Minor edits

Author: cdpark

articles/synapse-analytics/security/synapse-private-link-hubs.md

@@ -14,7 +14,7 @@ ms.reviewer: whhender
 
 This article explains how you can securely connect to Azure Synapse Studio from your Azure virtual network using private links. Azure Synapse Analytics private link hubs are Azure resources that act as connectors between your secured network and the Synapse Studio web experience.
 
-There are two steps to connect to Synapse Studio using private links:
+There are two steps for connecting to Synapse Studio using private links:
 
 1. Create an Azure private link hubs resource.
 1. Create a private endpoint from your Azure virtual network to this private link hub.
@@ -27,9 +27,9 @@ You can use a single Azure Synapse private link hub resource to privately connec
 
 Follow these steps to create an Azure private link hub:
 
-1. Sign in to the Azure portal and search for *Synapse private link hubs*.
+1. Sign in to the Azure portal and enter *Synapse private link hubs* in the search field.
 
-1. Select **Azure Synapse Analytics (private link hubs)** from the list under **Services**.
+1. Select **Azure Synapse Analytics (private link hubs)** from the results under **Services**.
 
 For a detailed guide, follow the steps in [Connect to workspace resources from a restricted network](./how-to-connect-to-workspace-from-restricted-network.md). Certain URLs must be accessible from the client browser after enabling Azure Synapse private link hub.
 

articles/synapse-analytics/spark/apache-spark-manage-pool-packages.md

@@ -77,7 +77,7 @@ Spark pool libraries can be managed either from Synapse Studio or the Azure port
 
 A system reserved Spark job is initiated each time a pool is updated with a new set of libraries. This Spark job helps monitor the status of the library installation. If the installation fails due to library conflicts or other issues, the Spark pool reverts to its previous or default state.
 
-In addition, users can also inspect the installation logs to identify dependency conflicts or see which libraries were installed during the pool update.
+In addition, users can inspect the installation logs to identify dependency conflicts or see which libraries were installed during the pool update.
 
 To view these logs:
 
@@ -111,7 +111,7 @@ alabaster==0.7.10
 
 ### YML format
 
-In addition, you can also provide an *environment.yml* file to update the pool environment. The packages listed in this file are downloaded from the default Conda channels, Conda-Forge, and PyPI. You can specify other channels or remove the default channels by using the configuration options.
+In addition, you can provide an *environment.yml* file to update the pool environment. The packages listed in this file are downloaded from the default Conda channels, Conda-Forge, and PyPI. You can specify other channels or remove the default channels by using the configuration options.
 
 This example specifies the channels and Conda/PyPI dependencies.
 
@@ -127,7 +127,7 @@ dependencies:
   - koalas==1.7.0
 ```
 
-For details on creating an environment from this *environment.yml* file, see [Creating an environment from an environment.yml file](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment).
+For details on creating an environment from this *environment.yml* file, see [Activating an environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment).
 
 ## Related content
 

articles/synapse-analytics/sql-data-warehouse/sql-data-warehouse-manage-compute-overview.md

@@ -19,7 +19,7 @@ This article explains how to manage compute resources for dedicated SQL pool (fo
 
 The architecture of dedicated SQL pool separates storage and compute, allowing each to scale independently. As a result, you can scale compute to meet performance demands independent of data storage. You can also pause and resume compute resources.
 
-A natural consequence of this architecture is that [billing](https://azure.microsoft.com/pricing/details/synapse-analytics/) for compute and storage is separate. If you don't need to use your dedicated SQL pool for a while, you can save compute costs by pausing compute.
+A natural consequence of this architecture is that [pricing](https://azure.microsoft.com/pricing/details/synapse-analytics/) for compute and storage is separate. If you don't need to use your dedicated SQL pool for a while, you can save compute costs by pausing compute.
 
 ## Scaling compute
 
@@ -111,7 +111,7 @@ When you pause or scale your dedicated SQL pool, behind the scenes your queries
 
 Rolling back the work completed by a transactional query can take as long, or even longer, than the original change the query was applying. For example, if you cancel a query that was deleting rows and has already been running for an hour, it could take the system an hour to insert back the deleted rows. If you run pause or scaling while transactions are in flight, your pause or scaling might seem to take a long time because pausing and scaling has to wait for the rollback to complete before it can proceed.
 
-For more information, see [Understanding transactions](sql-data-warehouse-develop-transactions.md) and [Optimizing transactions](sql-data-warehouse-develop-best-practices-transactions.md).
+For more information, see [Use transactions](sql-data-warehouse-develop-transactions.md) and [Optimizing transactions](sql-data-warehouse-develop-best-practices-transactions.md).
 
 ## Automate compute management
 

articles/synapse-analytics/toc.yml

@@ -764,7 +764,7 @@ items:
       items:
       - name: Manage Workspace packages
         href: ./spark/apache-spark-manage-workspace-packages.md
-      - name: Manage Spark pool libraries
+      - name: Manage Spark pool packages
         href: ./spark/apache-spark-manage-pool-packages.md
       - name: Manage Notebook session packages
         href: ./spark/apache-spark-manage-session-packages.md