see to read

Author: KingdomOfEnds

articles/time-series-insights/how-to-connect-power-bi.md

@@ -135,12 +135,12 @@ As an overview:
 1. Modify the JSON payload as desired.
 1. Select **Done** and then **Close & Apply** within the **Power Query Editor Window**.
 
-You should see the desired changes applied.  
+You should read the desired changes applied.  
 
 ## Next Steps
 
 * Read about [Power BI connector concepts](https://docs.microsoft.com/power-bi/desktop-query-overview) for Azure Time Series Insights.
 
 * Learn more about [Power BI desktop](https://docs.microsoft.com/power-bi/desktop-query-overview).
 
-* See [Time Series Insights GA Explorer](https://docs.microsoft.com/azure/time-series-insights/time-series-quickstart) and [Time Series Insights Preview Explorer](https://docs.microsoft.com/azure/time-series-insights/time-series-insights-update-quickstart).
+* Read [Time Series Insights GA Explorer](https://docs.microsoft.com/azure/time-series-insights/time-series-quickstart) and [Time Series Insights Preview Explorer](https://docs.microsoft.com/azure/time-series-insights/time-series-insights-update-quickstart).

articles/time-series-insights/how-to-shape-query-json.md

@@ -47,7 +47,7 @@ The following guidance helps to ensure the best possible query performance:
 
 ## Example overview
 
-The following two examples demonstrate how to send events to highlight the previous recommendations. Following each example, you can see how the recommendations were applied.
+The following two examples demonstrate how to send events to highlight the previous recommendations. Following each example, you can read how the recommendations were applied.
 
 The examples are based on a scenario where multiple devices send measurements or signals. Measurements or signals can be Flow Rate, Engine Oil Pressure, Temperature, and Humidity. In the first example, there are a few measurements across all devices. The second example has many devices, and each device sends many unique measurements.
 

articles/time-series-insights/time-series-insights-add-reference-data-set.md

@@ -69,7 +69,7 @@ Reference data is not joined retroactively. Thus, only current and future ingres
 
    [![Review reference data](media/add-reference-data-set/review-displayed-data-grid.png)](media/add-reference-data-set/review-displayed-data-grid.png#lightbox)
 
-1. Review each column to see the data type assumed, and change the data type if needed.  Select the data type symbol in the column heading: **#** for double (numerical data), **T|F** for boolean, or **Abc** for string.
+1. Review each column to read the data type assumed, and change the data type if needed.  Select the data type symbol in the column heading: **#** for double (numerical data), **T|F** for boolean, or **Abc** for string.
 
    [![Choose data types on the column headings.](media/add-reference-data-set/select-column-types.png)](media/add-reference-data-set/select-column-types.png#lightbox)
 
@@ -113,4 +113,4 @@ Reference data is not joined retroactively. Thus, only current and future ingres
 
 * [Manage reference data](time-series-insights-manage-reference-data-csharp.md) programmatically.
 
-* For the complete API reference, see [Reference Data API](https://docs.microsoft.com/rest/api/time-series-insights/ga-reference-data-api) document.
+* For the complete API reference, read [Reference Data API](https://docs.microsoft.com/rest/api/time-series-insights/ga-reference-data-api) document.

articles/time-series-insights/time-series-insights-authentication-and-authorization.md

@@ -82,7 +82,7 @@ Per **step 3**, separating your application's and your user credentials allows y
 
    1. Use the **Application ID** and **Client Secret** (Application Key) from the Azure Active Directory app registration section to acquire the token on behalf of the application.
 
-   1. In C#, the following code can acquire the token on behalf of the application. For a complete sample, see [Query data using C#](time-series-insights-query-data-csharp.md).
+   1. In C#, the following code can acquire the token on behalf of the application. For a complete sample, read [Query data using C#](time-series-insights-query-data-csharp.md).
 
         [!code-csharp[csharpquery-example](~/samples-tsi/csharp-tsi-ga-sample/Program.cs?range=170-199)]
 
@@ -102,7 +102,7 @@ This section describes common HTTP request headers and parameters used to make q
 To perform authenticated queries against the [Time Series Insights REST APIs](https://docs.microsoft.com/rest/api/time-series-insights/), a valid OAuth 2.0 bearer token must be passed in the [Authorization header](/rest/api/apimanagement/2019-01-01/authorizationserver/createorupdate) using a REST client of your choice (Postman, JavaScript, C#). 
 
