clear merge conflict

Author: v-thepet

.openpublishing.redirection.json

@@ -42920,6 +42920,11 @@
       "redirect_url": "/sql/machine-learning/predictions/native-scoring-predict-transact-sql",
       "redirect_document_id": false
     },
+    {
+      "source_path": "docs/machine-learning/tutorials/data-science-scenarios-and-solution-templates.md",
+      "redirect_url": "/sql/machine-learning/tutorials/python-tutorials",
+      "redirect_document_id": false
+    },
     {
       "source_path": "docs/linux/sql-server-linux-develop-use-ssms.md",
       "redirect_url": "/sql/linux/sql-server-linux-manage-ssms",

data-migration/index.yml

@@ -49,7 +49,7 @@ conceptualContent:
         - text: Azure Synapse Analytics
           url: /azure/synapse-analytics/migration-guides/migrate-to-synapse-analytics-guide
           itemType: how-to-guide
-    - title: "DB2 to"
+    - title: "Db2 to"
       links:
         - text: SQL Server
           url: /sql/sql-server/migrate/guides/db2-to-sql-server

docs/big-data-cluster/big-data-cluster-faq.yml

@@ -30,7 +30,9 @@ Use [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)
 - Virtualize data with [PolyBase](../relational-databases/polybase/polybase-guide.md). Query data from external SQL Server, Oracle, Teradata, MongoDB, and ODBC data sources with external tables.
 - Provide high availability for the SQL Server master instance and all databases by using Always On availability group technology.
 
-For more information about new features and known issues for latest release, see the [release notes](release-notes-big-data-cluster.md).
+For more information about new features and known issues for latest release, see the [release notes](release-notes-big-data-cluster.md).   
+
+For more information Big Data Clusters, see [Big Data Clusters FAQ](big-data-cluster-faq.yml).
 
 ## Scenarios
 
@@ -114,4 +116,5 @@ The storage pool consists of storage pool pods comprised of SQL Server on Linux,
 
 ## Next steps
 
-For more information about deploying [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see [Get started with [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)]](deploy-get-started.md).
+* For more information about deploying [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see [Get started with [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)]](deploy-get-started.md).    
+* Review the [Big Data Clusters FAQ](big-data-cluster-faq.yml).  

docs/big-data-cluster/big-data-cluster-overview.md

@@ -183,5 +183,5 @@ For for specific open-source projects and versions, see [Open-source software re
 To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following resources:
 
 - [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
-- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
+- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)
 - [How to deploy [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] on Kubernetes](deployment-guidance.md#configfile)

docs/big-data-cluster/concept-architecture-pods.md

@@ -60,4 +60,4 @@ Scenarios where the compute pool is **not** used include:
 To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following resources:
 
 - [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
-- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
+- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)

docs/big-data-cluster/concept-compute-pool.md

@@ -38,4 +38,4 @@ Access to the SQL server instances in the data pool is managed from the SQL Serv
 To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following resources:
 
 - [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
-- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
+- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)

docs/big-data-cluster/concept-data-pool.md

@@ -15,7 +15,7 @@ ms.technology: big-data-cluster
 
 [!INCLUDE[SQL Server 2019](../includes/applies-to-version/sqlserver2019.md)]
 
-This article describes the role of the *SQL Server master instance* in a SQL Server big data cluster. The master instance is a SQL Server instance running in a SQL Server big data cluster to manage connectivity, scale-out queries, metadata and user databases, and machine learning services.
+This article describes the role of the *SQL Server master instance* in a SQL Server big data cluster. The master instance is a SQL Server instance running in a SQL Server big data cluster. The master instance manages connectivity, scale-out queries, metadata and user databases, and machine learning services.
 
 The SQL Server master instance provides the following functionality:
 
@@ -25,11 +25,11 @@ The SQL Server master instance provides an externally accessible TDS endpoint fo
 
 ## Scale-out query management
 
-The SQL Server master instance contains the scale-out query engine that is used to distribute queries across SQL Server instances on nodes in the [compute pool](concept-compute-pool.md). The scale-out query engine also provides access through Transact-SQL to all Hive tables in the cluster without any additional configuration.
+The SQL Server master instance contains the scale-out query engine that is used to distribute queries across SQL Server instances on nodes in the [compute pool](concept-compute-pool.md). The scale-out query engine also provides access through Transact-SQL to all Hive tables in the cluster without any more configuration.
 
