diff --git a/docs/source/user-guide/data-sources.md b/docs/source/user-guide/data-sources.md
index 22e666837..15b5a7ddc 100644
--- a/docs/source/user-guide/data-sources.md
+++ b/docs/source/user-guide/data-sources.md
@@ -100,11 +100,16 @@ Supported Object Stores are
 - {py:class}`~datafusion.object_store.MicrosoftAzure`
 
 ```python
+import os
+
+from datafusion import SessionContext
 from datafusion.object_store import AmazonS3
 
 region = "us-east-1"
 bucket_name = "yellow-trips"
 
+ctx = SessionContext()
+
 s3 = AmazonS3(
     bucket_name=bucket_name,
     region=region,
@@ -120,6 +125,28 @@ ctx.register_parquet("trips", path)
 ctx.table("trips").show()
 ```
 
+### Use S3 in SQL
+
+Configure S3 access on an {py:class}`~datafusion.object_store.AmazonS3` object and
+register it on the context before issuing SQL that uses an `s3://` location. AWS
+credentials are not SQL `OPTIONS`: `aws.*` is not a recognized SQL configuration
+namespace.
+
+After registering the object store above, a SQL external table can use the same
+S3 path:
+
+```python
+ctx.sql(
+    f"""
+    CREATE EXTERNAL TABLE trips_sql
+    STORED AS PARQUET
+    LOCATION '{path}'
+    """
+).collect()
+
+ctx.sql("SELECT count(passenger_count) FROM trips_sql").show()
+```
+
 ## Other DataFrame Libraries
 
 DataFusion can import DataFrames directly from other libraries, such as