update article 11-14

Author: XiaoyuMSFT

articles/sql-data-warehouse/sql-data-warehouse-develop-ctas.md

@@ -1,6 +1,6 @@
 ---
 title: CREATE TABLE AS SELECT (CTAS) 
-description: Explanation and examples of the CREATE TABLE AS SELECT (CTAS) statement in Azure SQL Data Warehouse for developing solutions.
+description: Explanation and examples of the CREATE TABLE AS SELECT (CTAS) statement in SQL Analytics for developing solutions.
 services: sql-data-warehouse
 author: XiaoyuMSFT
 manager: craigg
@@ -11,11 +11,12 @@ ms.date: 03/26/2019
 ms.author: xiaoyul
 ms.reviewer: igorstan
 ms.custom: seoapril2019
+ms.custom: azure-synapse
 ---
 
-# CREATE TABLE AS SELECT (CTAS) in Azure SQL Data Warehouse
+# CREATE TABLE AS SELECT (CTAS) in SQL Analytics
 
-This article explains the CREATE TABLE AS SELECT (CTAS) T-SQL statement in Azure SQL Data Warehouse for developing solutions. The article also provides code examples.
+This article explains the CREATE TABLE AS SELECT (CTAS) T-SQL statement in SQL Analytics for developing solutions. The article also provides code examples.
 
 ## CREATE TABLE AS SELECT
 
@@ -118,7 +119,7 @@ DROP TABLE FactInternetSales_old;
 
 ## Use CTAS to work around unsupported features
 
-You can also use CTAS to work around a number of the unsupported features listed below. This method can often prove helpful, because not only will your code be compliant, but it will often run faster on SQL Data Warehouse. This performance is a result of its fully parallelized design. Scenarios include:
+You can also use CTAS to work around a number of the unsupported features listed below. This method can often prove helpful, because not only will your code be compliant, but it will often run faster on SQL Analytics. This performance is a result of its fully parallelized design. Scenarios include:
 
