Update index.md

Including AWS to the heading to provide more clarity.

Author: dineshraj-arunmozhi

src/connections/storage/data-lakes/index.md

@@ -29,7 +29,7 @@ To learn more about Segment Data Lakes, check out the Segment blog post [Introdu
 
 Segment supports Data Lakes hosted on two cloud providers: Amazon Web Services (AWS) and Microsoft Azure. Each cloud provider has a similar system for managing data, but offer different query engines, post-processing systems, and analytics options.
 
-### How Segment Data Lakes works
+### How Segment Data Lakes (AWS) works
 
 Data Lakes store Segment data in S3 in a read-optimized encoding format (Parquet) which makes the data more accessible and actionable. To help you zero-in on the right data, Data Lakes also creates logical data partitions and event tables, and integrates metadata with existing schema management tools, such as the AWS Glue Data Catalog. The resulting data set is optimized for use with systems like Spark, Athena, EMR, or machine learning vendors like DataBricks or DataRobot.
 
@@ -49,7 +49,7 @@ Data Lakes store Segment data in ADLS in a read-optimized encoding format (Parqu
 
 For detailed Segment Data Lakes (Azure) setup instructions, see the [Data Lakes setup page](/docs/connections/storage/catalog/data-lakes/).
 
-### Set up Segment Data Lakes
+### Set up Segment Data Lakes (AWS)
 
 When setting up your data lake using the [Data Lakes catalog page](/docs/connections/storage/catalog/data-lakes/), be sure to consider the EMR and AWS IAM components listed below.
 
@@ -84,7 +84,7 @@ TODO:
 add schema overview (tables/columns generated)
 -->
 
-### Segment Data Lakes schema
+### Segment Data Lakes (AWS) schema
 
 #### S3 partition structure