Merge pull request #96428 from aahill/ad-qs-update

[CogSvcs] UX testing updates

Author: Jak-MS

articles/cognitive-services/Anomaly-Detector/includes/quickstart-cleanup-next-steps.md

@@ -0,0 +1,31 @@
+---
+title: Next steps for Anomaly Detector quickstarts
+titleSuffix: Azure Cognitive Services
+services: cognitive-services
+author: aahill
+manager: nitinme
+ms.service: cognitive-services
+ms.topic: include 
+ms.date: 11/19/2019
+ms.author: aahi
+---
+
+## Clean up resources
+
+If you want to clean up and remove a Cognitive Services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with the resource group.
+
+* [Portal](../../cognitive-services-apis-create-account.md#clean-up-resources)
+* [Azure CLI](../../cognitive-services-apis-create-account-cli.md#clean-up-resources)
+
+## Next steps
+
+Concepts:
+
+* [What is the Anomaly Detector API?](../overview.md)
+* [Anomaly detection methods](../how-to/identify-anomalies.md)
+* [Best practices when using the Anomaly Detector API.](../concepts/anomaly-detection-best-practices.md) 
+
+Tutorials:
+
+* [Visualize anomalies as a batch using Power BI](../tutorials/batch-anomaly-detection-powerbi.md)
+* [Anomaly detection on streaming data using Azure Databricks](../tutorials/anomaly-detection-streaming-databricks.md)

articles/cognitive-services/Anomaly-Detector/quickstarts/detect-data-anomalies-csharp-sdk.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
 ms.topic: quickstart
-ms.date: 10/15/2019
+ms.date: 11/19/2019
 ms.author: aahi
 ---
 
@@ -21,12 +21,13 @@ Use the Anomaly Detector client library for .NET to:
 * Detect anomalies throughout your time series dataset, as a batch request
 * Detect the anomaly status of the latest data point in your time series
 
-[Library reference documentation](https://docs.microsoft.com/dotnet/api/Microsoft.Azure.CognitiveServices.AnomalyDetector?view=azure-dotnet-preview) | [Library source code](https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/cognitiveservices/AnomalyDetector) | [Package (NuGet)](https://www.nuget.org/packages/Microsoft.Azure.CognitiveServices.AnomalyDetector/) | [Code samples](https://github.com/Azure-Samples/anomalydetector)
+[Library reference documentation](https://docs.microsoft.com/dotnet/api/Microsoft.Azure.CognitiveServices.AnomalyDetector?view=azure-dotnet-preview) | [Library source code](https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/cognitiveservices/AnomalyDetector) | [Package (NuGet)](https://www.nuget.org/packages/Microsoft.Azure.CognitiveServices.AnomalyDetector/) | [Find the code on GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/csharp-sdk-sample.cs)
 
 ## Prerequisites
 
 * Azure subscription - [Create one for free](https://azure.microsoft.com/free/)
 * The current version of [.NET Core](https://dotnet.microsoft.com/download/dotnet-core)
+* An Anomaly detector key and endpoint
 
