Merge pull request #100483 from PeterCLu/plu-import-data

How to import data designer

Author: Jak-MS

articles/machine-learning/algorithm-module-reference/import-data.md

@@ -22,7 +22,7 @@ Use this module to load data into a machine learning pipeline from existing clou
 >  After you register a dataset, you can find it in the **Datasets** -> **My Datasets** category in designer interface. This module is reserved for Studio(classic) users to for a familiar experience. 
 >
 
-First, choose the source you are reading from, and finish the additional settings. The **Import Data** module support read data from following sources:
+The **Import Data** module support read data from following sources:
 
 - URL via HTTP
 - Azure cloud storages through [**Datastores**](../how-to-access-data.md))

articles/machine-learning/how-to-designer-import-data.md

@@ -0,0 +1,89 @@
+---
+title: Import data
+titleSuffix: Azure Machine Learning
+description: Learn how to import your data into Azure Machine Learning designer from various data sources.
+services: machine-learning
+ms.service: machine-learning
+ms.subservice: core
+ms.topic: how-to
+
+author: peterclu
+ms.author: peterlu
+ms.date: 01/16/2020
+---
+
+# Import your data into Azure Machine Learning designer (preview)
+
+In this article, you learn how to import your own data in the designer to create custom solutions. There are two ways you can import data into the designer: 
+
+* **Azure Machine Learning datasets** - Register [datasets](concept-data.md#datasets) in Azure Machine Learning to enable advanced features that help you manage your data.
+* **Import Data module** - Use the [Import Data](algorithm-module-reference/import-data.md) module to directly access data from online datasources.
+
+## Use Azure Machine Learning datasets
+
+We recommend that you use [datasets](concept-data.md#datasets) to import data into the designer. When you register a dataset, you can take full advantage of advanced data features like [versioning and tracking](how-to-version-track-datasets.md) and [data monitoring](how-to-monitor-datasets.md).
+
+### Register a dataset
+
+You can register existing datasets [programatically with the SDK](how-to-create-register-datasets.md#use-the-sdk) or [visually in Azure Machine Learning studio](how-to-create-register-datasets.md#use-the-ui).
+
+You can also register the output for any designer module as a dataset.
+
+1. Select the module that outputs the data you want to register.
+
+1. In the properties pane, select **Outputs** > **Register dataset**.
+
+    ![Screenshot showing how to navigate to the Register Dataset option](media/how-to-designer-import-data/register-dataset-designer.png)
+
+### Use a dataset
+
+Your registered datasets can be found in the module palette, under **Datasets** > **My Datasets**. To use a dataset, drag and drop it onto the pipeline canvas. Then, connect the output port of the dataset to other modules in the palette.
+
+![Screenshot showing location of saved datasets in the designer palette](media/how-to-designer-import-data/use-datasets-designer.png)
+
+Any [file dataset](how-to-create-register-datasets.md#dataset-types) registered to your machine learning workspace will appear in the module palette. You aren't limited to using datasets created in the designer.
+
+> [!NOTE]
+> The designer currently only supports processing [tabular datasets](how-to-create-register-datasets.md#dataset-types). If you want to use [file datasets](how-to-create-register-datasets.md#dataset-types), use the Azure Machine Learning SDK available for Python and R.
+
+## Import data using the Import Data module
+
+While we recommend that you use datasets to import data, you can also use the [Import Data](algorithm-module-reference/import-data.md) module. The Import Data module skips registering your dataset in Azure Machine Learning and imports data directly from a [datastore](concept-data.md#datastores) or HTTP URL.
+
+For detailed information on how to use the Import Data module, see the [Import Data reference page](algorithm-module-reference/import-data.md).
+
+
+## Supported sources
+
+This section lists the data sources supported by the designer. Data comes into into the designer from either a datastore or from [tabular dataset](how-to-create-register-datasets.md#dataset-types).
+
+### Datastore sources
+For a list of supported datastore sources, see [Access data in Azure storage services](how-to-access-data.md#supported-data-storage-service-types).
+
+### Tabular dataset sources
+
+The designer supports tabular datasets created from the following sources:
+ * Delimited files
+ * JSON files
+ * Parquet files
+ * SQL queries
+
+## Data types
+
+The designer internally recognizes the following data types:
+
+* String
+* Integer
+* Decimal
+* Boolean
+* Date
+
+The designer uses an internal data type to pass data between modules. You can explicitly convert your data into data table format using the [Convert to Dataset](algorithm-module-reference/convert-to-dataset.md) module. Any module that accepts formats other than the internal format will convert the data silently before passing it to the next module.
+
+## Data constraints
+
+Modules in the designer are limited by the size of the compute target. For larger datasets, you should use a larger Azure Machine Learning compute resource. For more information on Azure Machine Learning compute, see [What are compute targets in Azure Machine Learning?](concept-compute-target.md#azure-machine-learning-compute-managed)
+
+## Next steps
+
+Learn the basics of the designer with [Tutorial: Predict automobile price with the designer](tutorial-designer-automobile-price-train-score.md).

articles/machine-learning/media/how-to-designer-import-data/register-dataset-designer.png

@@ -178,6 +178,9 @@
     - name: Train with datasets
       displayName: data, dataset, mount
       href: how-to-train-with-datasets.md
+    - name: Import data in the designer
+      displayName: designer, data, import, dataset, datastore
+      href: how-to-designer-import-data.md
     - name: Detect drift on datasets
       displayName: data, dataset
       href: how-to-monitor-datasets.md