Update release-notes-10-0-10106-0.md

Author: anumjs

articles/sql-data-warehouse/release-notes-10-0-10106-0.md

@@ -32,7 +32,7 @@ Use the version identified to confirm which release has been applied to your Azu
 | Service improvements | Details |
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 |**Copy (Preview)**|We are excited to announce the public preview of a simple and flexible COPY statement for data ingestion. With only one statement, you can now seamlessly ingest data with additional flexibility and without requiring high privileged users. For more information, see [COPY command documentation](/sql/t-sql/statements/copy-into-transact-sql?view=azure-sqldw-latest).|
-|**Workload Isolation (Preview)**|To support customers as they democratize their data warehouses, we are announcing new features for intelligent workload management. The new [Workload Isolation](/azure/sql-data-warehouse/sql-data-warehouse-workload-isolation) functionality allows you to manage the execution of heterogeneous workloads while providing flexibility and control over data warehouse resources. This leads to improved execution predictability and enhances the ability to satisfy predefined SLAs. </br>In addition to workload isolation, additional options are now available for [Workload Classification](azure/sql-data-warehouse/sql-data-warehouse-workload-classification).  Beyond login classification, the [Create Workload Classifier](/sql/t-sql/statements/create-workload-classifier-transact-sql?view=azure-sqldw-latest) syntax provides the capability to classify requests based on query label, session context and time of day.|
+|**Workload Isolation (Preview)**|To support customers as they democratize their data warehouses, we are announcing new features for intelligent workload management. The new [Workload Isolation](/azure/sql-data-warehouse/sql-data-warehouse-workload-isolation) functionality allows you to manage the execution of heterogeneous workloads while providing flexibility and control over data warehouse resources. This leads to improved execution predictability and enhances the ability to satisfy predefined SLAs. </br>In addition to workload isolation, additional options are now available for [Workload Classification](/azure/sql-data-warehouse/sql-data-warehouse-workload-classification).  Beyond login classification, the [Create Workload Classifier](/sql/t-sql/statements/create-workload-classifier-transact-sql?view=azure-sqldw-latest) syntax provides the capability to classify requests based on query label, session context and time of day.|
 |**PREDICT (Preview)**|You can now score machine learning models within your data warehouse avoiding the need for large and complex data movement. The T-SQL PREDICT function relies on open model framework and takes data and machine learning model as input to generate predictions.
 |**SSDT CI/CD (GA)**|Today we are excited to announce the General Availability of the [highest requested feature](https://feedback.azure.com/forums/307516-sql-data-warehouse/suggestions/13313247--in-preview-database-project-from-visual-studio-t) for SQL Data Warehouse – SQL Server Data Tools (SSDT) Database projects. This release includes support for SSDT with Visual Studio 2019 along with native platform integration with Azure DevOps providing built-in continuous integration and deployment (CI/CD) capabilities for enterprise level deployments. |
 |**Materialized View (GA)**|A Materialized View persists the data returned from the view definition query and automatically gets updated as data changes in the underlying tables. It improves the performance of complex queries (typically queries with joins and aggregations) while offering simple maintenance operations. For more information, see [Performance tuning with materialized views](/azure/sql-data-warehouse/performance-tuning-materialized-views).  Install [SQL Server Management Studio 18.4 or later](https://docs.microsoft.com/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-ver15) for scripting Materialized Views.|