small changes after review with Apostolis

articles/TOC.yml

@@ -1135,7 +1135,7 @@
     items:
     - name: Overview
       href: automation-analytics-with-fabric-introduction.md
-    - name: Crafting automation-centric ad-hoc queries
+    - name: Create ad-hoc queries
       href: automation-analytics-with-fabric-queries.md
   - name: Capacity utilization
     items:

articles/automation-analytics-with-fabric-introduction.md

@@ -38,7 +38,7 @@ The Link to Microsoft Fabric feature built into Power Platform makes all your Dy
 
 ## Get started
 
-This guide explains how to use Dataverse shortcuts within Microsoft Fabric to create powerful data analytics solutions. By the end of this guide, you have the skills to build sophisticated data queries, generate insightful reports, design interactive dashboards, and set up proactive alerts to monitor your data at scale.
+This guide explains how to use Dataverse shortcuts within Microsoft Fabric to create powerful data analytics solutions. By the end of this guide, you have the skills to understand automation-centric data models, build sophisticated data queries in order to generate insightful reports.
 
 > [!NOTE]
 >
@@ -49,14 +49,14 @@ This guide explains how to use Dataverse shortcuts within Microsoft Fabric to cr
 Before you continue, ensure you meet the following prerequisites:
 
 1. Understand data modeling, Power Automate, Dataverse, and the Fabric ecosystem.
-2. Have access to a Dataverse environment (in the same region as your Fabric capacity) with a Power Automate premium license, (ideally) existing cloud, and desktop flow runs, and System Administrator role in this environment.
-3. Ensure that you meet the [**prerequisites**](/power-apps/maker/data-platform/azure-synapse-link-view-in-fabric#prerequisites) before linking your Dataverse environment with Fabric.
-4. Follow [**these steps**](/power-apps/maker/data-platform/azure-synapse-link-view-in-fabric#link-to-microsoft-fabric) to link your Dataverse environment with Microsoft Fabric. After linking the environment, you see a Lakehouse, a semantic model, and an SQL analytics endpoint. These items are prefixed with "Dataverse," followed by your environment name and a unique environment suffix, such as `dataverse_contosousap_cds2_workspace_unq111111111111111111111111`.
+1. Have access to a Dataverse environment (in the same region as your Fabric capacity) with a Power Automate premium license, (ideally) existing cloud, and desktop flow runs, and System Administrator role in this environment.
+1. Ensure that you meet the [**prerequisites**](/power-apps/maker/data-platform/azure-synapse-link-view-in-fabric#prerequisites) before linking your Dataverse environment with Fabric.
+1. Follow [**these steps**](/power-apps/maker/data-platform/azure-synapse-link-view-in-fabric#link-to-microsoft-fabric) to link your Dataverse environment with Microsoft Fabric. After linking the environment, you see a Lakehouse, a semantic model, and an SQL analytics endpoint. These items are prefixed with "Dataverse," followed by your environment name and a unique environment suffix, such as `dataverse_contosousap_cds2_workspace_unq111111111111111111111111`.
     :::image type="content" source="media/advanced-automation-related-data-analytics-fabric/fabric-workspace-with-lakehouse.png" alt-text="Screenshot of Fabric workspace showing a Dataverse-related lakehouse and other artifacts." lightbox="media/advanced-automation-related-data-analytics-fabric/fabric-workspace-with-lakehouse.png":::
-5. (Optional) Select Lakehouse settings and rename your Lakehouse to a more meaningful name, such as "contoso_westus_accounts_payable," and provide a brief description. This change helps others quickly identify the specific automations and data being processed in the Lakehouse.
+1. (Optional) Select Lakehouse settings and rename your Lakehouse to a more meaningful name, such as "contoso_westus_accounts_payable," and provide a brief description. This change helps others quickly identify the specific automations and data being processed in the Lakehouse.
     :::image type="content" source="media/advanced-automation-related-data-analytics-fabric/lakehouse-renaming.png" alt-text="Screenshot of the Fabric interface with details such as name, description, location, and ownership of a lakehouse." lightbox="media/advanced-automation-related-data-analytics-fabric/lakehouse-renaming.png":::
-6. (Optional) Link other Dataverse environments within the same geographical region to Fabric to create cross-environment analytics solutions.
-7. (Optional) If you plan to follow the advanced section for [Desktop flow action log-level analytics](automation-analytics-with-fabric-queries.md#governance-related-query-examples-for-v2-action-logs), ensure that [**Desktop Flow Logs V2**](/power-automate/desktop-flows/configure-desktop-flow-logs#configure-desktop-flow-action-log-version) is enabled in that environment and you have existing desktop flow runs.
+1. (Optional) Link other Dataverse environments within the same geographical region to Fabric to create cross-environment analytics solutions.
+1. (Optional) If you plan to follow the advanced section for [Desktop flow action log-level analytics](automation-analytics-with-fabric-queries.md#governance-related-query-examples-for-v2-action-logs), ensure that [**Desktop Flow Logs V2**](/power-automate/desktop-flows/configure-desktop-flow-logs#configure-desktop-flow-action-log-version) is enabled in that environment and you have existing desktop flow runs.
 
 ## What's next
 

articles/automation-analytics-with-fabric-queries.md

@@ -245,7 +245,7 @@ This query finds all desktop flows that use (OLEDB) database connection strings
 
 #### Potential SQL injection risk
 
-The query detects desktop flows that contain scripts potentially vulnerable to SQL injection by searching for the use of `database.executesqlstatement.execute` within the flow definitions. Consider a scenario where, instead of directly writing the SQL code in the [Execute SQL statement action](/power-automate/desktop-flows/actions-reference/database#executesqlstatement), the script uses a Power Automate desktop input variable (for example, *%LetsDeleteAllGeneralLedgerEntriesFromDB%*) provided to the script during runtime. Such a scenario could pose a significant SQL injection risk.
+The query detects desktop flows that contain scripts potentially vulnerable to SQL injection by searching for the use of `database.executesqlstatement.execute` within the flow definitions. Consider a scenario where, instead of directly writing the SQL code in the [Execute SQL statement action](/power-automate/desktop-flows/actions-reference/database#executesqlstatement), the script uses a Power Automate desktop input variable (for example, *%LetsDeleteAllGeneralLedgerEntriesFromDB%*) provided to the script during runtime.
 
 :::image type="content" source="media/advanced-automation-related-data-analytics-fabric/execute-sql-statmenet-risk.png" alt-text="Screenshot of an 'Execute SQL statement' configuration dialog in Power Automate desktop." lightbox="media/advanced-automation-related-data-analytics-fabric/execute-sql-statmenet-risk.png":::