Merging Vasiya's changes

Author: garyericson

articles/azure-sql-edge/deploy-azure-resources.md renamed to articles/azure-sql-edge/tutorial-deploy-azure-resources.md

@@ -17,15 +17,14 @@ In this three-part tutorial, you'll create a machine learning model to predict i
 ## Prerequisites
 
 1. If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/).
-2. Install [Visual Studio Professional/Enterprise](https://visualstudio.microsoft.com/vs/).
-3. Install [Python 3.6.8](https://www.python.org/downloads/release/python-368/).
+2. Install [Python 3.6.8](https://www.python.org/downloads/release/python-368/).
       * Use the Windows x86-x64 executable installer
       * Add `python.exe` to the PATH environment variable
-4. Install [Microsoft Visual C++ 14.0 and build tools for Visual Studio](https://visualstudio.microsoft.com/downloads/). You can find the download under "Tools For Visual Studio 2019".
-5. Install [Microsoft ODBC Driver 17 for SQL Server](https://www.microsoft.com/download/details.aspx?id=56567).
-6. Install [Azure Data Studio](/sql/azure-data-studio/download-azure-data-studio/)
-7. Open Azure Data Studio and configure Python for notebooks. For details, see [Configure Python for Notebooks](/sql/azure-data-studio/sql-notebooks#configure-python-for-notebooks).This step can take several minutes.
-8. Install the latest version of [Azure CLI](https://github.com/Azure/azure-powershell/releases/tag/v3.5.0-February2020).
+downloads/). You can find the download under "Tools For Visual Studio 2019".
+3. Install [Microsoft ODBC Driver 17 for SQL Server](https://www.microsoft.com/download/details.aspx?id=56567).
+4. Install [Azure Data Studio](/sql/azure-data-studio/download-azure-data-studio/)
+5. Open Azure Data Studio and configure Python for notebooks. For details, see [Configure Python for Notebooks](/sql/azure-data-studio/sql-notebooks#configure-python-for-notebooks).This step can take several minutes.
+6. Install the latest version of [Azure CLI](https://github.com/Azure/azure-powershell/releases/tag/v3.5.0-February2020). The following scripts require that AZ PowerShell be the latest version (3.5.0, Feb 2020).
 
 ## Deploy Azure resources using PowerShell Script
 
@@ -272,4 +271,4 @@ Deploy the Azure resources required by this Azure SQL Edge tutorial. These can b
 
 ## Next Steps
 
-- [Set up IoT Edge modules and connections](set-up-iot-edge-modules.md)
+* [Set up IoT Edge modules and connections](tutorial-set-up-iot-edge-modules.md)

articles/azure-sql-edge/run-ml-model-on-sql-edge.md renamed to articles/azure-sql-edge/tutorial-run-ml-model-on-sql-edge.md

@@ -155,7 +155,7 @@ Enter the following Python code in the Azure Data Studio notebook and run it.
    ```python
    ## Load the Model into a SQL Database.
    ## Define the Connection string parameters. These connection strings will be used later also in the demo.
-   server = '40.69.153.211,1600' # SQL Server IP address
+   server = '<SQL Server IP address>'
    username = 'sa' # SQL Server username
    password = '<SQL Server password>'
    database = 'IronOreSilicaPrediction'
@@ -177,7 +177,7 @@ Enter the following Python code in the Azure Data Studio notebook and run it.
 
    ```python
    ## Define the Connection string parameters. These connection strings will be used later also in the demo.
-   server = '40.69.153.211,1600' # SQL Server IP address
+   server = '<SQL Server IP address>'
    username = 'sa' # SQL Server username
    password = '<SQL Server password>'
    database = 'IronOreSilicaPrediction'
@@ -220,5 +220,4 @@ Enter the following Python code in the Azure Data Studio notebook and run it.
 
 ## Next steps
 
-For more information on using ONNX models in Azure SQL Edge, see 
-[Machine learning and AI with ONNX in Azure SQL Edge (Preview)](https://review.docs.microsoft.com/en-us/azure/azure-sql-edge/onnx-overview?branch=release-preview-sqldb-edge)
+For more information on using ONNX models in Azure SQL Edge, see [Machine learning and AI with ONNX in SQL Edge (Preview)](onnx-overview.md).

articles/azure-sql-edge/set-up-iot-edge-modules.md renamed to articles/azure-sql-edge/tutorial-set-up-iot-edge-modules.md

@@ -16,7 +16,7 @@ ms.date: 05/19/2020
 In part two of this three-part tutorial for predicting iron ore impurities in Azure SQL Edge, you'll set up the following IoT Edge modules:
 
 - Azure SQL Edge
-- A data generator module
+- Data generator IoT Edge module
 
 ## Create Azure Stream Analytics module
 
@@ -32,14 +32,17 @@ Once the Azure Stream Analytics job is created with the hosting environment set
    Encoding|UTF-8
    Event compression type|None
 
-2. To create the **output**, click **+Add** and choose SQL Database. Fill the details section using the following information:
+2. To create the **output**, click **+Add** and choose SQL Database. Fill the details section using the following information.
+
+   > [!NOTE]
+   > The password specified in this section needs to be specified for SQL SA password when deploying the SQL Edge module in section **"Deploy the Azure SQL Edge module"**.
 
    Field|Value
    -----|-----
    Database|IronOreSilicaPrediction
    Server name|tcp:.,1433
    Username|sa
-   Password|YourStrongPasswrod
+   Password|Specify a strong password
    Table|IronOreMeasurements1
 
 3. Navigate to the **Query** section and set up the query as follows:
@@ -91,7 +94,7 @@ Now, specify the container credentials in the IoT Edge module.
 
 3. CLick **Add**.
 
-## Deploythe Azure SQL Edge module
+## Deploy the Azure SQL Edge module
 
 1. Deploy the Azure SQL Edge module by following the steps listed in [Deploy Azure SQL Database Edge Preview](https://docs.microsoft.com/azure/sql-database-edge/deploy-portal#deploy-sql-database-edge).
 
@@ -120,15 +123,6 @@ Now, specify the container credentials in the IoT Edge module.
        }
    ```
 
-   For example:
-   
-   ```json
-         {
-           "SqlPackage": "https://ASEstorage.blob.core.windows.net/sqldatabasedacpac/SQLDatabasedacpac.zip?sp=r&st=2020-04-  01T20:01:49Z&se=2021-01-01T05:01:49Z&spr=https&sv=2019-02-02&sr=b&sig=AH71glRTfULcyzJZKlgezfa0Epjfe7zv10mF%2BNzEIn0%3D",
-           "ASAJobInfo": "https://ASEstorage.blob.core.windows.net/bootdiagnostics-ironorepr-6984a2b8-6901-41a8-b3a6-49f86276e63d/ASAEdgeJobs/1278e9b9-94af-41ec-90b3-8172560340c1/e9bb25a6-d0a1-422b-9e29-4305a89e92f2/ASAEdgeJobDefinition.zip?sv=2018-03-28&sr=b&sig=KQZqR7diisByoUkCK6pEA3VJm%2FI2wHWEPDL1OwjMTJ8%3D&st=2020-04-01T20%3A21%3A20Z&se=2023-04-01T20%3A31%3A20Z&sp=r"
-         }
-   ```
-
 ## Next Steps
 
-- [Deploy ML model on Azure SQL Edge using ONNX](run-ml-model-on-sql-edge.md)
+- [Deploy ML model on Azure SQL Edge using ONNX](tutorial-run-ml-model-on-sql-edge.md)