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Author: lootle1

learn-pr/azure/intro-to-azure-data-explorer/includes/1-introduction.md

@@ -1,4 +1,4 @@
-Daily operations and interactions with customers create a constant flow of data. This world of big data is growing steadily, and so is the need to store, process, and analyze the data in a timely and cost-efficient way.  Big data requires large amounts of scalable storage space. Because huge volumes of data flow in at high velocity from various sources, the ability to identify and respond to meaningful events is key. Additionally, data is generated in various formats like structured and semi-structured data and free text, as well as images and videos. In order to find correlations between these different data flows, businesses invest significant time and money into parsing, processing, and storing this data. A robust end-to-end data analytics system that can manage your huge, complex data and run advanced analytics is essential to make data-driven business decisions.  What tool can help you manage this vast array of data types, work flows, and visualizations?
+Daily operations and interactions with customers create a constant flow of data. This world of big data is growing steadily, and so is the need to store, process, and analyze the data in a timely and cost-efficient way. Big data requires large amounts of scalable storage space. Because huge volumes of data flow in at high velocity from various sources, the ability to identify and respond to meaningful events is key. Additionally, data is generated in various formats like structured and semi-structured data and free text, as well as images and videos. In order to find correlations between these different data flows, businesses invest significant time and money into parsing, processing, and storing this data. A robust end-to-end data analytics system that can manage your huge, complex data and run advanced analytics is essential to make data-driven business decisions. What tool can help you manage this vast array of data types, work flows, and visualizations?
 
 > [!VIDEO https://learn-video.azurefd.net/vod/player?id=02355c8a-a1f6-4740-ac9a-8d5c876e7ea7]
 

learn-pr/azure/intro-to-azure-data-explorer/includes/2-what-is-azure-data-explorer.md

@@ -34,7 +34,7 @@ Azure Data explorer uses the Kusto Query Language (KQL), an open-source language
 
 ### Advanced analytics
 
-Azure Data Explorer has a large set of functions for time series analysis. Functions includes adding and subtracting time series, filtering, regression, seasonality detection, geospatial analysis, anomaly detection, scanning, and forecasting. Time series functions are optimized for processing thousands of time series in seconds. Pattern detection is made easy with cluster plugins that can diagnose anomalies and do root cause analysis. You can also extend Azure Data Explorer capabilities by embedding python code in KQL queries.
+Azure Data Explorer has a large set of functions for time series analysis. Functions include adding and subtracting time series, filtering, regression, seasonality detection, geospatial analysis, anomaly detection, scanning, and forecasting. Time series functions are optimized for processing thousands of time series in seconds. Pattern detection is made easy with cluster plugins that can diagnose anomalies and do root cause analysis. You can also extend Azure Data Explorer capabilities by embedding python code in KQL queries.
 
 ### Easy-to-use wizard
 

learn-pr/azure/intro-to-azure-data-explorer/includes/3-how-azure-data-explorer-works.md

@@ -41,7 +41,7 @@ Azure Data Explorer uses the proprietary Kusto Query Language (KQL) to analyze d
 
 ### How does the Kusto Query Language work?
 
-Kusto Query Language is an expressive, intuitive, and highly productive query language. It offers a smooth transition from simple one-liners to complex data processing scripts, and supports querying structured, semi-structured, and unstructured (text search) data. There's a wide variety of query language operators and functions (aggregation, filtering, time series functions, geospatial functions, joins, unions, and more) in the language. KQL supports cross-cluster and cross-database queries, and it's feature rich from a parsing (json, XML etc.) perspective. In addition, the language natively supports advanced analytics.
+Kusto Query Language is an expressive, intuitive, and highly productive query language. It offers a smooth transition from simple one-liners to complex data processing scripts, and supports querying structured, semi-structured, and unstructured (text search) data. There's a wide variety of query language operators and functions (aggregation, filtering, time series functions, geospatial functions, joins, unions, and more) in the language. KQL supports cross-cluster and cross-database queries, and it's feature rich from a parsing (json, XML, etc.) perspective. In addition, the language natively supports advanced analytics.
 
 ### How can I display my query results?