 ## Metadata and user databases
 
-In addition to the standard SQL Server system databases, the SQL master instance also contains the following:
+In addition to the standard SQL Server system databases, the SQL master instance also contains:
 
 - A metadata database that holds HDFS-table metadata.
 - A data plane shard map.
@@ -40,13 +40,13 @@ You can also choose to add your own user databases to the SQL Server master inst
 
 ## Machine learning services
 
-SQL Server machine learning services is an add-on feature to the database engine, used for executing Java, R and Python code in SQL Server. This feature is based on the SQL Server extensibility framework, which isolates external processes from core engine processes, but fully integrates with the relational data as stored procedures, as T-SQL script containing R or Python statements, or as Java, R or Python code containing T-SQL.
+The SQL Server machine learning services feature is an add-on feature to the database engine. The machine learning services feature used for executing Java, R and Python code in SQL Server. This feature is based on the SQL Server extensibility framework, which isolates external processes from core engine processes, but fully integrates with the relational data as stored procedures, as T-SQL script containing R or Python statements, or as Java, R or Python code containing T-SQL.
 
-As part of a SQL Server big data cluster, machine learning services will be available on the SQL Server master instance by default. This means that once external script execution is enabled on the SQL Server master instance, it is going to be possible to execute Java, R and Python scripts using sp_execute_external_script.
+As part of a SQL Server big data cluster, machine learning services will be available on the SQL Server master instance by default. Once external script execution is enabled on the SQL Server master instance, it is possible to execute Java, R and Python scripts using sp_execute_external_script.
 
 ### Advantages of machine learning services in a big data cluster
 
-[!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] makes it easy for big data to be joined to the dimensional data typically stored in the enterprise database. The value of the big data greatly increases when it is not just in the hands of parts of an organization, but is also included in reports, dashboards, and applications. At the same time, data scientists can continue to use the Spark/HDFS ecosystem tools and have easy, real time access to the data in the SQL Server master instance and in external data sources accessible _through_ the SQL Server master instance.
+[!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] makes it easy for big data to be joined to the dimensional data typically stored in the enterprise database. The value of the big data greatly increases when it is not just in the hands of parts of an organization, but is also included in reports, dashboards, and applications. At the same time, data scientists can continue to use the Spark/HDFS ecosystem tools and have easy, real-time access to the data in the SQL Server master instance and in external data sources accessible _through_ the SQL Server master instance.
 
 With [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], you can do more with your enterprise data lakes. SQL Server developers and analysts can:
 
@@ -65,4 +65,4 @@ With [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md
 To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following resources:
 
 - [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
-- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
+- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)

docs/big-data-cluster/concept-master-instance.md

@@ -48,7 +48,7 @@ Currently, there is no option of opening up additional ports for accessing the c
 
 ## Authorization
 
-Throughout the cluster, integrated security between different components allows the original user’s identity to be passed through when issuing queries from Spark and SQL Server, all the way to HDFS. As mentioned above, the various external cluster endpoints support AD authentication.
+Throughout the cluster, integrated security between different components allows the original user's identity to be passed through when issuing queries from Spark and SQL Server, all the way to HDFS. As mentioned above, the various external cluster endpoints support AD authentication.
 
 There are two levels of authorization checks in the cluster for managing data access. Authorization in the context of big data is done in SQL Server, using the traditional SQL Server permissions on objects and in HDFS with control lists (ACLs), which associate user identities with specific permissions.
 
@@ -101,6 +101,8 @@ Cluster admin password:
 
 [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
 
-[Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
+[Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)
 
-[Kubernetes RBAC](kubernetes-rbac.md)
+[Kubernetes RBAC](kubernetes-rbac.md)  
+
+[Big Data Clusters FAQ](big-data-cluster-faq.yml)  

docs/big-data-cluster/concept-security.md

@@ -61,4 +61,4 @@ You can also interact with HDFS using:
 To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following resources:
 
 - [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
-- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
+- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)