 ## Setting up
 
@@ -132,18 +133,4 @@ Run the application with the `dotnet run` command from your application director
 dotnet run
 ```
 
-## Clean up resources
-
-If you want to clean up and remove a Cognitive Services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with the resource group.
-
-* [Portal](../../cognitive-services-apis-create-account.md#clean-up-resources)
-* [Azure CLI](../../cognitive-services-apis-create-account-cli.md#clean-up-resources)
-
-## Next steps
-
-> [!div class="nextstepaction"]
->[Streaming anomaly detection with Azure Databricks](../tutorials/anomaly-detection-streaming-databricks.md)
-
-* What is the [Anomaly Detector API?](../overview.md)
-* [Best practices](../concepts/anomaly-detection-best-practices.md) when using the Anomaly Detector API.
-* The source code for this sample can be found on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/csharp-sdk-sample.cs).
+[!INCLUDE [anomaly-detector-next-steps](../includes/quickstart-cleanup-next-steps.md)]

articles/cognitive-services/Anomaly-Detector/quickstarts/detect-data-anomalies-csharp.md

@@ -8,25 +8,25 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
 ms.topic: quickstart
-ms.date: 10/14/2019
+ms.date: 11/19/2019
 ms.author: aahi
 ---
 
 # Quickstart: Detect anomalies in your time series data using the Anomaly Detector REST API and C# 
 
 Use this quickstart to start using the Anomaly Detector API's two detection modes to detect anomalies in your time series data. This C# application sends two API requests containing JSON-formatted time series data, and gets the responses.
 
-| API request                                        | Application output                                                                                                                         |
-|----------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|
+| API request                                        | Application output                                                                                                                                         |
+|----------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | Detect anomalies as a batch                        | The JSON response containing the anomaly status (and other data) for each data point in the time series data, and the positions of any detected anomalies. |
-| Detect the anomaly status of the latest data point | The JSON response containing the anomaly status (and other data) for the latest data point in the time series data.                                                                                                                                         |
+| Detect the anomaly status of the latest data point | The JSON response containing the anomaly status (and other data) for the latest data point in the time series data.                                        |
 
- While this application is written in C#, the API is a RESTful web service compatible with most programming languages.
+ While this application is written in C#, the API is a RESTful web service compatible with most programming languages. You can find the source code for this quickstart on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/csharp-detect-anomalies.cs).
 
 ## Prerequisites
 
 - Any edition of [Visual Studio 2017 or later](https://visualstudio.microsoft.com/downloads/),
-
+- An Anomaly detector key and endpoint
 - The [Json.NET](https://www.newtonsoft.com/json) framework, available as a NuGet package. To install Newtonsoft.Json as a NuGet package in Visual Studio:
 
     1. Right click your project in **Solution Explorer**.
@@ -50,11 +50,11 @@ Use this quickstart to start using the Anomaly Detector API's two detection mode
 
 2. Create variables for your subscription key and your endpoint. Below are the URIs you can use for anomaly detection. These will be appended to your service endpoint later to create the API request URLs.
 
-    |Detection method  |URI  |
-    |---------|---------|
-    |Batch detection    | `/anomalydetector/v1.0/timeseries/entire/detect`        |
-    |Detection on the latest data point     | `/anomalydetector/v1.0/timeseries/last/detect`        |
-    
+    | Detection method                   | URI                                              |
+    |------------------------------------|--------------------------------------------------|
+    | Batch detection                    | `/anomalydetector/v1.0/timeseries/entire/detect` |
+    | Detection on the latest data point | `/anomalydetector/v1.0/timeseries/last/detect`   |
+        
     [!code-csharp[initial variables for endpoint, key and data file](~/samples-anomaly-detector/quickstarts/csharp-detect-anomalies.cs?name=vars)]
 
 ## Create a function to send requests
@@ -86,8 +86,8 @@ Use this quickstart to start using the Anomaly Detector API's two detection mode
 
 2. Deserialize the JSON object, and write it to the console.
 
-[!code-csharp[Detect anomalies latest](~/samples-anomaly-detector/quickstarts/csharp-detect-anomalies.cs?name=detectAnomaliesLatest)]
-
+    [!code-csharp[Detect anomalies latest](~/samples-anomaly-detector/quickstarts/csharp-detect-anomalies.cs?name=detectAnomaliesLatest)]
+ 
 ## Load your time series data and send the request
 
 1. In the main method of your application, load your JSON time series data with `File.ReadAllText()`. 
@@ -102,11 +102,4 @@ A successful response is returned in JSON format. Click the links below to view
 * [Example batch detection response](https://github.com/Azure-Samples/anomalydetector/blob/master/example-data/batch-response.json)
 * [Example latest point detection response](https://github.com/Azure-Samples/anomalydetector/blob/master/example-data/latest-point-response.json)
 
-## Next steps
-
-> [!div class="nextstepaction"]
->[Streaming anomaly detection with Azure Databricks](../tutorials/anomaly-detection-streaming-databricks.md)
-
-* What is the [Anomaly Detector API?](../overview.md)
-* [Best practices](../concepts/anomaly-detection-best-practices.md) when using the Anomaly Detector API.
-* The source code for this sample can be found on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/csharp-sdk-sample.cs).
+[!INCLUDE [anomaly-detector-next-steps](../includes/quickstart-cleanup-next-steps.md)]

articles/cognitive-services/Anomaly-Detector/quickstarts/detect-data-anomalies-java.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
