Fix typo in Teradata connector documentation

Author: ttorble

articles/data-factory/connector-teradata.md

@@ -355,7 +355,7 @@ You are suggested to enable parallel copy with data partitioning especially when
 | ------------------------------------------------------------ | ------------------------------------------------------------ |
 | Full load from large table.                                   | **Partition option**: Hash. <br><br/>During execution, the service automatically detects the primary index column, applies a hash against it, and copies data by partitions. |
 | Load large amount of data by using a custom query.                 | **Partition option**: Hash.<br>**Query**: `SELECT * FROM <TABLENAME> WHERE ?AdfHashPartitionCondition AND <your_additional_where_clause>`.<br>**Partition column**: Specify the column used for apply hash partition. If not specified, the service automatically detects the PK column of the table you specified in the Teradata dataset.<br><br>During execution, the service replaces `?AdfHashPartitionCondition` with the hash partition logic, and sends to Teradata. |
-| Load large amount of data by using a custom query, having an integer column with evenly distributed value for range partitioning. | **Partition options**: Dynamic range partition.<br>**Query**: `SELECT * FROM <TABLENAME> WHERE ?AdfRangePartitionColumnName <= ?AdfRangePartitionUpbound AND ?AdfRangePartitionColumnName >= ?AdfRangePartitionLowbound AND <your_additional_where_clause>`.<br>**Partition column**: Specify the column used to partition data. You can partition against the column with integer data type.<br>**Partition upper bound** and **partition lower bound**: Specify if you want to filter against the partition column to retrieve data only between the lower and upper range.<br><br>During execution, the service replaces `?AdfRangePartitionColumnName`, `?AdfRangePartitionUpbound`, and `?AdfRangePartitionLowbound` with the actual column name and value ranges for each partition, and sends to Teradata. <br>For example, if your partition column "ID" set with the lower bound as 1 and the upper bound as 80, with parallel copy set as 4, the service retrieves data by 4 partitions. Their IDs are between [1,20], [21, 40], [41, 60], and [61, 80], respectively. |
+| Load large amount of data by using a custom query, having an integer column with evenly distributed value for range partitioning. | **Partition options**: Dynamic range partition.<br>**Query**: `SELECT * FROM <TABLENAME> WHERE ?AdfRangePartitionColumnName <= ?AdfRangePartitionUpbound AND ?AdfRangePartitionColumnName >= ?AdfRangePartitionLowbound AND <your_additional_where_clause>`.<br>**Partition column**: Specify the column used to partition data. You can partition against the column with integer data type.<br>**Partition upper bound** and **partition lower bound**: Specify if you want to filter against the partition column to retrieve data only between the lower and upper range.<br><br>During execution, the service replaces `?AdfRangePartitionColumnName`, `?AdfRangePartitionUpbound`, and `?AdfRangePartitionLowbound` with the actual column name and value ranges for each partition, and sends to Teradata. <br>For example, if your partition column "ID" is set with the lower bound as 1 and the upper bound as 80, with parallel copy set as 4, the service retrieves data by 4 partitions. Their IDs are between [1,20], [21, 40], [41, 60], and [61, 80], respectively. |
 
 **Example: query with hash partition**