 * ANSI JOINS on UPDATEs
 * ANSI JOINs on DELETEs
@@ -169,7 +170,7 @@ ON    [acs].[EnglishProductCategoryName]    = [fis].[EnglishProductCategoryName]
 AND    [acs].[CalendarYear]                = [fis].[CalendarYear];
 ```
 
-SQL Data Warehouse doesn't support ANSI joins in the `FROM` clause of an `UPDATE` statement, so you can't use the previous example without modifying it.
+SQL Analytics doesn't support ANSI joins in the `FROM` clause of an `UPDATE` statement, so you can't use the previous example without modifying it.
 
 You can use a combination of a CTAS and an implicit join to replace the previous example:
 
@@ -203,7 +204,7 @@ DROP TABLE CTAS_acs;
 
 ## ANSI join replacement for delete statements
 
-Sometimes the best approach for deleting data is to use CTAS, especially for `DELETE` statements that use ANSI join syntax. This is because SQL Data Warehouse doesn't support ANSI joins in the `FROM` clause of a `DELETE` statement. Rather than deleting the data, select the data you want to keep.
+Sometimes the best approach for deleting data is to use CTAS, especially for `DELETE` statements that use ANSI join syntax. This is because SQL Analytics doesn't support ANSI joins in the `FROM` clause of a `DELETE` statement. Rather than deleting the data, select the data you want to keep.
 
 The following is an example of a converted `DELETE` statement:
 
@@ -407,7 +408,7 @@ OPTION (LABEL = 'CTAS : Partition IN table : Create');
 
 You can see that type consistency and maintaining nullability properties on a CTAS is an engineering best practice. It helps to maintain integrity in your calculations, and also ensures that partition switching is possible.
 
-CTAS is one of the most important statements in SQL Data Warehouse. Make sure you thoroughly understand it. See the [CTAS documentation](/sql/t-sql/statements/create-table-as-select-azure-sql-data-warehouse).
+CTAS is one of the most important statements in SQL Analytics. Make sure you thoroughly understand it. See the [CTAS documentation](/sql/t-sql/statements/create-table-as-select-azure-sql-data-warehouse).
 
 ## Next steps
 

articles/sql-data-warehouse/sql-data-warehouse-reference-tsql-language-elements.md

@@ -1,6 +1,6 @@
 ---
 title: T-SQL language elements
-description: Links to the documentation for T-SQL statements supported in Azure SQL Data Warehouse.
+description: Links to the documentation for T-SQL statements supported in SQL Analytics.
 services: sql-data-warehouse
 author: XiaoyuMSFT
 manager: craigg
@@ -11,10 +11,11 @@ ms.date: 06/13/2018
 ms.author: xiaoyul
 ms.reviewer: igorstan
 ms.custom: seo-lt-2019
+ms.custom: azure-synapse
 ---
 
-# T-SQL language elements supported in Azure SQL Data Warehouse
-Links to the documentation for T-SQL language elements supported in Azure SQL Data Warehouse.
+# T-SQL language elements supported in SQL Analytics
+Links to the documentation for T-SQL language elements supported in SQL Analytics.
 
 ## Core elements
 * [syntax conventions](/sql/t-sql/language-elements/transact-sql-syntax-conventions-transact-sql)
@@ -273,5 +274,5 @@ Links to the documentation for T-SQL language elements supported in Azure SQL Da
 * [SET XACT_ABORT](https://msdn.microsoft.com/library/ms188792.aspx)
 
 ## Next steps
-For more reference information, see [T-SQL statements in Azure SQL Data Warehouse](sql-data-warehouse-reference-tsql-statements.md), and [System views in Azure SQL Data Warehouse](sql-data-warehouse-reference-tsql-system-views.md).
+For more reference information, see [T-SQL statements in SQL Analytics](sql-data-warehouse-reference-tsql-statements.md), and [System views in SQL Analytics](sql-data-warehouse-reference-tsql-system-views.md).
 

articles/sql-data-warehouse/sql-data-warehouse-reference-tsql-statements.md

@@ -1,6 +1,6 @@
 ---
 title: T-SQL statements
-description: Links to the documentation for T-SQL statements supported in Azure SQL Data Warehouse.
+description: Links to the documentation for T-SQL statements supported in SQL Analytics.
 services: sql-data-warehouse
 author: XiaoyuMSFT
 manager: craigg
@@ -11,10 +11,11 @@ ms.date: 05/01/2019
 ms.author: xiaoyul
 ms.reviewer: igorstan
 ms.custom: seo-lt-2019
+ms.custom: azure-synapse
 ---
 
-# T-SQL statements supported in Azure SQL Data Warehouse
-Links to the documentation for T-SQL statements supported in Azure SQL Data Warehouse.
+# T-SQL statements supported in SQL Analytics
+Links to the documentation for T-SQL statements supported in SQL Analytics.
 
 ## Data Definition Language (DDL) statements
 * [ALTER DATABASE](https://msdn.microsoft.com/library/mt204042.aspx)
@@ -115,4 +116,4 @@ Links to the documentation for T-SQL statements supported in Azure SQL Data Ware
 * [OPEN MASTER KEY](https://msdn.microsoft.com/library/ms174433.aspx)
 
 ## Next steps
-For more reference information, see [T-SQL language elements in Azure SQL Data Warehouse](sql-data-warehouse-reference-tsql-language-elements.md), and [System views in Azure SQL Data Warehouse](sql-data-warehouse-reference-tsql-system-views.md).
+For more reference information, see [T-SQL language elements in SQL Analytics](sql-data-warehouse-reference-tsql-language-elements.md), and [System views in SQL Analytics](sql-dat-warehouse-reference-tsql-system-views.md).

articles/sql-data-warehouse/sql-data-warehouse-reference-tsql-system-views.md

