you're using Azure roles, make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) has **Data and Reader** permissions.
++ Read permissions on Azure Storage. A "full access" connection string includes a key that gives access to the content, but if you're using Azure roles, make sure the [search service managed identity](search-howto-managed-identities-data-sources.md) has **Reader and Data Access** permissions.
 
-+ Use a [REST client](search-get-started-rest.md) to formulate REST calls similar to the ones shown in this article.
+To work through the examples in this article, you need the Azure portal or a [REST client](search-get-started-rest.md). If you're using Azure portal, make sure that access to all public networks is enabled. Other approaches for creating an Azure Table indexer include Azure SDKs.
 
-## Define the data source
+## Try with sample data
+
+Use these instructions to create a table in Azure Storage.
+
+1. Sign in to the Azure portal, navigate to your storage account, and create a table named *hotels*. 
+
+1. [Install Azure Storage Explorer](https://azure.microsoft.com/products/storage/storage-explorer/#Download-4).
+
+1. [Download HotelsData_toAzureSearch.csv](https://github.com/HeidiSteen/azure-search-sample-data/blob/main/hotels/HotelsData_toAzureSearch.csv) from GitHub. This file is a subset of the built-in hotels sample dataset. It omits the rooms collection, translated descriptions, and geography coordinates.
+
+1. In Azure Storage Explorer, sign in to Azure, select your subscription, and then select your storage account.
+
+1. Open **Tables** and select *hotels*.
+
+1. Select **Import** on the command bar, and then select the *HotelsData_toAzureSearch.csv* file.
+
+1. Accept the default. Select **Import** to load the data.
+
+You should have 50 hotel records in the table with an autogenerated partitionKey, rowKey, and timestamp. You can now use this content for indexing in the Azure portal, REST client, or an Azure SDK.
+
+## Use the Azure portal
+
+You can use either the **Import data** wizard or **Import and vectorize data** wizard to automate indexing from an SQL database table or view. The data source configuration similar for both wizards.
+
+1. [Start the wizard](search-import-data-portal.md#starting-the-wizards).
+
+1. On **Connect to your data**, select or verify that the data source type is either *Azure Table Storage* or that the data selection fields prompt for tables.
+
+   The data source name refers to the data source connection object in Azure AI Search. If you use the vector wizard, your data source name is autogenerated using a custom prefix specified at the end of the wizard workflow.
+
+1. Specify the storage account and table name. The query is optional. It's useful if you have specific columns you want to import.
+
+1. Specify an authentication method, either a managed identity or built-in API key. If you don't specify a managed identity connection, the portal uses the key.
+
+   If you [configure Azure AI Search to use a managed identity](search-howto-managed-identities-data-sources.md), and you create a role assignment on Azure Storage that grants **Reader and Data Access** permissions to the identity, your indexer can connect to table storage using Microsoft Entra ID and roles.
+
+1. For the **Import and vectorize data** wizard, you can specify options for deletion detection,
+
+   Deletion detection requires that you have a pre-existing field in the table that can be used as a soft-delete flag. It should be a Boolean field (you could name it IsDeleted). Specify `true` as the soft-delete value. In the search index, add a corresponding search field called *IsDeleted* set to retrievable and filterable. 
+
+1. Continue with the remaining steps to complete the wizard:
+
+   + [Quickstart: Import data wizard](search-get-started-portal.md)
+
+   + [Quickstart: Import and vectorize data wizard](search-get-started-portal-import-vectors.md)
+
+## Use the REST APIs
+
+This section demonstrates the REST API calls that create a data source, index, and indexer.
+
+### Define the data source
 
 The data source definition specifies the source data to index, credentials, and policies for change detection. A data source is an independent resource that can be used by multiple indexers.
 
@@ -69,7 +119,7 @@ A data source definition can also include [soft deletion policies](search-howto-
 
 <a name="Credentials"></a>
 
-### Supported credentials and connection strings
+#### Supported credentials and connection strings
 
 Indexers can connect to a table using the following connections.
 
@@ -98,7 +148,7 @@ Indexers can connect to a table using the following connections.
 
 <a name="Performance"></a>
 
-### Partition for improved performance
+#### Partition for improved performance
 
 By default, Azure AI Search uses the following internal query filter to keep track of which source entities have been updated since the last run: `Timestamp >= HighWaterMarkValue`. Because Azure tables don’t have a secondary index on the `Timestamp` field, this type of query requires a full table scan and is therefore slow for large tables.
 
@@ -116,7 +166,7 @@ To avoid a full scan, you can use table partitions to narrow the scope of each i
 
   + With this approach, if you need to trigger a full reindex, reset the data source query in addition to [resetting the indexer](search-howto-run-reset-indexers.md). 
 
-## Add search fields to an index
+### Add search fields to an index
 
 In a [search index](search-what-is-an-index.md), add fields to accept the content and metadata of your table entities.
 
@@ -156,7 +206,7 @@ In a [search index](search-what-is-an-index.md), add fields to accept the conten
 
    Using the same names and compatible [data types](/rest/api/searchservice/supported-data-types) minimizes the need for [field mappings](search-indexer-field-mappings.md). When names and types are the same, the indexer can determine the data path automatically.
 
-## Configure and run the table indexer
+### Configure and run the table indexer
 
 Once you have an index and data source, you're ready to create the indexer. Indexer configuration specifies the inputs, parameters, and properties controlling run time behaviors.
 
@@ -199,7 +249,17 @@ An indexer runs automatically when it's created. You can prevent this by setting
 
 ## Check indexer status
 
-To monitor the indexer status and execution history, send a [Get Indexer Status](/rest/api/searchservice/indexers/get-status) request:
+To monitor the indexer status and execution history, check the indexer execution history in the Azure portal, or send a [Get Indexer Status](/rest/api/searchservice/indexers/get-status) REST APIrequest
+
+### [**Portal**](#tab/portal-check-indexer)
+
+1. On the search service page, open **Search management** > **Indexers**.
+
+1. Select an indexer to access configuration and execution history.
+
+1. Select a specific indexer job to view details, warnings, and errors.
+
+### [**REST**](#tab/rest-check-indexer)
 
 ```http
 GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
@@ -241,6 +301,8 @@ The response includes status and the number of items processed. It should look s
     }
 ```
 
+---
+
 Execution history contains up to 50 of the most recently completed executions, which are sorted in the reverse chronological order so that the latest execution comes first.
 
 ## Next steps

articles/search/search-import-data-portal.md

@@ -29,6 +29,13 @@ This article isn't a step by step. For help with using the wizard with sample da
 + [Quickstart: Create a vector index](search-get-started-portal-import-vectors.md)
 + [Quickstart: image search (vectors)](search-get-started-portal-image-search.md)
 
+## Supported data sources and scenarios
+
+| Wizard | Skills | Azure blobs | ADLS Gen2 | Azure tables | Azure files | Cosmos DB | Azure SQL | OneLake | SharePoint | MySQL |
+|--|--|--|--|--|--|--|--|--|--|--|
+|Import data | No embedding skills| ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+|Import and vectorize data | All skills | ✅ | ✅ |✅ | ❌ | ✅| ✅ |  ✅ | ❌ | ❌ |
+
 ## What the wizards create
 
 The import wizards create the objects described in the following table. After the objects are created, you can review their JSON definitions in the portal or call them from code.