Merge pull request #7810 from MicrosoftDocs/master

10/23 AM Publish

Author: huypub

.openpublishing.redirection.json

@@ -30,6 +30,11 @@
             "redirect_url": "/sql/advanced-analytics/tutorials/demo-data-nyctaxi-in-sql",
             "redirect_document_id": false
         }, 
+        {
+            "source_path": "docs/advanced-analytics/tutorials/sqldev-py2-import-data-to-sql-server-using-powershell.md",
+            "redirect_url": "/sql/advanced-analytics/tutorials/demo-data-nyctaxi-in-sql",
+            "redirect_document_id": false
+        }, 
         {
             "source_path": "docs/advanced-analytics/r/configuration-sql-server-r-services.md",
             "redirect_url": "/sql/advanced-analytics/r/managing-and-monitoring-r-solutions",

docs/advanced-analytics/toc.yml

@@ -72,6 +72,8 @@
   items:
   - name: Data
     items:
+    - name: Airline data set
+      href: tutorials/demo-data-airlinedemo-in-sql.md
     - name: Iris data set
       href: tutorials/demo-data-iris-in-sql.md
     - name: NYC Taxi data set
@@ -84,8 +86,6 @@
     - name: Learn in-database analytics
       href: tutorials/sqldev-in-database-python-for-sql-developers.md
       items:
-      - name: Import data
-        href: tutorials/sqldev-py2-import-data-to-sql-server-using-powershell.md
       - name: Explore and visualize data
         href: tutorials/sqldev-py3-explore-and-visualize-the-data.md
       - name: Create data features

docs/advanced-analytics/tutorials/demo-data-airlinedemo-in-sql.md

@@ -0,0 +1,62 @@
+---
+title: Airline flight arrival and delay demo data set for SQL Server Python and R tutorials | Microsoft Docs
+Description: Create a database containing the Airline dataset from R and Python. This dataset is used in exercises showing how to wrap R language or Python code in a SQL Server stored procedure.
+ms.prod: sql
+ms.technology: machine-learning
+
+ms.date: 10/22/2018  
+ms.topic: tutorial
+author: HeidiSteen
+ms.author: heidist
+manager: cgronlun
+---
+#  Airline flight arrival demo data for SQL Server Python and R tutorials
+[!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md-winonly](../../includes/appliesto-ss-xxxx-xxxx-xxx-md-winonly.md)]
+
+In this exercise, create a SQL Server database to store imported data from R or Python built-in Airline demo data sets. R and Python distributions provide equivalent data, which you can import to a SQL Server database using Management Studio.
+
+To complete this exercise, you should have [SQL Server Management Studio](https://docs.microsoft.com/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-2017) or another tool that can run T-SQL queries.
+
+Tutorials and quickstarts using this data set include the following:
+
++  [Create a Python model using revoscalepy](use-python-revoscalepy-to-create-model.md)
+
+## Create the database
+
+1. Start SQL Server Management Studio, connect to a database engine instance that has R or Python integration.  
+
+2. In Object Explorer, right-click **Databases** and create a new database called **flightdata**.
+
+3. Right-click **flightdata**, click **Tasks**, click **Import Flat File**.
+
+4. Open the AirlineDemoData.csv file provided in the R or Python distribution, depending on which language you installed.
+
+   For R, look for **AirlineDemoSmall.csv** at C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\R_SERVICES\library\RevoScaleR\SampleData
+   
+   For Python, look for **AirlineDemoSmall.csv** at C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\PYTHON_SERVICES\Lib\site-packages\revoscalepy\data\sample_data
+  
+When you select the file, default values are filled in for table name and schema.
+
+  ![Import flat file wizard showing airline demo defaults](media/import-airlinedemosmall.png)
+
+Click through the remaining pages, accepting the defaults, to import the data.
+
+
+## Query the data
+
+As a validation step, run a query to confirm the data was uploaded.
+
+1. In Object Explorer, under Databases, right-click the **flightdata** database, and start a new query.
+
+2. Run some simple queries:
+
+    ```sql
+    SELECT TOP(10) * FROM AirlineDemoSmall;
+    SELECT COUNT(*) FROM AirlineDemoSmall;
+    ```
+
+## Next steps
+
+In the following lesson, you will create a linear regression model based on this data.
+
++ [Create a Python model using revoscalepy](use-python-revoscalepy-to-create-model.md)

