Merging changes synced from https://github.com/MicrosoftDocs/sql-docs-pr (branch live)

Author: fenxu

.openpublishing.redirection.json

@@ -10,6 +10,16 @@
             "redirect_url": "/sql/relational-databases/polybase/polybase-guide",
             "redirect_document_id": false 
         },
+        {
+            "source_path": "docs/advanced-analytics/tutorials/walkthrough-prepare-the-data.md",
+            "redirect_url": "/sql/advanced-analytics/tutorials/demo-data-nyctaxi-in-sql",
+            "redirect_document_id": false
+        }, 
+        {
+            "source_path": "docs/advanced-analytics/tutorials/walkthrough-view-and-explore-the-data.md",
+            "redirect_url": "/sql/advanced-analytics/tutorials/demo-data-nyctaxi-in-sql",
+            "redirect_document_id": false
+        }, 
         {
             "source_path": "docs/advanced-analytics/r/sqldev-train-and-save-a-model-using-t-sql.md",
             "redirect_url": "/sql/advanced-analytics/tutorials/sqldev-train-and-save-a-model-using-t-sql",

docs/advanced-analytics/python/setup-python-client-tools-sql.md

@@ -15,13 +15,13 @@ manager: cgronlun
 
 Python integration is available starting in SQL Server 2017 or later when you include the Python option in a [Machine Learning Services (In-Database) installation](../install/sql-machine-learning-services-windows-install.md). 
 
-To create and deploy Python solutions on SQL Server, install Microsoft's [revoscalepy](https://docs.microsoft.com/machine-learning-server/python-reference/revoscalepy/revoscalepy-package) and other Python libraries on the client workstation. The revoscalepy library, which is also on the remote SQL Server instance, coordinates computing requests between both systems. 
+To develop and deploy Python solutions for SQL Server, install Microsoft's [revoscalepy](https://docs.microsoft.com/machine-learning-server/python-reference/revoscalepy/revoscalepy-package) and other Python libraries your development workstation. The revoscalepy library, which is also on the remote SQL Server instance, coordinates computing requests between both systems. 
 
-In this article, learn how to configure a Python development workstation so that you can connect to a remote SQL Server enabled for machine learning and Python integration. After completing the steps in this article, you will have the same Python libraries as those on SQL Server. You will also know how to push computations from a local Python session to a remote Python session on SQL Server.
+In this article, learn how to configure a Python development workstation so that you can interact with a remote SQL Server enabled for machine learning and Python integration. After completing the steps in this article, you will have the same Python libraries as those on SQL Server. You will also know how to push computations from a local Python session to a remote Python session on SQL Server.
 
 ![Client-server components](media/sqlmls-python-client-revo.png "Local and remote Python sessions and libraries")
 
-You can use built-in Jupyter Notebooks as described in this article, or [link the libraries](#install-ide) to PyCharm or any another IDE that you normally use.
+To validate the installation, you can use built-in Jupyter Notebooks as described in this article, or [link the libraries](#install-ide) to PyCharm or any another IDE that you normally use.
 
 > [!Tip]
 > For a video demonstration of these exercises, see [Run R and Python remotely in SQL Server from Jupyter Notebooks](https://blogs.msdn.microsoft.com/mlserver/2018/07/10/run-r-and-python-remotely-in-sql-server-from-jupyter-notebooks-or-any-ide/).

docs/advanced-analytics/r/set-up-a-data-science-client.md

@@ -15,13 +15,13 @@ manager: cgronlun
 
 R integration is available in SQL Server 2016 or later when you include the R language option in an [SQL Server 2016 R Services](../install/sql-r-services-windows-install.md) or [SQL Server 2017 Machine Learning Services (In-Database)](../install/sql-machine-learning-services-windows-install.md) installation. 
 
