diff --git a/manage-data/ingest/transform-enrich/index-mapping-text-analysis.md b/manage-data/ingest/transform-enrich/index-mapping-text-analysis.md
index 8b5e7f4c0c..cbb1c98a0a 100644
--- a/manage-data/ingest/transform-enrich/index-mapping-text-analysis.md
+++ b/manage-data/ingest/transform-enrich/index-mapping-text-analysis.md
@@ -1,7 +1,7 @@
 # Index mapping and text analysis
 
-% What needs to be done: Write from scratch
+As part of planning how your incoming data might be transformed and enriched as it is ingested, you may want to customize how the data should be organized inside {{es}} and how text fields should be analyzed.
 
-% GitHub issue: docs-projects#367
+Refer to [Mapping](/manage-data/data-store/mapping.md) to learn about the dynamic mapping rules that Elasticsearch runs by default to identify the data types in your data and to store it in matching fields. You can also configure your own custom mappings to take full control over how your data is organized in the documents in an {{es}} index.
 
-% Scope notes: This should be a stub page that makes it clear to the reader that next step in transforming/enriching data at ingest time is using index mapping and text analysis, and linking to where these concepts are documented in more detail (above in the The Elasticsearch data store section).
\ No newline at end of file
+Refer to [Text analysis](/manage-data/data-store/text-analysis.md) to learn how to configure an analyzer to run on incoming text, in order to ensure that relevant documents are retrieved from text-based queries. You can opt to use one of several built-in analyzers, or create a custom analyzer for your specific use cases.