Merge origin/master — resolve conflicts in featured-quickstarts.json and aiapps_natural_language_with_claude.md

- featured-quickstarts.json: combined both branches, FFF April 2026 entry added ahead of the three QS entries from master
- aiapps_natural_language_with_claude.md: accepted master (published, complete version with screenshots)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: pballai

site/app/data/announcement.json

@@ -1,7 +1,7 @@
 {
   "visible": true,
-  "title": "Content update:",
+  "title": "WORKFLOW 2026 - ",
 
-  "message": "The QuickStart <strong>Forms: Quick Capture and Analysis</strong> has been replaced. See the updated version: <a href='/guide/aiapps_forms/index.html' style='color: #000000 !important;'><strong>Building Forms for Data Capture and Analysis</strong></a>"
+  "message": "<strong>SIGMA'S FIRST USER CONFERENCE</strong> <a href='https://www.sigmacomputing.com/resources/webinars-and-events/workflow-on-demand?upload_salesforce_campaign_id=701Nt00000dyUclIAE&upload_campaign_member_status=Registered' target='_blank' style='color: #000000 !important;'><strong>WATCH THE HIGHLIGHTS &#8594;</strong></a>"
 
 }

site/app/data/featured-quickstarts.json

@@ -6,6 +6,24 @@
       "category": "first_friday_features",
       "date": "May 1, 2026"
     },
+    {
+      "title": "Reshaping Data with Transpose Tables",
+      "id": "tables_transpose_tables",
+      "category": "tables",
+      "date": "April 24, 2026"
+    },
+    {
+      "title": "Scheduling Sigma Insights to Slack",
+      "id": "aiapps_scheduling_sigma_insights_to_slack",
+      "category": "aiapps",
+      "date": "April 15, 2026"
+    },
+    {
+      "title": "Natural Language Analytics with Claude and Sigma",
+      "id": "aiapps_natural_language_with_claude",
+      "category": "aiapps",
+      "date": "April 15, 2026"
+    },
     {
       "title": "Building Forms for Data Capture and Analysis",
       "id": "aiapps_forms",
@@ -59,18 +77,6 @@
       "id": "developers_data_models_as_code",
       "category": "Developers",
       "date": "Jan 29, 2026"
-    },
-    {
-      "title": "Sigma Tenants: Managing Isolated Organizations",
-      "id": "administration_multitenancy",
-      "category": "Administration",
-      "date": "Jan 26, 2026"
-    },    
-    {
-      "title": "Fundamentals 11: Pixel Perfect Reporting",
-      "id": "fundamentals_11_pixel_perfect_reporting",
-      "category": "Fundamentals",
-      "date": "Jan 6, 2026"
     }
   ]
 }

site/sigmaguides/src/Fundamentals 10: Data Modeling/fundamentals_10_data_modeling.md

@@ -456,7 +456,7 @@ The user does not see the underlying calculation, but knows that since it is a m
 ### Metric best practices:
 
 **Define Metrics in Your Data Models:**<br>
-Establish Metrics within Data Models to ensure uniform calculations across all analyses.​ When Metrics are created in Data Models (rather than on warehouse tables), users gain significantly more functionality, including a display of metrics at the top of a Data Model, and a centralized browsing UX.
+Establish Metrics within Data Models to ensure uniform calculations across all analyses. When Metrics are created in Data Models (rather than on warehouse tables), users gain significantly more functionality, including a display of metrics at the top of a Data Model, and a centralized browsing UX.
 
 **Apply Time Series to Metric Displays:**<br>
 When creating a Metric, you have the ability to specify a time series field to display the Metric value over time in all Metric previews. This provides users with more context around the KPI. You can also choose to compare metric values to previous periods if desired.
@@ -465,7 +465,7 @@ When creating a Metric, you have the ability to specify a time series field to d
 Name Metrics intuitively and provide clear descriptions to aid user understanding and adoption.​
 
 **Use Aggregations in Metrics:**<br>
-Metrics are meant to serve as aggregations over dimensional columns. They’ll always calculate at the correct level of aggregation, no matter how many groupings you use. Be sure to use aggregations in your Metric Formulas
+Metrics are meant to serve as aggregations over dimensional columns. They’ll always calculate at the correct level of aggregation, no matter how many groupings you use. Be sure to use aggregations in your Metric Formulas.
 
 ![Footer](assets/sigma_footer.png)
 <!-- END OF SECTION-->
@@ -628,7 +628,7 @@ Duration: 5
 
 Sigma data models support built-in materialization.
 
-Data models that use expensive or long-running queries, such as a complex join between data elements, or data with high cardinality, multiple grouping levels, and calculated columns, setting up materialization can enhance query performance and can help reduce compute costs.
+For data models that use expensive or long-running queries — such as complex joins between data elements, or data with high cardinality, multiple grouping levels, and calculated columns — setting up materialization can enhance query performance and reduce compute costs.
 
 Back in the data model again and in `Edit` mode, click the `+` icon next to `MATERIALIZATION` to create a new job: