Merge pull request #95966 from orspod/2019-11-ADF-intro

requested PR changes

Author: PRMerger7

articles/data-explorer/data-factory-integration.md

@@ -12,7 +12,7 @@ ms.date: 11/14/2019
 #Customer intent: I want to use Azure Data Factory to integrate with Azure Data Explorer.
 ---
 
-# Azure Data Explorer integration with Azure Data Factory
+# Integrate Azure Data Explorer with Azure Data Factory
 
 [Azure Data Factory](/azure/data-factory/) (ADF) is a cloud-based data integration service that allows you to integrate different data stores and perform activities on the data. ADF allows you to create data-driven workflows for orchestrating and automating data movement and data transformation. Azure Data Explorer is one of the [supported data stores](/azure/data-factory/copy-activity-overview#supported-data-stores-and-formats) in Azure Data Factory. 
 
@@ -36,21 +36,21 @@ In addition to the response size limit of 5,000 rows and 2 MB, the activity also
 ### Command activity
 
 The Command activity allows the execution of Azure Data Explorer [control commands](/azure/kusto/concepts/#control-commands). Unlike queries, the control commands can potentially modify data or metadata. Some of the control commands are targeted to ingest data into Azure Data Explorer, using commands such as `.ingest`or `.set-or-append`) or copy data from Azure Data Explorer to external data stores using commands such as `.export`.
-For a detailed walk-through of the command activity, see [use Azure Data Factory command activity to run Azure Data Explorer control commands](data-factory-command-activity.md).  Using a control command to copy data can, at times, be a faster and cheaper option than the Copy activity. To determine when to use the Command activity versus the Copy activity, see [select between Copy and Command activities when copying data](#select-between-copy-and-azure-data-explorer-command-activities-when-copying-data).
+For a detailed walk-through of the command activity, see [use Azure Data Factory command activity to run Azure Data Explorer control commands](data-factory-command-activity.md).  Using a control command to copy data can, at times, be a faster and cheaper option than the Copy activity. To determine when to use the Command activity versus the Copy activity, see [select between Copy and Command activities when copying data](#select-between-copy-and-azure-data-explorer-command-activities-when-copy-data).
 
 ### Copy in bulk from a database template
 
 The [Copy in bulk from a database to Azure Data Explorer by using the Azure Data Factory template](data-factory-template.md) is a predefined Azure Data Factory pipeline. The template is used to create many pipelines per database or per table for faster data copying. 
 
-## Select between Copy and Azure Data Explorer Command activities when copying data 
+## Select between Copy and Azure Data Explorer Command activities when copy data 
 
 This section will assist you in selecting the correct activity for your data copying needs.
 
 When copying data from or to Azure Data Explorer, there are two available options in Azure Data Factory:
 * Copy activity.
 * Azure Data Explorer Command activity, which executes one of the control commands that transfer data in Azure Data Explorer. 
 
-### Copying data from Azure Data Explorer
+### Copy data from Azure Data Explorer
 
 You can copy data from Azure Data Explorer using the copy activity or the [`.export`](/azure/kusto/management/data-export/) command. The `.export` command executes a query, and then exports the results of the query. 
 
@@ -115,7 +115,7 @@ This section addresses the use of copy activity where Azure Data Explorer is the
 | **Data processing complexity** | Latency varies according to source file format, column mapping, and compression.|
 | **The VM running your integration runtime** | <ul><li>For Azure copy, ADF VMs and machine SKUs can't be changed.</li><li> For on-prem to Azure copy, determine that the VM hosting your self-hosted IR is strong enough.</li></ul>|
 
-## Monitoring activity progress
+## Monitor activity progress
 
 * When monitoring the activity progress, the *Data written* property may be much larger than the *Data read* property
 because *Data read* is calculated according to the binary file size, while *Data written* is calculated according to the in-memory size, after data is de-serialized and decompressed.