 > [!TIP]
-> See the hosted Azure Time Series Insights [client SDK sample visualization](https://tsiclientsample.azurewebsites.net/) to see how to authenticate with the Time Series Insights APIs programmatically using the [JavaScript Client SDK](https://github.com/microsoft/tsiclient/blob/master/docs/API.md) along with charts and graphs.
+> Read the hosted Azure Time Series Insights [client SDK sample visualization](https://tsiclientsample.azurewebsites.net/) to read how to authenticate with the Time Series Insights APIs programmatically using the [JavaScript Client SDK](https://github.com/microsoft/tsiclient/blob/master/docs/API.md) along with charts and graphs.
 
 ### HTTP headers
 
@@ -156,10 +156,10 @@ Optional URL query string parameters include setting a timeout for HTTP request
 
 ## Next steps
 
-- For sample code that calls the GA Time Series Insights API, see [Query data using C#](./time-series-insights-query-data-csharp.md).
+- For sample code that calls the GA Time Series Insights API, read [Query data using C#](./time-series-insights-query-data-csharp.md).
 
-- For Preview Time Series Insights API code samples, see [Query Preview data using C#](./time-series-insights-update-query-data-csharp.md).
+- For Preview Time Series Insights API code samples, read [Query Preview data using C#](./time-series-insights-update-query-data-csharp.md).
 
-- For API reference information, see the [Query API reference](https://docs.microsoft.com/rest/api/time-series-insights/ga-query-api) documentation.
+- For API reference information, read the [Query API reference](https://docs.microsoft.com/rest/api/time-series-insights/ga-query-api) documentation.
 
 - Learn how to [create a service principal](../active-directory/develop/howto-create-service-principal-portal.md).

articles/time-series-insights/time-series-insights-concepts-retention.md

@@ -39,7 +39,7 @@ Both data retention policies are described in greater detail below.
 ## Purge old data
 
 - **Purge old data** is the default setting for Azure Time Series Insights environments.  
-- **Purge old data** is preferred when users want to always see their *most recent data* in their Time Series Insights environment.
+- **Purge old data** is preferred when users want to always read their *most recent data* in their Time Series Insights environment.
 - The **Purge old data** setting *purges* data once the environment’s limits (retention time, size, or count, whichever comes first) are reached. Retention is set to 30 days by default.
 - The oldest ingested data is purged first (the "First In First Out" approach).
 

articles/time-series-insights/time-series-insights-customer-data-requests.md

@@ -29,9 +29,9 @@ A tenant administrator can delete customer data using the Azure portal.
 
 [!INCLUDE [gdpr-dsr-and-stp-note](../../includes/gdpr-dsr-and-stp-note.md)]
 
-However, before you delete customer data through the portal, you should remove the user's access policies from the Time Series Insights environment within the Azure portal. For more information, see [Grant data access to a Time Series Insights environment using Azure portal](time-series-insights-data-access.md).
+However, before you delete customer data through the portal, you should remove the user's access policies from the Time Series Insights environment within the Azure portal. For more information, read [Grant data access to a Time Series Insights environment using Azure portal](time-series-insights-data-access.md).
 
-You can also perform delete operations on access policies using the REST API. For more information, see [Access Policies - Delete](https://docs.microsoft.com/rest/api/time-series-insights/management/accesspolicies/delete).
+You can also perform delete operations on access policies using the REST API. For more information, read [Access Policies - Delete](https://docs.microsoft.com/rest/api/time-series-insights/management/accesspolicies/delete).
 
 Time Series Insights is integrated with the Policy blade in the Azure portal. Both Time Series Insights and the Policy blade enable you to view, export, and delete user data stored within the service. Any delete action taken within the Policy blade of the Azure portal results in the deletion of user data within Time Series Insights. For example, if a user has a saved personal query, that query is permanently deleted from the Time Series Insights explorer. If the user has a saved shared query, the query persists, but the user information is permanently deleted. The following note contains instructions on how to accomplish these tasks.
 
