Merge pull request #292506 from whhender/december-synapse-freshness

December synapse freshness part 4

Author: Jill Grant

articles/synapse-analytics/.openpublishing.redirection.synapse-analytics.json

@@ -25,6 +25,16 @@
             "redirect_url": "/azure/synapse-analytics/partner/data-integration",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/synapse-analytics/machine-learning/tutorial-automl.md",
+            "redirect_url": "/azure/synapse-analytics/machine-learning/what-is-machine-learning",
+            "redirect_document_id": false
+        },
+        {
+          "source_path_from_root": "/articles/synapse-analytics/spark/apache-spark-azure-machine-learning-tutorial.md",
+          "redirect_url": "/azure/synapse-analytics/machine-learning/what-is-machine-learning",
+          "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/synapse-analytics/sql-data-warehouse/sql-data-warehouse-partner-data-management.md",
             "redirect_url": "/azure/synapse-analytics/partner/data-management",

articles/synapse-analytics/database-designer/quick-start-create-lake-database.md

@@ -7,7 +7,7 @@ ms.reviewer: wiassaf, jovanpop
 ms.service: azure-synapse-analytics
 ms.subservice: database-editor
 ms.topic: quickstart
-ms.date: 08/16/2022
+ms.date: 12/31/2024
 ms.custom: template-concept
 ---
 
@@ -23,9 +23,9 @@ This quick start gives you a complete sample scenario on how you can apply datab
 
 ## Create a lake database from database templates
 
-Use the new database templates functionality to create a lake database that you can use to configure your data model for the database. 
+Use the new database templates functionality to create a lake database that you can use to configure your data model for the database.
 
-For our scenario we will use the `Retail` database template and select the following entities: 
+For our scenario we'll use the `Retail` database template and select the following entities:
 
 - **RetailProduct** - A product is anything that can be offered to a market that might satisfy a need by potential customers. That product is the sum of all physical, psychological, symbolic, and service attributes associated with it.
 - **Transaction** - The lowest level of executable work or customer activity.
@@ -43,7 +43,7 @@ The easiest way to find entities is by using the search box above the different
 
 After you have created the database, make sure the storage account and the filepath is set to a location where you wish to store the data. The path will default to the primary storage account within Azure Synapse Analytics but can be changed to your needs. 
 
- :::image type="content" source="./media/quick-start-create-lake-database/lake-database-example.png" alt-text="Screenshot of an individual entity properties in the Retail database template." lightbox="./media/quick-start-create-lake-database/lake-database-example.png":::
+ :::image type="content" source="./media/quick-start-create-lake-database/lake-database-example.png" alt-text="Screenshot of an individual entity property in the Retail database template." lightbox="./media/quick-start-create-lake-database/lake-database-example.png":::
 
 To save your layout and make it available within Azure Synapse, **Publish** all changes. This step completes the setup of the lake database and makes it available to all components within Azure Synapse Analytics and outside. 
 
@@ -77,10 +77,6 @@ df = spark.sql("SELECT * FROM `Retail_mil`.`RetailProduct`")
 df.show(10)
 ```
 
-## Train machine learning models
-
-You can use lake database to train your machine learning models and score the data. For more details [Train machine learning models](../machine-learning/tutorial-automl.md) 
-
 ## Next steps
 
 Continue to explore the capabilities of the database designer using the links below.