Update data-flow-cast.md

Author: kromerm

articles/data-factory/data-flow-cast.md

@@ -1,6 +1,6 @@
 ---
-title: Rank transformation in mapping data flow 
-description: Learn how to use a mapping data flow rank transformation to generate a ranking column in Azure Data Factory or Synapse Analytics pipelines.
+title: Cast transformation in mapping data flow 
+description: Learn how to use a mapping data flow cast transformation to easily change column data types in Azure Data Factory or Synapse Analytics pipelines.
 titleSuffix: Azure Data Factory & Azure Synapse
 author: kromerm
 ms.author: makromer
@@ -9,30 +9,28 @@ ms.service: data-factory
 ms.subservice: data-flows
 ms.topic: conceptual
 ms.custom: synapse
-ms.date: 09/09/2021
+ms.date: 07/13/2022
 ---
 
-# Rank transformation in mapping data flow 
+# Cast transformation in mapping data flow 
 
 [!INCLUDE[appliesto-adf-asa-md](includes/appliesto-adf-asa-md.md)]
 
 [!INCLUDE[data-flow-preamble](includes/data-flow-preamble.md)]
 
-Use the rank transformation to generate an ordered ranking based upon sort conditions specified by the user. 
-
-> [!VIDEO https://www.microsoft.com/en-us/videoplayer/embed/RE4GGJo]
+Use the cast transformation to easily modify the data types of individual columns in a data flow.
 
 ## Configuration
 
-:::image type="content" source="media/data-flow/rank-configuration.png" alt-text="Rank settings":::
+:::image type="content" source="media/data-flow/cast-transformation-001.png" alt-text="Rank settings":::
 
-**Case insensitive:** If a sort column is of type string, case will be factored into the ranking. 
+**Column name:** If a sort column is of type string, case will be factored into the ranking. 
 
-**Dense:** If enabled, the rank column will be dense ranked. Each rank count will be a consecutive number and rank values won't be skipped after a tie.
+**Type:** If enabled, the rank column will be dense ranked. Each rank count will be a consecutive number and rank values won't be skipped after a tie.
 
-**Rank column:** The name of the rank column generated. This column will be of type long.
+**Format:** The name of the rank column generated. This column will be of type long.
 
-**Sort conditions:** Choose which columns you're sorting by and in which order the sort happens. The order determines sorting priority.
+**Assert type check:** Choose which columns you're sorting by and in which order the sort happens. The order determines sorting priority.
 
 The above configuration takes incoming basketball data and creates a rank column called 'pointsRanking'. The row with the highest value of the column *PTS* will have a *pointsRanking* value of 1.
 
@@ -42,32 +40,14 @@ The above configuration takes incoming basketball data and creates a rank column
 
 ```
 <incomingStream>
-    rank(
-        desc(<sortColumn1>),
-        asc(<sortColumn2>),
-        ...,
-        caseInsensitive: { true | false }
-        dense: { true | false }
-        output(<rankColumn> as long)
-    ) ~> <sortTransformationName<>
-```
-
-### Example
-
-:::image type="content" source="media/data-flow/rank-configuration.png" alt-text="Rank settings":::
-
-The data flow script for the above rank configuration is in the following code snippet.
-
+    cast(output(
+		AddressID as integer,
+		AddressLine1 as string,
+		AddressLine2 as string,
+		City as string
+	),
+	errors: true) ~> <castTransformationName<>
 ```
-PruneColumns
-    rank(
-        desc(PTS, true),
-        caseInsensitive: false,
-        output(pointsRanking as long),
-        dense: false
-    ) ~> RankByPoints
-```
-
 ## Next steps
 
-Filter rows based upon the rank values using the [filter transformation](data-flow-filter.md).
+Modify existing columns and new columns using the [derived column transformation](data-flow-derived-column.md).