@@ -1,6 +1,6 @@
 ---
 title: System views
-description: Links to the documentation for system views supported in Azure SQL Data Warehouse.
+description: Links to the documentation for system views supported in SQL Analytics.
 services: sql-data-warehouse
 author: XiaoyuMSFT 
 manager: craigg
@@ -11,12 +11,13 @@ ms.date: 01/06/2020
 ms.author: xiaoyul
 ms.reviewer: igorstan
 ms.custom: seo-lt-2019
+ms.custom: azure-synapse
 ---
 
-# System views supported in Azure SQL Data Warehouse
-Links to the documentation for T-SQL statements supported in Azure SQL Data Warehouse.
+# System views supported in SQL Analytics
+Links to the documentation for T-SQL statements supported in SQL Analytics.
 
-## SQL Data Warehouse catalog views
+## SQL Analytics catalog views
 * [sys.pdw_column_distribution_properties](https://msdn.microsoft.com/library/mt204022.aspx)
 * [sys.pdw_distributions](https://msdn.microsoft.com/library/mt203892.aspx)
 * [sys.pdw_index_mappings](https://msdn.microsoft.com/library/mt203912.aspx)
@@ -60,8 +61,8 @@ Links to the documentation for T-SQL statements supported in Azure SQL Data Ware
 * [sys.dm_pdw_waits](/sql/relational-databases/system-dynamic-management-views/sys-dm-pdw-waits-transact-sql)
 * [sys.dm_workload_management_workload_groups_stats](https://docs.microsoft.com/sql/relational-databases/system-dynamic-management-views/sys-dm-workload-management-workload-group-stats-transact-sql) (Preview)
 
-## SQL Server DMVs applicable to SQL Data Warehouse
-The following DMVs are applicable to SQL Data Warehouse, but must be executed by connecting to the **master** database.
+## SQL Server DMVs applicable to SQL Analytics
+The following DMVs are applicable to SQL Analytics, but must be executed by connecting to the **master** database.
 
 * [sys.database_service_objectives](https://msdn.microsoft.com/library/mt712619.aspx)
 * [sys.dm_operation_status](https://msdn.microsoft.com/library/dn270022.aspx)
@@ -140,17 +141,17 @@ The following DMVs are applicable to SQL Data Warehouse, but must be executed by
 * [sys.types](https://msdn.microsoft.com/library/ms188021.aspx)
 * [sys.views](https://msdn.microsoft.com/library/ms190334.aspx)
 
-## SQL Server DMVs available in SQL Data Warehouse
-SQL Data Warehouse exposes many of the SQL Server dynamic management views (DMVs). These views, when queried in SQL Data Warehouse, are reporting the state of SQL Databases running on the distributions.
+## SQL Server DMVs available in SQL Analytics
+SQL Analytics exposes many of the SQL Server dynamic management views (DMVs). These views, when queried in SQL Analytics, are reporting the state of SQL Databases running on the distributions.
 
-SQL Data Warehouse and Analytics Platform System's Parallel Data Warehouse (PDW) use the same system views. Each DMV has a column called pdw_node_id, which is the identifier for the Compute node. 
+SQL Analytics and Parallel Data Warehouse (PDW) use the same system views. Each DMV has a column called pdw_node_id, which is the identifier for the Compute node. 
 
 > [!NOTE]
 > To use these views, insert ‘pdw_nodes_’ into the name, as shown in the following table:
 > 
 > 
 
-| DMV name in SQL Data Warehouse | SQL Server Transact-SQL article|
+| DMV name in SQL Analytics | SQL Server Transact-SQL article|
 |:--- |:--- |
 | sys.dm_pdw_nodes_db_column_store_row_group_physical_stats | [sys.dm_db_column_store_row_group_physical_stats](/sql/relational-databases/system-dynamic-management-views/sys-dm-db-column-store-row-group-physical-stats-transact-sql)| 
 | sys.dm_pdw_nodes_db_column_store_row_group_operational_stats | [sys.dm_db_column_store_row_group_operational_stats](/sql/relational-databases/system-dynamic-management-views/sys-dm-db-column-store-row-group-operational-stats-transact-sql)| 
@@ -212,8 +213,8 @@ SQL Data Warehouse and Analytics Platform System's Parallel Data Warehouse (PDW)
 | sys.dm_pdw_nodes_tran_session_transactions |[sys.dm_tran_session_transactions](https://msdn.microsoft.com/library/ms188739.aspx) |
 | sys.dm_pdw_nodes_tran_top_version_generators |[sys.dm_tran_top_version_generators](https://msdn.microsoft.com/library/ms188778.aspx) |
 
-## SQL Server 2016 PolyBase DMVs available in SQL Data Warehouse
-The following DMVs are applicable to SQL Data Warehouse, but must be executed by connecting to the **master** database.
+## SQL Server 2016 PolyBase DMVs available in SQL Analytics
+The following DMVs are applicable to SQL Analytics, but must be executed by connecting to the **master** database.
 
 * [sys.dm_exec_compute_node_errors](https://msdn.microsoft.com/library/mt146380.aspx)
 * [sys.dm_exec_compute_node_status](https://msdn.microsoft.com/library/mt146382.aspx)
@@ -238,4 +239,4 @@ The following DMVs are applicable to SQL Data Warehouse, but must be executed by
 * [VIEWS](https://msdn.microsoft.com/library/ms181381.aspx)
 
 ## Next steps
-For more reference information, see [T-SQL statements in Azure SQL Data Warehouse](sql-data-warehouse-reference-tsql-statements.md), and [T-SQL language elements in Azure SQL Data Warehouse](sql-data-warehouse-reference-tsql-language-elements.md).
+For more reference information, see [T-SQL statements in SQL Analytics](sql-data-warehouse-reference-tsql-statements.md), and [T-SQL language elements in SQL Analytics](sql-data-warehouse-reference-tsql-language-elements.md).