Merge pull request #125088 from ArieHein/Spelling-Wave-17

Spelling Fixes

Author: v-dirichards

articles/data-factory/compute-linked-services.md

@@ -86,7 +86,7 @@ The following JSON defines a Linux-based on-demand HDInsight linked service. The
         "value": "<service principal key>",
         "type": "SecureString"
       },
-      "tenant": "<tenent id>",
+      "tenant": "<tenant id>",
       "clusterResourceGroup": "<resource group name>",
       "version": "3.6",
       "osType": "Linux",
@@ -195,7 +195,7 @@ You can also specify the following properties for the granular configuration of
             "value": "<service principal key>",
             "type": "SecureString"
           },
-          "tenant": "<tenent id>",
+          "tenant": "<tenant id>",
           "clusterResourceGroup": "<resource group name>",
           "version": "3.6",
           "osType": "Linux",
@@ -600,7 +600,7 @@ You create an Azure Synapse Analytics (Artifacts) linked service and use it with
         },
         "ConnectVia":{
           "referenceName": "integrationRuntime1",
-          "type": "IntergrationRuntimeReference"
+          "type": "IntegrationRuntimeReference"
         }
     }
 }

articles/data-factory/concepts-data-flow-flowlet.md

@@ -62,7 +62,7 @@ For a single transformation activity, you can right-click the mapping data flow
 
 ![Screenshot showing creating a flowlet from an existing activity using the right-click menu option.](./media/data-flow-flowlet/flowlet-context-create.png)
 
-If you have mulit-select turned on, you can also select multiple mapping data flow activities. This can be done by either lassoing multiple activities by drawing a rectangle to select them or using shift+select to select multiple activities. Then you'll right-click and select Create a new flowlet.
+If you have multi-select turned on, you can also select multiple mapping data flow activities. This can be done by either lassoing multiple activities by drawing a rectangle to select them or using shift+select to select multiple activities. Then you'll right-click and select Create a new flowlet.
 
 ![Screenshot showing multiple selection from existing activities.](./media/data-flow-flowlet/flowlet-context-multi.png)
 

articles/data-factory/concepts-workflow-orchestration-manager.md

@@ -16,7 +16,7 @@ ms.custom: references_regions
 
 > [!NOTE]
 > Apache Airflow is now accessible through Microsoft Fabric. Microsoft Fabric offers a wide range of Apache Airflow capabilities via Data Workflows. 
-> We recommend migrating your existing Workflow Orchestration Manager (Apache Airflow in ADF) based workflows to Data Workflows (Apache Airflow in Microsoft Fabric) for a broader set of features. Apache Airflow capabilities will be Genrally Available in Q1 CY2025 only in Microsoft Fabric. 
+> We recommend migrating your existing Workflow Orchestration Manager (Apache Airflow in ADF) based workflows to Data Workflows (Apache Airflow in Microsoft Fabric) for a broader set of features. Apache Airflow capabilities will be Generally Available in Q1 CY2025 only in Microsoft Fabric. 
 > For new Apache Airflow projects, we recommend using Apache Airflow in Microsoft Fabric. More details can be found [here](https://blog.fabric.microsoft.com/blog/introducing-data-workflows-in-microsoft-fabric?ft=All).
 > New users will not be allowed to create a new workflow orchestration manager in ADF, but existing users with a workflow orchestration manager may continue to use it but plan a migration soon.
 

articles/data-factory/connector-amazon-rds-for-oracle.md

@@ -276,7 +276,7 @@ The Amazon RDS for Oracle connector provides built-in data partitioning to copy
 
 When you enable partitioned copy, the service runs parallel queries against your Amazon RDS for Oracle source to load data by partitions. The parallel degree is controlled by the [`parallelCopies`](copy-activity-performance-features.md#parallel-copy) setting on the copy activity. For example, if you set `parallelCopies` to four, the service concurrently generates and runs four queries based on your specified partition option and settings, and each query retrieves a portion of data from your Amazon RDS for Oracle database.
 
-You are suggested to enable parallel copy with data partitioning especially when you load large amount of data from your Amazon RDS for Oracle database. The following are suggested configurations for different scenarios. When copying data into file-based data store, it's recommanded to write to a folder as multiple files (only specify folder name), in which case the performance is better than writing to a single file.
+You are suggested to enable parallel copy with data partitioning especially when you load large amount of data from your Amazon RDS for Oracle database. The following are suggested configurations for different scenarios. When copying data into file-based data store, it's recommended to write to a folder as multiple files (only specify folder name), in which case the performance is better than writing to a single file.
 
