Merge pull request #32909 from nschonni/chore--Remove-link-locale

chore: Remove link locale

Author: chbain

articles/cognitive-services/Anomaly-Detector/tutorials/anomaly-detection-streaming-databricks.md

@@ -14,7 +14,7 @@ ms.author: aahi
 
 # Tutorial: Anomaly detection on streaming data using Azure Databricks
 
-[Azure Databricks](https://azure.microsoft.com/en-us/services/databricks/) is a fast, easy, and collaborative Apache Spark–based analytics service. The Anomaly Detector API, part of Azure Cognitive Services, provides a way of monitoring your time series data. Use this tutorial to run anomaly detection on a stream of data in near real-time using Azure Databricks. You'll ingest twitter data using Azure Event Hubs, and import them into Azure Databricks using the Spark Event Hubs connector. Afterwards, you'll use the API to detect anomalies on the streamed data. 
+[Azure Databricks](https://azure.microsoft.com/services/databricks/) is a fast, easy, and collaborative Apache Spark–based analytics service. The Anomaly Detector API, part of Azure Cognitive Services, provides a way of monitoring your time series data. Use this tutorial to run anomaly detection on a stream of data in near real-time using Azure Databricks. You'll ingest twitter data using Azure Event Hubs, and import them into Azure Databricks using the Spark Event Hubs connector. Afterwards, you'll use the API to detect anomalies on the streamed data. 
 
 The following illustration shows the application flow: