Fix typo in event processing section

Corrected minor typographical error in the text.

Author: Carolyn135

learn-pr/data-ai-cert/introduction-to-data-streaming/includes/3-understand-event-processing.md

@@ -26,7 +26,7 @@ Azure Stream Analytics can ingest data from the following kinds of input:
 - Azure Data Lake Storage Gen2
 - Apache Kafka
 
-Inputs are generally used to reference a source of streaming data, which is processed as new event records are added. Additionally, you can define *reference* inputs that are used to ingest static data to augment the real-time event stream data. For example, you could ingest a stream of real-time weather observation data that includes a unique ID for each weather station, and augment that data with a static reference input that matches the weather station ID to a more meaningful name.
+Inputs are generally used to reference a source of streaming data, which is processed as new event records are added. Additionally, you can define *reference* inputs that are used to ingest static data to augment the real-time eventstream data. For example, you could ingest a stream of real-time weather observation data that includes a unique ID for each weather station, and augment that data with a static reference input that matches the weather station ID to a more meaningful name.
 
 ## Outputs
 
@@ -56,4 +56,4 @@ The field used as a timestamp is important when aggregating data over temporal w
 
 If you prefer to build your stream processing job without writing SQL, Azure Stream Analytics includes a no-code editor. You can access it from the Azure Stream Analytics portal or the Azure Event Hubs portal. The no-code editor provides a drag-and-drop canvas where you connect input sources, add transformations (including windowing and aggregations), and configure outputs—without writing any code.
 
-You can use the no-code editor to prototype quickly, and then optionally view or customize the generated SQL query for more advanced scenarios.
+You can use the no-code editor to prototype quickly, and then optionally view or customize the generated SQL query for more advanced scenarios.