docs/advanced-analytics/tutorials/demo-data-iris-in-sql.md

@@ -1,6 +1,6 @@
 ---
-title: Iris demo data set for SQL Server | Microsoft Docs
-Description: Create a database containing the Iris dataset and a table for storing models. This dataset is used in exercises showing how to wrap Python code in a SQL Server stored procedure.
+title: Iris demo data set for SQL Server Python and R tutorials | Microsoft Docs
+Description: Create a database containing the Iris dataset and a table for storing models. This dataset is used in exercises showing how to wrap R language or Python code in a SQL Server stored procedure.
 ms.prod: sql
 ms.technology: machine-learning
 
@@ -10,18 +10,18 @@ author: HeidiSteen
 ms.author: heidist
 manager: cgronlun
 ---
-#  Iris demo data for SQL Server
+#  Iris demo data for SQL Server Python and R tutorials
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md-winonly](../../includes/appliesto-ss-xxxx-xxxx-xxx-md-winonly.md)]
 
-In this exercise, prepare a SQL Server database containing tables for the [Iris flower data set](https://en.wikipedia.org/wiki/Iris_flower_data_set) and model storage. Iris data is included in both the R and Python distributions installed by SQL Server. It's used in machine learning tutorials for SQL Server. 
+In this exercise, create a SQL Server database to store data from the [Iris flower data set](https://en.wikipedia.org/wiki/Iris_flower_data_set) and models based on the same data. Iris data is included in both the R and Python distributions installed by SQL Server, and is used in machine learning tutorials for SQL Server. 
 
 To complete this exercise, you should have [SQL Server Management Studio](https://docs.microsoft.com/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-2017) or another tool that can run T-SQL queries.
 
 Tutorials and quickstarts using this data set include the following:
 
 +  [Use a Python model in SQL Server for training and scoring](train-score-using-python-in-tsql.md)
 
-## Prepare the database and tables
+## Create the database
 
 1. Start SQL Server Management Studio, and open a new **Query** window.  
 
@@ -134,7 +134,7 @@ You can obtain built-in Iris data from either R or Python. You can use Python or
     > To modify the stored procedure later, you don't need to drop and recreate it. Use the [ALTER PROCEDURE](https://docs.microsoft.com/sql/t-sql/statements/alter-procedure-transact-sql) statement. 
 
 
-## Query data for verification
+## Query the data
 
 As a validation step, run a query to confirm the data was uploaded.
 

docs/advanced-analytics/tutorials/demo-data-nyctaxi-in-sql.md

@@ -1,6 +1,6 @@
 ---
 title: Download NYC Taxi demo data and scripts for embedded R and Python (SQL Server Machine Learning) | Microsoft Docs
-description: Instructions for downloading New York City taxi sample data and creating a database. Data is used in SQL Server tutorials showing how to embed R and Python in SQL Server stored procedures and T-SQL functions.
+description: Instructions for downloading New York City taxi sample data and creating a database. Data is used in SQL Server Python and R language tutorials showing how to embed script in SQL Server stored procedures and T-SQL functions.
 ms.prod: sql
 ms.technology: machine-learning
 
@@ -10,7 +10,7 @@ author: HeidiSteen
 ms.author: heidist
 manager: cgronlun
 ---
-# NYC Taxi demo data for SQL Server
+# NYC Taxi demo data for SQL Server Python and R tutorials
 [!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md-winonly](../../includes/appliesto-ss-xxxx-xxxx-xxx-md-winonly.md)]
 
 This article explains how to set up a sample database consisting of public data from the [New York City Taxi and Limousine Commission](http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml). This data is used in several R and Python tutorials for in-database analytics in SQL Server. The sample data is one percent of the public data set. On your system, the database backup file is slightly over 90 MB, providing 1.7 million rows in the primary data table.
@@ -21,7 +21,7 @@ Tutorials and quickstarts using this data set include the following:
 
 +  [Use a Python model in SQL Server for training and scoring](train-score-using-python-in-tsql.md)
 
-## Download demo database
+## Download files
 
 The sample database is a backup file hosted by Microsoft. File download begins immediately when you click the link. 
 
