Merge pull request #269239 from fbsolo-ms1/freshness-update-branch

Freshness update for how-to-designer-transform-data.md . . .

Author: Stacyrch140

articles/machine-learning/v1/how-to-designer-transform-data.md

@@ -15,7 +15,7 @@ ms.custom: UpdateFrequency5, designer
 
 # Transform data in Azure Machine Learning designer
 
-In this article, you'll learn how to transform and save datasets in the Azure Machine Learning designer, to prepare your own data for machine learning.
+In this article, you learn how to transform and save datasets in the Azure Machine Learning designer, to prepare your own data for machine learning.
 
 You'll use the sample [Adult Census Income Binary Classification](samples-designer.md) dataset to prepare two datasets: one dataset that includes adult census information from only the United States, and another dataset that includes census information from non-US adults.
 
@@ -28,135 +28,134 @@ In this article, you'll learn how to:
 This how-to is a prerequisite for the [how to retrain designer models](how-to-retrain-designer.md) article. In that article, you'll learn how to use the transformed datasets to train multiple models, with pipeline parameters.
 
 > [!IMPORTANT]
-> If you do not see graphical elements mentioned in this document, such as buttons in studio or designer, you may not have the right level of permissions to the workspace. Please contact your Azure subscription administrator to verify that you have been granted the correct level of access. For more information, see [Manage users and roles](../how-to-assign-roles.md).
+> If you do not observe graphical elements mentioned in this document, such as buttons in studio or designer, you may not have the correct level of permissions to the workspace. Please contact your Azure subscription administrator to verify that you have been granted the correct level of access. For more information, visit [Manage users and roles](../how-to-assign-roles.md).
 
 ## Transform a dataset
 
-In this section, you'll learn how to import the sample dataset, and split the data into US and non-US datasets. See [how to import data](how-to-designer-import-data.md) for more information about how to import your own data into the designer.
+In this section, you'll learn how to import the sample dataset, and split the data into US and non-US datasets. Visit [how to import data](how-to-designer-import-data.md) for more information about how to import your own data into the designer.
 
 ### Import data
 
 Use these steps to import the sample dataset:
 
-1. Sign in to <a href="https://ml.azure.com?tabs=jre" target="_blank">ml.azure.com</a>, and select the workspace you want to use.
+1. Sign in to [Azure Machine Learning studio](https://ml.azure.com), and select the workspace you want to use
 
-1. Go to the designer. Select **Easy-to-use-prebuild components** to create a new pipeline.
+1. Go to the designer. Select **Create a new pipeline using classic prebuilt components** to create a new pipeline
 
-1. Select a default compute target to run the pipeline.
+1. To the left of the pipeline canvas, in the **Component** tab, expand the **Sample data** node
 
-1. To the left of the pipeline canvas, you'll see a palette of datasets and components. Select **Datasets**. Then view the **Samples** section.
+1. Drag and drop the **Adult Census Income Binary classification** dataset onto the canvas
 
-1. Drag and drop the **Adult Census Income Binary classification** dataset onto the canvas.
+1. Right-select the **Adult Census Income** dataset component, and select **Preview data**
 
-1. Right-click the **Adult Census Income** dataset component, and select **Visualize** > **Dataset output**
-
-1. Use the data preview window to explore the dataset. Take special note of the "native-country" column values.
+1. Use the data preview window to explore the dataset. Take special note of the "native-country" column values
 
 ### Split the data
 
-In this section, you'll use the [Split Data component](../algorithm-module-reference/split-data.md) to identify and split rows that contain "United-States" in the "native-country" column.
+In this section, you'll use the [Split Data component](../algorithm-module-reference/split-data.md) to identify and split rows that contain "United-States" in the "native-country" column
 
-1. To the left of the canvas, in the component palette, expand the **Data Transformation** section, and find the **Split Data** component.
+1. To the left of the canvas, in the component tab, expand the **Data Transformation** section, and find the **Split Data** component
 