-To create and deploy R solutions on SQL Server, install [Microsoft R Client](https://docs.microsoft.com/machine-learning-server/r-client/what-is-microsoft-r-client) to get [RevoScaleR](https://docs.microsoft.com/machine-learning-server/r-reference/revoscaler/revoscaler) and other R libraries on your development workstation. The RevoScaleR library, which is also on the remote SQL Server instance, coordinates computing requests between both systems. 
+To develop and deploy R solutions for SQL Server, install [Microsoft R Client](https://docs.microsoft.com/machine-learning-server/r-client/what-is-microsoft-r-client) on your development workstation to get [RevoScaleR](https://docs.microsoft.com/machine-learning-server/r-reference/revoscaler/revoscaler) and other R libraries. The RevoScaleR library, which is also required on the remote SQL Server instance, coordinates computing requests between both systems. 
 
-In this article, learn how to configure an R client development workstation so that you can connect to a remote SQL Server enabled for machine learning and R integration. After completing the steps in this article, you will have the same R libraries as those on SQL Server. You will also know how to push computations from a local R session to a remote R session on SQL Server.
+In this article, learn how to configure an R client development workstation so that you can interact with a remote SQL Server enabled for machine learning and R integration. After completing the steps in this article, you will have the same R libraries as those on SQL Server. You will also know how to push computations from a local R session to a remote R session on SQL Server.
 
 ![Client-server components](media/sqlmls-r-client-revo.png "Local and remote R sessions and libraries")
 
-You can use built-in **RGUI** tool as described in this article, or [link the libraries](#install-ide) to RStudio or any another IDE that you normally use.
+To validate the installation, you can use built-in **RGUI** tool as described in this article, or [link the libraries](#install-ide) to RStudio or any another IDE that you normally use.
 
 > [!Tip]
 > For a video demonstration of these exercises, see [Run R and Python remotely in SQL Server from Jupyter Notebooks](https://blogs.msdn.microsoft.com/mlserver/2018/07/10/run-r-and-python-remotely-in-sql-server-from-jupyter-notebooks-or-any-ide/).

docs/advanced-analytics/toc.yml

@@ -70,7 +70,7 @@
 - name: Tutorials
   href: tutorials/machine-learning-services-tutorials.md
   items:
-  - name: Data
+  - name: Sample data
     items:
     - name: Airline data set
       href: tutorials/demo-data-airlinedemo-in-sql.md
@@ -82,20 +82,20 @@
     href: tutorials/sql-server-python-tutorials.md
     items:
     - name: Train and use your first model
-      href: tutorials/train-score-using-python-in-tsql.md    
+      href: tutorials/train-score-using-python-in-tsql.md 
+    - name: Create a Python model using revoscalepy
+      href: tutorials/use-python-revoscalepy-to-create-model.md  
     - name: Learn in-database analytics
       href: tutorials/sqldev-in-database-python-for-sql-developers.md
       items:
-      - name: 1 - Visualize data
+      - name: 1 - Data exploration
         href: tutorials/sqldev-py3-explore-and-visualize-the-data.md
-      - name: 2 - Create data features
+      - name: 2 - Feature engineering
         href: tutorials/sqldev-py4-create-data-features-using-t-sql.md
-      - name: 3 - Train and save to SQL
+      - name: 3 - Train and deploy
         href: tutorials/sqldev-py5-train-and-save-a-model-using-t-sql.md
-      - name: 4 - Predict outcomes
+      - name: 4 - Predictions
         href: tutorials/sqldev-py6-operationalize-the-model.md
-    - name: Create a model using revoscalepy
-      href: tutorials/use-python-revoscalepy-to-create-model.md
   - name: R
     href: tutorials/sql-server-r-tutorials.md
     items:
@@ -104,22 +104,18 @@
     - name: Learn in-database analytics
       href: tutorials/sqldev-in-database-r-for-sql-developers.md
       items:
-      - name: 1 - Visualize data
+      - name: 1 - Data exploration
         href: tutorials/sqldev-explore-and-visualize-the-data.md
-      - name: 2 - Create data features
+      - name: 2 - Feature engineering
         href: tutorials/sqldev-create-data-features-using-t-sql.md
-      - name: 3 - Train and save to SQL
+      - name: 3 - Train and deploy
         href: tutorials/sqldev-train-and-save-a-model-using-t-sql.md
-      - name: 4 - Predict outcomes
+      - name: 4 - Predictions
         href: tutorials/sqldev-operationalize-the-model.md
-    - name: Data science end-to-end walkthrough
+    - name: Data science walkthrough
       href: tutorials/walkthrough-data-science-end-to-end-walkthrough.md
       items:
-      - name: Prepare data
-        href: tutorials/walkthrough-prepare-the-data.md
-      - name: Explore data using SQL
-        href: tutorials/walkthrough-view-and-explore-the-data.md
-      - name: Summarize data using R
+      - name: Explore and summarize data
         href: tutorials/walkthrough-view-and-summarize-data-using-r.md
       - name: Create graphs and plots
         href: tutorials/walkthrough-create-graphs-and-plots-using-r.md
@@ -129,7 +125,7 @@
         href: tutorials/walkthrough-build-and-save-the-model.md
       - name: Deploy and use the model
         href: tutorials/walkthrough-deploy-and-use-the-model.md
-    - name: Deep dive with RevoScaleR
+    - name: RevoScaleR deep dive
       href: tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md
       items:
       - name: Create database and permissions