@@ -61,7 +61,7 @@ The following table summarizes the objects created in the NYC Taxi demo database
 |**PredictTipSingleMode**  |stored procedure| Created by the PredictTipSingleMode.sql script. Calls the trained model to create predictions using the model. This stored procedure accepts a new observation as input, with individual feature values passed as in-line parameters, and returns a value that predicts the outcome for the new observation. This stored procedure is used in [Operationalize the R model](sqldev-operationalize-the-model.md).|
 |**TrainTipPredictionModel**  |stored procedure|Created by the TrainTipPredictionModel.sql script. Trains a logistic regression model by calling an R package. The model predicts the value of the  tipped column, and is trained using a randomly selected 70% of the data. The output of the stored procedure is the trained model, which is saved in the table nyc_taxi_models. This stored procedure is used in [Train and save a model](sqldev-train-and-save-a-model-using-t-sql.md).|
 
-## Query data for verification
+## Query the data
 
 As a validation step, run a query to confirm the data was uploaded.
 

docs/advanced-analytics/tutorials/machine-learning-services-tutorials.md

@@ -18,8 +18,6 @@ This article provides a comprehensive list of the tutorials, demos, and sample a
 
 + [R tutorials](../tutorials/sql-server-r-tutorials.md)
 
-For more information about requirements and how to get set up, see [Prerequisites](#bkmk_prerequisites).
-
 ## Samples and solutions
 
 + [Samples](#bkmk_samples) 
@@ -53,7 +51,7 @@ The Microsoft Data Science Team has provided solution templates that can be used
 
 For more information, see [Machine Learning Templates with SQL Server 2016 R Services](https://blogs.technet.microsoft.com/machinelearning/2016/03/23/machine-learning-templates-with-sql-server-2016-r-services/).
 
-## More resources and reading
+## Recommended reading
 
 + [Why did we build it?](https://blogs.msdn.microsoft.com/sqlserverstorageengine/2017/01/10/sql-server-r-services-why-did-we-build-it/)
 

docs/advanced-analytics/tutorials/media/import-airlinedemosmall.png

@@ -32,30 +32,23 @@ The data is from the well-known NYC Taxi data set. To make this walkthrough quic
 
 All tasks can be done using [!INCLUDE[tsql](../../includes/tsql-md.md)] stored procedures in the familiar environment of [!INCLUDE[ssManStudio](../../includes/ssmanstudio-md.md)]
 
-- [Step 1: Download the sample data](demo-data-nyctaxi-in-sql.md)
 
-    Download the sample dataset and all script files to a local computer.
-
-- [Step 2: Import data to SQL Server using PowerShell](sqldev-py2-import-data-to-sql-server-using-powershell.md)
-
-    Execute a PowerShell script that creates a database and a table on the specified instance, and loads the sample data to the table.
-
-- [Step 3: Explore and visualize the data using Python](sqldev-py3-explore-and-visualize-the-data.md)
+- [Explore and visualize the data using Python](sqldev-py3-explore-and-visualize-the-data.md)
 
     Perform basic data exploration and visualization, by calling Python from [!INCLUDE[tsql](../../includes/tsql-md.md)] stored procedures.
 
-- [Step 4: Create data features using Python in T-SQL](sqldev-py5-train-and-save-a-model-using-t-sql.md)
+- [Create data features using Python in T-SQL](sqldev-py5-train-and-save-a-model-using-t-sql.md)
 
     Create new data features using custom SQL functions.
 
-- [Step 5: Train and save a Python model using T-SQL](sqldev-py5-train-and-save-a-model-using-t-sql.md)
+- [Train and save a Python model using T-SQL](sqldev-py5-train-and-save-a-model-using-t-sql.md)
 
     Build and save the machine learning model, using Python in stored procedures.
 
     This walkthrough demonstrates how to perform a binary classification task; you could also use the data to build models for regression or multiclass classification.
 
 
--  [Step 6: Operationalize the Python model](sqldev-py6-operationalize-the-model.md)
+-  [ Operationalize the Python model](sqldev-py6-operationalize-the-model.md)
 
     After the model has been saved to the database, call the model for prediction using [!INCLUDE[tsql](../../includes/tsql-md.md)].