Scrubbed docs for broken links

Author: HeidiSteen

articles/search/TOC.yml

@@ -258,8 +258,6 @@
       href: search-query-understand-collection-filters.md
     - name: Filter by language
       href: search-filters-language.md
-    - name: Example of multi-level facets
-      href: search-example-adventureworks-multilevel-faceting.md
   - name: Results
     items:
     - name: Work with results

articles/search/index-sql-relational-data.md

@@ -102,7 +102,7 @@ The solution is to capture the room detail as nested JSON, and then insert the J
 This rowset is now ready for import into Azure Cognitive Search.
 
 > [!NOTE]
-> This approach assumes that embedded JSON is under the [maximum column size limits of SQL Server](https://docs.microsoft.com/sql/sql-server/maximum-capacity-specifications-for-sql-server). If your data doesn't fit, you can try a programmatic approach, as illustrated in [Example: Model the AdventureWorks Inventory database for Azure Cognitive Search](search-example-adventureworks-modeling.md).
+> This approach assumes that embedded JSON is under the [maximum column size limits of SQL Server](https://docs.microsoft.com/sql/sql-server/maximum-capacity-specifications-for-sql-server). 
 
  ## Use a complex collection for the "many" side of a one-to-many relationship
 

articles/search/search-example-adventureworks-modeling.md

@@ -24,10 +24,8 @@ Some situations where field mappings are useful:
 * You need to Base64 encode or decode your data. Field mappings support several **mapping functions**, including functions for Base64 encoding and decoding.
 
 > [!NOTE]
-> The field mapping feature of Azure Cognitive Search indexers provides a simple way to map data fields to index fields, with a few options for data conversion. More complex data might require pre-processing to reshape it into a form that's easy to index.
->
-> Microsoft Azure Data Factory is a powerful cloud-based solution for importing and transforming data. You can also write code to transform source data before indexing. For code examples, see [Model relational data](search-example-adventureworks-modeling.md) and [Model multilevel facets](search-example-adventureworks-multilevel-faceting.md).
->
+> The field mapping feature of Azure Cognitive Search indexers provides a simple way to map data fields to index fields, with a few options for data conversion. More complex data might require pre-processing to reshape it into a form that's easy to index. One option you might consider is [Azure Data Factory](https://docs.microsoft.com/zure/data-factory/).
+
 
 ## Set up field mappings
 
@@ -242,8 +240,6 @@ Azure SQL Database doesn't have a built-in data type that naturally maps to `Col
   }]
 ```
 
-For a detailed example that transforms relational data into index collection fields, see [Model relational data](search-example-adventureworks-modeling.md).
-
 <a name="urlEncodeFunction"></a>
 
 ### urlEncode function