Merge pull request #286811 from whhender/synapse-freshness-sept-2024

Synapse freshness sept 2024

Author: JamesJBarnett

articles/synapse-analytics/get-started-analyze-sql-on-demand.md

@@ -7,7 +7,7 @@ ms.reviewer: whhender, wiassaf
 ms.service: azure-synapse-analytics
 ms.subservice: sql
 ms.topic: tutorial
-ms.date: 02/15/2023
+ms.date: 09/16/2024
 ---
 
 # Analyze data with a serverless SQL pool
@@ -18,16 +18,16 @@ In this tutorial, you'll learn how to analyze data with serverless SQL pool.
 
 Serverless SQL pools let you use SQL without having to reserve capacity. Billing for a serverless SQL pool is based on the amount of data processed to run the query and not the number of nodes used to run the query.
 
-Every workspace comes with a pre-configured serverless SQL pool called **Built-in**. 
+Every workspace comes with a preconfigured serverless SQL pool called **Built-in**. 
 
 ## Analyze NYC Taxi data with a serverless SQL pool
 
 > [!NOTE]
 > Make sure you have [placed the sample data into the primary storage account](get-started-create-workspace.md#place-sample-data-into-the-primary-storage-account)
 
-1. In Synapse Studio, go to the **Develop** hub
+1. In the Synapse Studio, go to the **Develop** hub
 1. Create a new SQL script.
-1. Paste the following code into the script.
+1. Paste the following code into the script. (Update `contosolake` to the name of your storage account and `users` with the name of your container.)
 
     ```sql
     SELECT
@@ -38,7 +38,8 @@ Every workspace comes with a pre-configured serverless SQL pool called **Built-i
             FORMAT='PARQUET'
         ) AS [result]
     ```
-1. Select **Run**. 
+
+1. Select **Run**.
 
 Data exploration is just a simplified scenario where you can understand the basic characteristics of your data. Learn more about data exploration and analysis in this [tutorial](sql/tutorial-data-analyst.md).
 
@@ -51,23 +52,23 @@ However, as you continue data exploration, you might want to create some utility
 - Database users with the permissions to access some data sources or database objects.
 - Utility views, procedures, and functions that you can use in the queries.
 
-1. Use the `master` database to create a separate database for custom database objects. Custom database objects, cannot be created in the `master` database.
+1. Use the `master` database to create a separate database for custom database objects. Custom database objects can't be created in the `master` database.
 
    ```sql
    CREATE DATABASE DataExplorationDB 
                    COLLATE Latin1_General_100_BIN2_UTF8
    ```
 
    > [!IMPORTANT]
-   > Use a collation with `_UTF8` suffix to ensure that UTF-8 text is properly converted to `VARCHAR` columns. `Latin1_General_100_BIN2_UTF8` provides the best performance in the queries that read data from Parquet files and Azure Cosmos DB containers. For more information on changing collations, refer to [Collation types supported for Synapse SQL](sql/reference-collation-types.md).
+   > Use a collation with `_UTF8` suffix to ensure that UTF-8 text is properly converted to `VARCHAR` columns. `Latin1_General_100_BIN2_UTF8` provides the best performance in the queries that read data from Parquet files and Azure Cosmos DB containers. For more information on changing collations, see [Collation types supported for Synapse SQL](sql/reference-collation-types.md).
 
 1. Switch the database context from `master` to `DataExplorationDB` using the following command. You can also use the UI control **use database** to switch your current database:
 
    ```sql
    USE DataExplorationDB
    ```
 
-1. From `DataExplorationDB`, create utility objects such as credentials and data sources.
+1. From `DataExplorationDB` create utility objects such as credentials and data sources.
 
    ```sql
    CREATE EXTERNAL DATA SOURCE ContosoLake