corrections per final read through

HeidiSteen · HeidiSteen · commit 5930a6bc3336 · 2024-11-18T10:22:20.000-08:00
diff --git a/articles/search/search-get-started-portal-import-vectors.md b/articles/search/search-get-started-portal-import-vectors.md
@@ -8,7 +8,7 @@ ms.service: azure-ai-search
 ms.custom:
   - build-2024
 ms.topic: quickstart
-ms.date: 11/19/2024
+ms.date: 11/20/2024
 ---
 
 # Quickstart: Vectorize text and images by using the Azure portal
@@ -37,12 +37,12 @@ The **Import and vectorize data** wizard supports the following data sources:
 
 + [OneLake lakehouse (preview)](search-how-to-index-onelake-files.md).
 
-+ [Azure Cosmos DB](/azure/cosmos-db/nosql/quickstart-portal) for NoSQL, Mongo DB, and Apache Gremlin (preview).
++ [Azure Cosmos DB](/azure/cosmos-db/nosql/quickstart-portal) for NoSQL, MongoDB, and Apache Gremlin (preview).
 
 + [Azure SQL Database](/azure/azure-sql/database/single-database-create-quickstart), [Azure SQL Managed Instance](/azure/azure-sql/managed-instance/instance-create-quickstart), and Azure SQL Server virtual machines.
 
 > [!NOTE]
-> This quicktart provides steps for just those data sources that work with whole files: Azure Blob storage, ADLS Gen2, OneLake. For more information about using this wizard with other data soruces, see [Azure Table indexer](search-howto-indexing-azure-tables.md), [Cosmos DB for NoSQL indexer](search-howto-index-cosmosdb.md), and [Azuer SQL indexer](search-how-to-index-sql-database.md).
+> This quicktart provides steps for just those data sources that work with whole files: Azure Blob storage, ADLS Gen2, OneLake. To use the wizard with other data sources, see [Azure Table indexer](search-howto-indexing-azure-tables.md), [Cosmos DB for NoSQL indexer](search-howto-index-cosmosdb.md), and [Azuer SQL indexer](search-how-to-index-sql-database.md).
 
 ### Supported embedding models
 
@@ -471,6 +471,7 @@ Search Explorer accepts text strings as input and then vectorizes the text for v
           }
        ]
    }
+   ```
 
 ## Clean up
 
diff --git a/articles/search/search-how-to-index-sql-database.md b/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 and load a table in Azure SQL Database.
+Use these instructions to create and load a table in Azure SQL Database for testing purposes.
 
 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.
 
@@ -102,7 +102,7 @@ Now that you have a database table, you can use the Azure portal, REST client, o
 
 ## 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.
+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 is similar for both wizards.
 
 1. [Start the wizard](search-import-data-portal.md#starting-the-wizards).
 
diff --git a/articles/search/search-howto-index-cosmosdb.md b/articles/search/search-howto-index-cosmosdb.md
@@ -24,7 +24,7 @@ Because terminology can be confusing, it's worth noting that [Azure Cosmos DB in
 
 ## Prerequisites
 
-+ An [Azure Cosmos DB account, database, container and items](/azure/cosmos-db/sql/create-cosmosdb-resources-portal). Use the same region for both Azure AI Search and Azure Cosmos DB for lower latency and to avoid bandwidth charges.
++ An [Azure Cosmos DB account, database, container, and items](/azure/cosmos-db/sql/create-cosmosdb-resources-portal). Use the same region for both Azure AI Search and Azure Cosmos DB for lower latency and to avoid bandwidth charges.
 
 + An [automatic indexing policy](/azure/cosmos-db/index-policy) on the Azure Cosmos DB collection, set to [Consistent](/azure/cosmos-db/index-policy#indexing-mode). This is the default configuration. Lazy indexing isn't recommended and can result in missing data.
 
@@ -34,7 +34,7 @@ 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 container and database in Cosmos DB.
+Use these instructions to create a container and database in Cosmos DB for testing purposes.
 
 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.
 
@@ -62,9 +62,11 @@ Use these instructions to create a container and database in Cosmos DB.
 
 Now that you have a container, you can use the Azure portal, REST client, or an Azure SDK to index your data.
 
+The Description field provides the most verbose content. You should target this field for full text search and optional vector queries.
+
 ## 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.
+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 is similar for both wizards.
 
 1. [Start the wizard](search-import-data-portal.md#starting-the-wizards).
 
@@ -76,7 +78,7 @@ You can use either the **Import data** wizard or **Import and vectorize data** w
 
 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 Cosmos DB that grants **Cosmos DB Account Reader Role** and [**Cosmos DB Built-in Data Reader Role**](/azure/cosmos-db/how-to-setup-rbac#built-in-role-definitions) permissions to the identity, your indexer can connect to Cosmos DB using Microsoft Entra ID and roles.
+   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 Cosmos DB](/azure/cosmos-db/how-to-setup-rbac#built-in-role-definitions) that grants **Cosmos DB Account Reader** and **Cosmos DB Built-in Data Reader** permissions to the identity, your indexer can connect to Cosmos DB using Microsoft Entra ID and roles.
 
 1. For the **Import and vectorize data** wizard, you can specify options for change and deletion tracking.
 
@@ -140,7 +142,7 @@ The data source definition specifies the data to index, credentials, and policie
 
 Indexers can connect to a collection using the following connections.
 
-Avoid port numbers in the endpoint URL. If you include the port number, the connection will fail. 
+Avoid port numbers in the endpoint URL. If you include the port number, the connection fails. 
 
 | Full access connection string |
 |-----------------------------------------------|
diff --git a/articles/search/search-howto-indexing-azure-tables.md b/articles/search/search-howto-indexing-azure-tables.md
@@ -18,7 +18,7 @@ ms.date: 11/20/2024
 
 In this article, learn how to configure an [**indexer**](search-indexer-overview.md) that imports content from Azure Table Storage and makes it searchable in Azure AI Search. Inputs to the indexer are your entities, in a single table. Output is a search index with searchable content and metadata stored in individual fields.
 
-This article supplements [**Create an indexer**](search-howto-create-indexers.md) with information that's specific to indexing from Azure Table Storage. It uses the REST APIs to demonstrate a three-part workflow common to all indexers: create a data source, create an index, create an indexer. Data extraction occurs when you submit the Create Indexer request.
+This article supplements [**Create an indexer**](search-howto-create-indexers.md) with information that's specific to indexing from Azure Table Storage. It uses the Azure portal and REST APIs to demonstrate a three-part workflow common to all indexers: create a data source, create an index, create an indexer. Data extraction occurs when you submit the Create Indexer request.
 
 ## Prerequisites
 
@@ -32,7 +32,7 @@ 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 Storage.
+Use these instructions to create a table in Azure Storage for testing purposes.
 
 1. Sign in to the Azure portal, navigate to your storage account, and create a table named *hotels*. 
 
@@ -46,13 +46,15 @@ Use these instructions to create a table in Azure Storage.
 
 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.
+1. Accept the defaults. 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.
 
+The Description field provides the most verbose content. You should target this field for full text search and optional vector queries.
+
 ## 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.
+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 is similar for both wizards.
 
 1. [Start the wizard](search-import-data-portal.md#starting-the-wizards).
 
diff --git a/articles/search/search-import-data-portal.md b/articles/search/search-import-data-portal.md
@@ -9,7 +9,7 @@ ms.author: heidist
 ms.service: azure-ai-search
 ms.custom:
 ms.topic: concept-article
-ms.date: 11/19/2024
+ms.date: 11/20/2024
 ---
 
 # Import data wizards in the Azure portal