docs/advanced-analytics/tutorials/deepdive-data-science-deep-dive-using-the-revoscaler-packages.md

@@ -4,7 +4,7 @@ description: In this tutorial, learn how to call RevoScaleR function in SQL Serv
 ms.prod: sql
 ms.technology: machine-learning
 
-ms.date: 07/15/2018  
+ms.date: 11/27/2018  
 ms.topic: tutorial
 author: HeidiSteen
 ms.author: heidist
@@ -13,7 +13,7 @@ manager: cgronlun
 # Tutorial: Use RevoScaleR R functions with SQL Server data
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md-winonly](../../includes/appliesto-ss-xxxx-xxxx-xxx-md-winonly.md)]
 
-RevoScaleR is a Microsoft R package providing distributed and parallel processing for data science and machine learning workloads. For R development in SQL Server, RevoScaleR is one of the core built-in packages, with functions for setting a compute context, managing packages, and most importantly: working with data end-to-end, from import to visualization and analysis. Machine Learning algorithms in SQL Server have a dependency on RevoScaleR data sources. Given the importance of RevoScaleR, knowing when and how to call its functions is an essential skill. 
+RevoScaleR is a Microsoft R package providing distributed and parallel processing for data science and machine learning workloads. For R development in SQL Server, RevoScaleR is one of the core built-in packages, with functions for creating data source objects, setting a compute context, managing packages, and most importantly: working with data end-to-end, from import to visualization and analysis. Machine Learning algorithms in SQL Server have a dependency on RevoScaleR data sources. Given the importance of RevoScaleR, knowing when and how to call its functions is an essential skill. 
 
 In this tutorial, you will learn how to create a remote compute context, move data between local and remote compute contexts, and execute R code on a remote SQL Server. You also learn how to analyze and plot data both locally and on the remote server, and how to create and deploy models.
 
@@ -41,29 +41,34 @@ You should also be comfortable with [!INCLUDE[tsql](../../includes/tsql-md.md)]
 
 ## Prerequisites
 
-- **SQL Server with support for R**
++ [SQL Server 2017 Machine Learning Services](../install/sql-machine-learning-services-windows-install.md) with the R feature, or [SQL Server 2016 R Services (in-Database)](../install/sql-r-services-windows-install.md)
 
-    Install [SQL Server 2017 Machine Learning Services](../install/sql-machine-learning-services-windows-install.md) with the R feature, or install [SQL Server 2016 R Services (in-Database)](../install/sql-r-services-windows-install.md).
++ [Database permissions](../security/user-permission.md) and a SQL Server database user login
 
