Add additional gems

docs/Spark/gems/transform/bulk-column-expressions.md

@@ -1,6 +1,6 @@
 ---
 sidebar_position: 11
-title: Bulk Column Expressions
+title: BulkColumnExpressions
 id: bulk-column-expressions
 description: Change the data type of multiple columns at once.
 tags:
@@ -9,7 +9,7 @@ tags:
   - columns
 ---
 
-The Bulk Column Expressions Gem primarily lets you cast or change the data type of multiple columns at once. It provides additional functionality, including:
+The BulkColumnExpressions Gem primarily lets you cast or change the data type of multiple columns at once. It provides additional functionality, including:
 
 - Adding a prefix or suffix to selected columns.
 - Applying a custom expression to selected columns.
@@ -28,7 +28,7 @@ The Bulk Column Expressions Gem primarily lets you cast or change the data type
 
 Assume you have some columns in a table that represent zero-based indices and are stored as long data types. You want them to represent one-based indices and be stored as integers to optimize memory use.
 
-Using the Bulk Column Expressions Gem, you can:
+Using the BulkColumnExpressions Gem, you can:
 
 - Filter your columns by long data types.
 - Select the columns you wish to transform.

docs/Spark/gems/transform/bulk-column-rename.md

@@ -1,6 +1,6 @@
 ---
 sidebar_position: 10
-title: Bulk Column Rename
+title: BulkColumnRename
 id: bulk-column-rename
 description: Rename multiple columns in your Dataset in a systematic way.
 tags:
@@ -9,7 +9,7 @@ tags:
   - columns
 ---
 
-Use the Bulk Column Rename Gem to rename multiple columns in your Dataset in a systematic way.
+Use the BulkColumnRename Gem to rename multiple columns in your Dataset in a systematic way.
 
 ## Parameters
 

docs/Spark/gems/transform/data-cleansing.md

@@ -1,6 +1,6 @@
 ---
 sidebar_position: 12
-title: Data Cleansing
+title: DataCleansing
 id: data-cleansing
 description: Standardize data formats and address missing or null values in the data.
 tags:
@@ -9,7 +9,7 @@ tags:
   - format
 ---
 
-Use the Data Cleansing Gem to standardize data formats and address missing or null values in the data.
+Use the DataCleansing Gem to standardize data formats and address missing or null values in the data.
 
 ## Parameters
 
@@ -22,6 +22,6 @@ Use the Data Cleansing Gem to standardize data formats and address missing or nu
 
 ## Example
 
-Assume you have a table that includes customer feedback on individual orders. In this scenario, some customers may not provide feedback, resulting in null values in the data. You can use the Data Cleansing Gem to replace null values with the string `NA`.
+Assume you have a table that includes customer feedback on individual orders. In this scenario, some customers may not provide feedback, resulting in null values in the data. You can use the DataCleansing Gem to replace null values with the string `NA`.
 
 ![Replace null with string](./img/replace-null-with-string.png)

docs/Spark/gems/transform/dynamic-select.md

@@ -1,6 +1,6 @@
 ---
 sidebar_position: 13
-title: Dynamic Select
+title: DynamicSelect
 id: dynamic-select
 description: Dynamically filter columns of your dataset based on a set of conditions.
 tags:
@@ -9,11 +9,11 @@ tags:
   - dynamic
 ---
 
-Use the Dynamic Select Gem to dynamically filter columns of your Dataset based on a set of conditions.
+Use the DynamicSelect Gem to dynamically filter columns of your Dataset based on a set of conditions.
 
 ## Configuration
 
-There are two ways to configure the Dynamic Select.
+There are two ways to configure the DynamicSelect.
 
 | Configuration         | Description                                                                                   |
 | --------------------- | --------------------------------------------------------------------------------------------- |
@@ -22,7 +22,7 @@ There are two ways to configure the Dynamic Select.
 
 ## Examples
 
-You’ll use Dynamic Select when you want to avoid hard-coding your choice of columns. In other words, rather than define each column to keep in your Pipeline, you let the system automatically choose the columns based on certain conditions or rules.
+You’ll use DynamicSelect when you want to avoid hard-coding your choice of columns. In other words, rather than define each column to keep in your Pipeline, you let the system automatically choose the columns based on certain conditions or rules.
 
 ### Remove date columns using field type