-1. Drag the **Split Data** component onto the canvas, and drop that component below the dataset component.
+1. Drag the **Split Data** component onto the canvas, and drop that component below the dataset component
 
-1. Connect the dataset component to the **Split Data** component.
+1. Connect the dataset component to the **Split Data** component
 
-1. Select the **Split Data** component.
+1. Select the **Split Data** component, to open the **Split Data** pane
 
-1. To the right of the canvas in the component details pane, set **Splitting mode** to **Regular Expression**.
+1. To the right of the canvas in the **Parameters** icon, set **Splitting mode** to **Regular Expression**
 
-1. Enter the **Regular Expression**: `\"native-country" United-States`.
+1. Enter the **Regular Expression**: `\"native-country" United-States`
 
-    The **Regular expression** mode tests a single column for a value. See the related [algorithm component reference page](../algorithm-module-reference/split-data.md) for more information on the Split Data component.
+    The **Regular expression** mode tests a single column for a value. Visit the related [algorithm component reference page](../algorithm-module-reference/split-data.md) for more information on the Split Data component
 
-Your pipeline should look like this:
+Your pipeline should resemble this screenshot:
 
 :::image type="content" source="./media/how-to-designer-transform-data/split-data.png" alt-text="Screenshot that shows how to configure the pipeline and the Split Data component":::
 
-
 ## Save the datasets
 
-Now that you set up your pipeline to split the data, you must specify where to persist the datasets. For this example, use the **Export Data** component to save your dataset to a datastore. See [Connect to Azure storage services](how-to-access-data.md) for more information about datastores.
+Now that you set up your pipeline to split the data, you must specify where to persist the datasets. For this example, use the **Export Data** component to save your dataset to a datastore. Visit [Connect to Azure storage services](how-to-access-data.md) for more information about datastores.
 
-1. To the left of the canvas in the component palette, expand the **Data Input and Output** section, and find the **Export Data** component.
+1. To the left of the canvas in the component palette, expand the **Data Input and Output** section, and find the **Export Data** component
 
-1. Drag and drop two **Export Data** components below the **Split Data** component.
+1. Drag and drop two **Export Data** components below the **Split Data** component
 
-1. Connect each output port of the **Split Data** component to a different **Export Data** component.
+1. Connect each output port of the **Split Data** component to a different **Export Data** component
 
-    Your pipeline should look something like this:
+    Your pipeline should resemble this:
 
-    ![Screenshot showing how to connect the Export Data components](media/how-to-designer-transform-data/export-data-pipeline.png).
+    ![Screenshot showing how to connect the Export Data components](media/how-to-designer-transform-data/export-data-pipeline.png)
 
-1. Select the **Export Data** component connected to the *left*-most port of the **Split Data** component.
+1. Select the **Export Data** component connected to the *left*-most port of the **Split Data** component, to open the Export Data configuration pane
 
-    For the **Split Data** component, the output port order matters. The first output port contains the rows where the regular expression is true. In this case, the first port contains rows for US-based income, and the second port contains rows for non-US based income.
+    For the **Split Data** component, the output port order is important. The first output port contains the rows where the regular expression is true. In this case, the first port contains rows for US-based income, and the second port contains rows for non-US based income
 
 1. In the component details pane to the right of the canvas, set the following options:
 
     **Datastore type**: Azure Blob Storage
 
-    **Datastore**: Select an existing datastore, or select "New datastore" to create one now.
+    **Datastore**: Select an existing datastore, or select "New datastore" to create a new one
 
     **Path**: `/data/us-income`
 
     **File format**: csv
 
     > [!NOTE]
-    > This article assumes that you have access to a datastore registered to the current Azure Machine Learning workspace. See [Connect to Azure storage services](how-to-connect-data-ui.md#create-datastores) for datastore setup instructions.
+    > This article assumes that you have access to a datastore registered to the current Azure Machine Learning workspace. Visit [Connect to Azure storage services](how-to-connect-data-ui.md#create-datastores) for datastore setup instructions
 