-    Make sure external scripting is enabled, Launchpad service is running, and that you have permissions to access the service.
-  
--  **Database permissions**
-  
-    To run the queries used to train the model, you must have **db_datareader** privileges on the database where the data is stored. To run R, your user must have the permission, EXECUTE ANY EXTERNAL SCRIPT.
++ [SQL Server Management Studio](https://docs.microsoft.com/sql/ssms/download-sql-server-management-studio-ssms)
 
--   **Data science development computer**
-  
-    To switch back and forth between local and remote compute contexts, you need two systems. Local is typically a development workstation with sufficent power for data science workloads. Remote in this case is SQL Server 2017 or SQL Server 2016 with the R feature enabled. 
-    
-    Switching compute contexts is predicated on having the same-version RevoScaleR on both local and remote systems. On a local workstation, you can get the RevoScaleR packages and related providers by installing or using any one of the following: [Data Science VM on Azure](https://docs.microsoft.com/azure/machine-learning/data-science-virtual-machine/overview), [Microsoft R Client (free)](https://docs.microsoft.com/machine-learning-server/r-client/what-is-microsoft-r-client), or [Microsoft Machine Learning Server (Standalone)](https://docs.microsoft.com/machine-learning-server/install/machine-learning-server-install). For the standalone server option, install the free developer edition, using either Linux or Windows installers. You can also use SQL Server Setup to install a standalone server.
-      
--   **Additional R Packages**
++ An IDE such as RStudio or the built-in RGUI tool included with R
+
+To switch back and forth between local and remote compute contexts, you need two systems. Local is typically a development workstation with sufficent power for data science workloads. Remote in this case is SQL Server 2017 or SQL Server 2016 with the R feature enabled. 
+
+Switching compute contexts is predicated on having the same-version RevoScaleR on both local and remote systems. On a local workstation, you can get the RevoScaleR packages and related providers by installing Microsoft R Client.
+
+If you need to put client and server on the same computer, be sure to install a second set of Microsoft R libraries for sending R script from a "remote" client. Do not use the R libraries that are installed in the program files of the SQL Server instance. Specifically, if you are using one computer, you need the RevoScaleR library in both of these locations to support client and server operations.
+
++ C:\Program Files\Microsoft\R Client\R_SERVER\library\RevoScaleR 
++ C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\R_SERVICES\library\RevoScaleR
+
+For instructions on client configuration, see [Set up a data science client for R development](../r/set-up-a-data-science-client.md).
+
+<a name="add-packages"></a>
+
+## Additional R packages
 
-    In this tutorial, you install the following packages: **dplyr**, **ggplot2**, **ggthemes**, **reshape2**, and **e1071**. Instructions are provided as part of the tutorial.
+In this tutorial, you install the following packages: **dplyr**, **ggplot2**, **ggthemes**, **reshape2**, and **e1071**. Instructions are provided as part of the tutorial.
 
-    All packages must be installed in two places: on the workstation used for R solution development, and on the SQL Server computer where R scripts are executed. If you do not have permission to install packages on the server computer, ask an administrator. 
-    
-    **Do not install the packages to a user library.** The packages must be installed in the R package library that is used by the SQL Server instance.
+All packages must be installed in two places: on the workstation used for R solution development, and on the SQL Server computer where R scripts are executed. If you do not have permission to install packages on the server computer, ask an administrator. 
+
+**Do not install the packages to a user library.** The packages must be installed in the R package library that is used by the SQL Server instance.
 
 ## R development tools
 

docs/advanced-analytics/tutorials/deepdive-work-with-sql-server-data-using-r.md

@@ -1,9 +1,9 @@
 ---
-title: Work with SQL Server data using R  (SQL and R deep dive)| Microsoft Docs
+title: Create a database and permissions (SQL and RevoScaleR deep dive)| Microsoft Docs
 ms.prod: sql
 ms.technology: machine-learning
 
-ms.date: 04/15/2018  
+ms.date: 11/27/2018  
 ms.topic: tutorial
 author: HeidiSteen
 ms.author: heidist