 | Scenario                                                     | Suggested settings                                           |
 | ------------------------------------------------------------ | ------------------------------------------------------------ |

articles/data-factory/connector-azure-databricks-delta-lake.md

@@ -431,7 +431,7 @@ If your source data store and format meet the criteria described in this section
             },
             "sink": {
                 "type": "AzureDatabricksDeltaLakeSink",
-                "sqlReadrQuery": "VACUUM eventsTable DRY RUN"
+                "sqlReaderQuery": "VACUUM eventsTable DRY RUN"
             }
         }
     }

articles/data-factory/connector-azure-search.md

@@ -71,7 +71,7 @@ The following properties are supported for Azure AI Search linked service:
 | connectVia | The [Integration Runtime](concepts-integration-runtime.md) to be used to connect to the data store. You can use Azure Integration Runtime or Self-hosted Integration Runtime (if your data store is located in private network). If not specified, it uses the default Azure Integration Runtime. |No |
 
 > [!IMPORTANT]
-> When copying data from a cloud data store into search index, in Azure AI Search linked service, you need to refer an Azure Integration Runtime with explicit region in connactVia. Set the region as the one where your search service resides. Learn more from [Azure Integration Runtime](concepts-integration-runtime.md#azure-integration-runtime).
+> When copying data from a cloud data store into search index, in Azure AI Search linked service, you need to refer an Azure Integration Runtime with explicit region in connectVia. Set the region as the one where your search service resides. Learn more from [Azure Integration Runtime](concepts-integration-runtime.md#azure-integration-runtime).
 
 **Example:**
 

articles/data-factory/connector-marketo.md

@@ -139,7 +139,7 @@ To copy data from Marketo, set the source type in the copy activity to **Marketo
 | Property | Description | Required |
 |:--- |:--- |:--- |
 | type | The type property of the copy activity source must be set to: **MarketoSource** | Yes |
-| query | Use the custom SQL query to read data. For example: `"SELECT * FROM Activitiy_Types"`. | No (if "tableName" in dataset is specified) |
+| query | Use the custom SQL query to read data. For example: `"SELECT * FROM Activity_Types"`. | No (if "tableName" in dataset is specified) |
 
 **Example:**
 
@@ -163,7 +163,7 @@ To copy data from Marketo, set the source type in the copy activity to **Marketo
         "typeProperties": {
             "source": {
                 "type": "MarketoSource",
-                "query": "SELECT top 1000 * FROM Activitiy_Types"
+                "query": "SELECT top 1000 * FROM Activity_Types"
             },
             "sink": {
                 "type": "<sink type>"

articles/data-factory/connector-netezza.md

@@ -230,7 +230,7 @@ The Data Factory Netezza connector provides built-in data partitioning to copy d
 
 When you enable partitioned copy, the service runs parallel queries against your Netezza source to load data by partitions. The parallel degree is controlled by the [`parallelCopies`](copy-activity-performance-features.md#parallel-copy) setting on the copy activity. For example, if you set `parallelCopies` to four, the service concurrently generates and runs four queries based on your specified partition option and settings, and each query retrieves a portion of data from your Netezza database.
 
-You are suggested to enable parallel copy with data partitioning especially when you load large amount of data from your Netezza database. The following are suggested configurations for different scenarios. When copying data into file-based data store, it's recommanded to write to a folder as multiple files (only specify folder name), in which case the performance is better than writing to a single file.
+You are suggested to enable parallel copy with data partitioning especially when you load large amount of data from your Netezza database. The following are suggested configurations for different scenarios. When copying data into file-based data store, it's recommended to write to a folder as multiple files (only specify folder name), in which case the performance is better than writing to a single file.
 
 | Scenario                                                     | Suggested settings                                           |
 | ------------------------------------------------------------ | ------------------------------------------------------------ |

articles/data-factory/connector-oracle.md

@@ -329,7 +329,7 @@ The Oracle connector provides built-in data partitioning to copy data from Oracl
 
 When you enable partitioned copy, the service runs parallel queries against your Oracle source to load data by partitions. The parallel degree is controlled by the [`parallelCopies`](copy-activity-performance-features.md#parallel-copy) setting on the copy activity. For example, if you set `parallelCopies` to four, the service concurrently generates and runs four queries based on your specified partition option and settings, and each query retrieves a portion of data from your Oracle database.
 
-You are suggested to enable parallel copy with data partitioning especially when you load large amount of data from your Oracle database. The following are suggested configurations for different scenarios. When copying data into file-based data store, it's recommanded to write to a folder as multiple files (only specify folder name), in which case the performance is better than writing to a single file.
+You are suggested to enable parallel copy with data partitioning especially when you load large amount of data from your Oracle database. The following are suggested configurations for different scenarios. When copying data into file-based data store, it's recommended to write to a folder as multiple files (only specify folder name), in which case the performance is better than writing to a single file.
 
 | Scenario                                                     | Suggested settings                                           |
 | ------------------------------------------------------------ | ------------------------------------------------------------ |

articles/data-factory/connector-postgresql.md

@@ -299,7 +299,7 @@ When copying data from PostgreSQL, the following mappings are used from PostgreS
 |`XML`|`String`|`String`|
 |`IntArray`|`String`|`String`|
 |`TextArray`|`String`|`String`|
-|`NumbericArray`|`String`|`String`|
+|`NumericArray`|`String`|`String`|
 |`DateArray`|`String`|`String`|
 |`Range`|`String`|`String`|
 |`Bpchar`|`String`|`String`|