Update cognitive-search-incremental-indexing-conceptual.md

Improve documentation to let the customers know that change and deletion tracking in general are managed per data source and not directly configured as part of this article.

Author: gmndrg

articles/search/cognitive-search-incremental-indexing-conceptual.md

@@ -8,7 +8,7 @@ ms.service: cognitive-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 02/16/2024
+ms.date: 06/17/2024
 ---
 
 # Incremental enrichment and caching in Azure AI Search
@@ -18,6 +18,8 @@ ms.date: 02/16/2024
 
 *Incremental enrichment* refers to the use of cached enrichments during [skillset execution](cognitive-search-working-with-skillsets.md) so that only new and changed skills and documents incur pay-as-you-go processing charges for API calls to Azure AI services. The cache contains the output from [document cracking](search-indexer-overview.md#document-cracking), plus the outputs of each skill for every document. Although caching is billable (it uses Azure Storage), the overall cost of enrichment is reduced because the costs of storage are less than image extraction and AI processing.
 
+To ensure synchronization between your data source data and your index, it's important to understand your unique [data source](search-data-sources-gallery.md) change and deletion tracking prerequisites. This guide specifically addresses how to manage incremental modifications in terms of your skills procressing and how to utilize cache for this purpose.
+
 When you enable caching, the indexer evaluates your updates to determine whether existing enrichments can be pulled from the cache. Image and text content from the document cracking phase, plus skill outputs that are upstream or orthogonal to your edits, are likely to be reusable.
 
 After skillset processing is finished, the refreshed results are written back to the cache, and also to the search index or knowledge store.