-    You can create a datastore if you don't have one now. For example purposes, this article will save the datasets to the default blob storage account associated with the workspace. It will save the datasets into the `azureml` container, in a new folder named `data`.
+    You can create a datastore if you don't have one now. For example purposes, this article saves the datasets to the default blob storage account associated with the workspace. It saves the datasets into the `azureml` container, in a new folder named `data`
 
-1.  Select the **Export Data** component connected to the *right*-most port of the **Split Data** component.
+1.  Select the **Export Data** component connected to the *right*-most port of the **Split Data** component, to open the Export Data configuration pane
 
 1. To the right of the canvas in the component details pane, set the following options:
 
     **Datastore type**: Azure Blob Storage
 
-    **Datastore**: Select the same datastore as above
+    **Datastore**: Select the earlier datastore
 
     **Path**: `/data/non-us-income`
 
     **File format**: csv
 
-1. Verify that the **Export Data** component connected to the left port of the **Split Data** has the **Path** `/data/us-income`.
+1. Verify that the **Export Data** component connected to the left port of the **Split Data** has the **Path** `/data/us-income`
 
-1. Verify that the **Export Data** component connected to the right port has the **Path** `/data/non-us-income`.
+1. Verify that the **Export Data** component connected to the right port has the **Path** `/data/non-us-income`
 
     Your pipeline and settings should look like this:
 
-    ![Screenshot showing how to configure the Export Data components](media/how-to-designer-transform-data/us-income-export-data.png).
+    ![Screenshot showing how to configure the Export Data components](media/how-to-designer-transform-data/us-income-export-data.png)
 
 ### Submit the job
 
 Now that you set up your pipeline to split and export the data, submit a pipeline job.
 
-1. Select **Submit** at the top of the canvas.
+1. Select **Configure & Submit** at the top of the canvas
 
-1. Select **Create new** in the **Set up pipeline job**, to create an experiment.
+1. Select the **Create new** option in the Basics pane of **Set up pipeline job**, to create an experiment
 
-    Experiments logically group related pipeline jobs together. If you run this pipeline in the future, you should use the same experiment for logging and tracking purposes.
+    Experiments logically group related pipeline jobs together. If you run this pipeline in the future, you should use the same experiment for logging and tracking purposes
 
-1. Provide a descriptive experiment name - for example "split-census-data".
+1. Provide a descriptive experiment name - for example "split-census-data"
 
-1. Select **Submit**.
+1. Select **Review + Submit**, and then select **Submit**
 
 ## View results
 
-After the pipeline finishes running, you can navigate to your Azure portal blob storage to view your results. You can also view the intermediary results of the **Split Data** component to confirm that your data has been split correctly.
+After the pipeline finishes running, you can navigate to your Azure portal blob storage to view your results. You can also view the intermediary results of the **Split Data** component to confirm that your data split correctly.
+
+1. Select the **Split Data** component
 
-1. Select the **Split Data** component.
+1. In the component details pane to the right of the canvas, select the **Outputs + logs** tab
 
-1. In the component details pane to the right of the canvas, select **Outputs + logs**.
+1. Select the **Show data outputs** dropdown
 
-1. Select the visualize icon ![visualize icon](media/how-to-designer-transform-data/visualize-icon.png) next to **Results dataset1**.
+1. Select the visualize icon ![visualize icon](media/how-to-designer-transform-data/visualize-icon.png) next to **Results dataset1**
 
-1. Verify that the "native-country" column contains only the value "United-States".
+1. Verify that the "native-country" column contains only the value "United-States"
 
-1. Select the visualize icon ![visualize icon](media/how-to-designer-transform-data/visualize-icon.png) next to **Results dataset2**.
+1. Select the visualize icon ![visualize icon](media/how-to-designer-transform-data/visualize-icon.png) next to **Results dataset2**
 
-1. Verify that the "native-country" column does not contain the value "United-States".
+1. Verify that the "native-country" column doesn't contain the value "United-States"
 
 ## Clean up resources