 ms.topic: quickstart
-ms.date: 07/26/2019
+ms.date: 11/19/2019
 ms.author: aahi
 ---
 
@@ -21,12 +21,12 @@ Use this quickstart to start using the Anomaly Detector API's two detection mode
 | Detect anomalies as a batch                        | The JSON response containing the anomaly status (and other data) for each data point in the time series data, and the positions of any detected anomalies. |
 | Detect the anomaly status of the latest data point | The JSON response containing the anomaly status (and other data) for the latest data point in the time series data.                                                                                                                                         |
 
- While this application is written in Java, the API is a RESTful web service compatible with most programming languages.
+ While this application is written in Java, the API is a RESTful web service compatible with most programming languages. You can find the source code for this quickstart on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/java-detect-anomalies.java).
 
 ## Prerequisites
 
 - The [Java™ Development Kit(JDK) 7](https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html) or later.
-
+- An Anomaly detector key and endpoint
 - Import these libraries from the Maven Repository
     - [JSON in Java](https://mvnrepository.com/artifact/org.json/json) package
     - [Apache HttpClient](https://mvnrepository.com/artifact/org.apache.httpcomponents/httpclient) package
@@ -66,7 +66,7 @@ Use this quickstart to start using the Anomaly Detector API's two detection mode
 
 6. Create an `HttpEntity` object to store the response content. Get the content with `getEntity()`. If the response isn't empty, return it.
 
-[!code-java[API request method](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=request)]
+    [!code-java[API request method](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=request)]
 
 ## Detect anomalies as a batch
 
@@ -76,11 +76,11 @@ Use this quickstart to start using the Anomaly Detector API's two detection mode
 
 3. Otherwise, find the positions of anomalies in the data set. The response's `isAnomaly` field contains a boolean value relating to whether a given data point is an anomaly. Get the JSON array, and iterate through it, printing the index of any `true` values. These values correspond to the index of anomalous data points, if any were found.
 
-[!code-java[Method for batch detection](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=detectBatch)]
+    [!code-java[Method for batch detection](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=detectBatch)]
 
 ## Detect the anomaly status of the latest data point
 
-* Create a method called `detectAnomaliesLatest()` to detect the anomaly status of the last data point in the data set. Call the `sendRequest()` method created above with your endpoint, url, subscription key, and json data. Get the result, and print it to the console.
+Create a method called `detectAnomaliesLatest()` to detect the anomaly status of the last data point in the data set. Call the `sendRequest()` method created above with your endpoint, url, subscription key, and json data. Get the result, and print it to the console.
 
 [!code-java[Latest point detection method](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=detectLatest)]
 
@@ -90,19 +90,12 @@ Use this quickstart to start using the Anomaly Detector API's two detection mode
 
 2. Call the two anomaly detection functions created above.
 
-[!code-java[Main method](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=main)]
+    [!code-java[Main method](~/samples-anomaly-detector/quickstarts/java-detect-anomalies.java?name=main)]
 
 ### Example response
 
 A successful response is returned in JSON format. Click the links below to view the JSON response on GitHub:
 * [Example batch detection response](https://github.com/Azure-Samples/anomalydetector/blob/master/example-data/batch-response.json)
 * [Example latest point detection response](https://github.com/Azure-Samples/anomalydetector/blob/master/example-data/latest-point-response.json)
 
-## Next steps
-
-> [!div class="nextstepaction"]
->[Streaming anomaly detection with Azure Databricks](../tutorials/anomaly-detection-streaming-databricks.md)
-
-* What is the [Anomaly Detector API?](../overview.md)
-* [Best practices](../concepts/anomaly-detection-best-practices.md) when using the Anomaly Detector API.
-* The source code for this sample can be found on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/csharp-sdk-sample.cs).
+[!INCLUDE [anomaly-detector-next-steps](../includes/quickstart-cleanup-next-steps.md)]

articles/cognitive-services/Anomaly-Detector/quickstarts/detect-data-anomalies-nodejs-sdk.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
 ms.topic: quickstart
-ms.date: 09/17/2019
+ms.date: 11/19/2019
 ms.author: aahi
 ---
 
@@ -21,12 +21,13 @@ Use the Anomaly Detector client library for Node.js to:
 * Detect anomalies throughout your time series dataset, as a batch request
 * Detect the anomaly status of the latest data point in your time series
 
-[Reference documentation](https://docs.microsoft.com/javascript/api/@azure/cognitiveservices-anomalydetector/?view=azure-node-latest) | [Library source code](https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/cognitiveservices/AnomalyDetector) | [Package (npm)](https://www.npmjs.com/package/@azure/cognitiveservices-anomalydetector) | [Code samples](https://github.com/Azure-Samples/anomalydetector)
+[Reference documentation](https://docs.microsoft.com/javascript/api/@azure/cognitiveservices-anomalydetector/?view=azure-node-latest) | [Library source code](https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/cognitiveservices/AnomalyDetector) | [Package (npm)](https://www.npmjs.com/package/@azure/cognitiveservices-anomalydetector) | [Find the code on GitHub](https://github.com/Azure-Samples/cognitive-services-quickstart-code/tree/master/javascript/AnomalyDetector)
 
 ## Prerequisites
 
 * Azure subscription - [Create one for free](https://azure.microsoft.com/free/)
 * The current version of [Node.js](https://nodejs.org/)
+* An Anomaly detector key and endpoint
 
 ## Setting up
 
@@ -122,18 +123,4 @@ Run the application with the `node` command on your quickstart file.
 node index.js
 ```
 
