Merge pull request #106970 from TimShererWithAquent/us1604855a

Add description for SEO.

Author: v-shils

articles/azure-monitor/app/custom-data-correlation.md

@@ -1,6 +1,6 @@
 ---
 title: Azure Application Insights | Microsoft Docs
-description: 
+description: Correlate data from Application Insights to other datasets, such as data enrichment or lookup tables, non-Application Insights data sources, and custom data.
 ms.topic: conceptual
 author: eternovsky
 ms.author: evternov
@@ -11,7 +11,7 @@ ms.reviewer: mbullwin
 
 # Correlating Application Insights data with custom data sources
 
-Application Insights collects several different data types: exceptions, traces, page views, and others. While this is often sufficient to investigate your application’s performance, reliability, and usage, there are cases when it is useful to correlate the data stored in Application Insights to other completely custom datasets.
+Application Insights collects several different data types: exceptions, traces, page views, and others. While this is often sufficient to investigate your application's performance, reliability, and usage, there are cases when it is useful to correlate the data stored in Application Insights to other completely custom datasets.
 
 Some situations where you might want custom data include:
 
@@ -21,17 +21,17 @@ Some situations where you might want custom data include:
 
 ## How to correlate custom data with Application Insights data 
 
-Since Application Insights is backed by the powerful Azure Monitor log platform, we are able to use the full power of Azure Monitor to ingest the data. Then, we will write queries using the “join” operator that will correlate this custom data with the data available to us in Azure Monitor logs. 
+Since Application Insights is backed by the powerful Azure Monitor log platform, we are able to use the full power of Azure Monitor to ingest the data. Then, we will write queries using the "join" operator that will correlate this custom data with the data available to us in Azure Monitor logs. 
 
 ## Ingesting data
 
 In this section, we will review how to get your data into Azure Monitor logs.
 
-If you don’t already have one, provision a new Log Analytics workspace by following [these instructions](../learn/quick-collect-azurevm.md) through and including the “create a workspace” step.
+If you don't already have one, provision a new Log Analytics workspace by following [these instructions](../learn/quick-collect-azurevm.md) through and including the "create a workspace" step.
 
 To start sending log data into Azure Monitor. Several options exist:
 
-- For a synchronous mechanism, you can either directly call the [data collector API](https://docs.microsoft.com/azure/log-analytics/log-analytics-data-collector-api) or use our Logic App connector – simply look for “Azure Log Analytics” and pick the “Send Data” option:
+- For a synchronous mechanism, you can either directly call the [data collector API](https://docs.microsoft.com/azure/log-analytics/log-analytics-data-collector-api) or use our Logic App connector – simply look for "Azure Log Analytics" and pick the "Send Data" option:
 
   ![Screenshot choose and action](./media/custom-data-correlation/01-logic-app-connector.png)  
 
@@ -41,7 +41,7 @@ To start sending log data into Azure Monitor. Several options exist:
 
 Application Insights is based on the Azure Monitor log platform. We can therefore use [cross-resource joins](https://docs.microsoft.com/azure/log-analytics/log-analytics-cross-workspace-search) to correlate any data we ingested into Azure Monitor with our Application Insights data.
 
-For example, we can ingest our lab inventory and locations into a table called “LabLocations_CL” in a Log Analytics workspace called “myLA”. If we then wanted to review our requests tracked in Application Insights app called “myAI” and correlate the machine names that served the requests to the locations of these machines stored in the previously mentioned custom table, we can run the following query from either the Application Insights or Azure Monitor context:
+For example, we can ingest our lab inventory and locations into a table called "LabLocations_CL" in a Log Analytics workspace called "myLA". If we then wanted to review our requests tracked in Application Insights app called "myAI" and correlate the machine names that served the requests to the locations of these machines stored in the previously mentioned custom table, we can run the following query from either the Application Insights or Azure Monitor context:
 
 ```
 app('myAI').requests