-## Clean up resources
-
-If you want to clean up and remove a Cognitive Services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
-
-* [Portal](../../cognitive-services-apis-create-account.md#clean-up-resources)
-* [Azure CLI](../../cognitive-services-apis-create-account-cli.md#clean-up-resources)
-
-## Next steps
-
-> [!div class="nextstepaction"]
->[Streaming anomaly detection with Azure Databricks](../tutorials/anomaly-detection-streaming-databricks.md)
-
-* What is the [Anomaly Detector API?](../overview.md)
-* [Best practices](../concepts/anomaly-detection-best-practices.md) when using the Anomaly Detector API.
-* The source code for this sample can be found on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/csharp-sdk-sample.cs).
+[!INCLUDE [anomaly-detector-next-steps](../includes/quickstart-cleanup-next-steps.md)]

articles/cognitive-services/Anomaly-Detector/quickstarts/detect-data-anomalies-python-sdk.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
 ms.topic: quickstart
-ms.date: 10/15/2019
+ms.date: 11/19/2019
 ms.author: aahi
 ---
 
@@ -21,11 +21,12 @@ Use the Anomaly Detector client library for Python to:
 * Detect anomalies throughout your time series dataset, as a batch request
 * Detect the anomaly status of the latest data point in your time series
 
-[Library reference documentation](https://docs.microsoft.com/python/api/azure-cognitiveservices-anomalydetector/azure.cognitiveservices.anomalydetector?view=azure-python) | [Library source code](https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/cognitiveservices/azure-cognitiveservices-anomalydetector) | [Package (PyPi)](https://pypi.org/project/azure-cognitiveservices-anomalydetector/) | [Code samples](https://github.com/Azure-Samples/anomalydetector)
+[Library reference documentation](https://docs.microsoft.com/python/api/azure-cognitiveservices-anomalydetector/azure.cognitiveservices.anomalydetector?view=azure-python) | [Library source code](https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/cognitiveservices/azure-cognitiveservices-anomalydetector) | [Package (PyPi)](https://pypi.org/project/azure-cognitiveservices-anomalydetector/) | [Find the sample code on GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/python-sdk-sample.py)
 
 ## Prerequisites
 
 * Azure subscription - [Create one for free](https://azure.microsoft.com/free/)
+* An Anomaly detector key and endpoint
 * [Python 3.x](https://www.python.org/)
 * The [Pandas data analysis library](https://pandas.pydata.org/)
 
@@ -109,18 +110,4 @@ Call the Anomaly Detector API to determine if your latest data point is an anoma
 
 Run the application with the `python` command and your file name.
 
-## Clean up resources
-
-If you want to clean up and remove a Cognitive Services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with the resource group.
-
-* [Portal](../../cognitive-services-apis-create-account.md#clean-up-resources)
-* [Azure CLI](../../cognitive-services-apis-create-account-cli.md#clean-up-resources)
-
-## Next steps
-
-> [!div class="nextstepaction"]
->[Streaming anomaly detection with Azure Databricks](../tutorials/anomaly-detection-streaming-databricks.md)
-
-* What is the [Anomaly Detector API?](../overview.md)
-* [Best practices](../concepts/anomaly-detection-best-practices.md) when using the Anomaly Detector API.
-* The source code for this sample can be found on [GitHub](https://github.com/Azure-Samples/AnomalyDetector/blob/master/quickstarts/sdk/csharp-sdk-sample.cs).
+[!INCLUDE [anomaly-detector-next-steps](../includes/quickstart-cleanup-next-steps.md)]