@@ -41,9 +41,9 @@ Similarly to deleting data, a tenant administrator can view and export data stor
 
 [!INCLUDE [gdpr-dsr-and-stp-note](../../includes/gdpr-dsr-and-stp-note.md)]
 
-If you are a tenant administrator, you can view data access policies within the Time Series Insights environment in the Azure portal. For more information, see [Grant data access to a Time Series Insights environment using Azure portal](time-series-insights-data-access.md).
+If you are a tenant administrator, you can view data access policies within the Time Series Insights environment in the Azure portal. For more information, read [Grant data access to a Time Series Insights environment using Azure portal](time-series-insights-data-access.md).
 
-It is also possible to perform export operations on access policies using the "list by environment" operation in the provided REST API. For more information, see [Access Policies - List By Environment](https://docs.microsoft.com/rest/api/time-series-insights/management/accesspolicies/listbyenvironment).
+It is also possible to perform export operations on access policies using the "list by environment" operation in the provided REST API. For more information, read [Access Policies - List By Environment](https://docs.microsoft.com/rest/api/time-series-insights/management/accesspolicies/listbyenvironment).
 
 ## To delete data stored within Time Series Insights
 
@@ -53,13 +53,13 @@ Personal data might make its way into Time Series Insights storage, a different
 
 To view and export data stored within Time Series Insights, you need to search for that data. You can use the Time Series Insights explorer or Time Series Insights query APIs to view and export data. To view and export data using the Time Series Insights explorer, first search to find the user data in question. After searching, right-click on the chart and select **Explore events**. The events grid appears and presents options to export the data as CSV and JSON.
 
-For more information, see [Azure Time Series Insights explorer](time-series-insights-explorer.md).
+For more information, read [Azure Time Series Insights explorer](time-series-insights-explorer.md).
 
 **Delete data**
 
 Currently, Time Series Insights does not support granular deletion of data. However, Time Series Insights provides the ability to remove customer data stored within Time Series Insights by configuring retention policies. You can adjust the retention period of the entire Time Series Insights environment to any number of days to support your deletion requirements.
 
-For more information, see [Configuring retention in Time Series Insights](time-series-insights-how-to-configure-retention.md).
+For more information, read [Configuring retention in Time Series Insights](time-series-insights-how-to-configure-retention.md).
 
 ## Next steps
 

articles/time-series-insights/time-series-insights-data-access.md

@@ -108,7 +108,7 @@ Follow these steps to grant guest access to a Time Series Insights environment t
 
 1. The guest can now access the shared environment using the environment URL provided by the administrator. They can enter that URL into their web browser for immediate access.
 
-1. The guest user will see the administrator's tenant by selecting their profile icon in the upper-right corner of the Time Series explorer.
+1. The guest user will read the administrator's tenant by selecting their profile icon in the upper-right corner of the Time Series explorer.
 
     [![Avatar selection on insights.azure.com](media/data-access/data-access-select-tenant-and-instance.png)](media/data-access/data-access-select-tenant-and-instance.png#lightbox)
 

articles/time-series-insights/time-series-insights-diagnose-and-solve-problems.md

@@ -29,7 +29,7 @@ No data in the [Azure Time Series Insights explorer](https://insights.timeseries
 
 ### Cause A: event source data isn't in JSON format
 
-Azure Time Series Insights only supports JSON data. For JSON samples, see [Supported JSON shapes](./how-to-shape-query-json.md).
+Azure Time Series Insights only supports JSON data. For JSON samples, read [Supported JSON shapes](./how-to-shape-query-json.md).
 
 ### Cause B: the event source key is missing a required permission
 
@@ -64,7 +64,7 @@ If you have old events in your event source, you can approach throttling in one
 - Change your event source's retention limits to help remove old events that you don't want to show up in Time Series Insights.
 - Provision a larger environment size (number of units) to increase the throughput of old events. Using the preceding example, if you increase the same S1 environment to five units for one day, the environment should catch up within a day. If your steady-state event production is 1 million or fewer events per day, you can reduce the capacity of the event to one unit after it catches up.
 
-The throttling limit is enforced based on the environment's SKU type and capacity. All event sources in the environment share this capacity. If the event source for your IoT hub or event hub pushes data beyond the enforced limits, you see throttling and a lag.
+The throttling limit is enforced based on the environment's SKU type and capacity. All event sources in the environment share this capacity. If the event source for your IoT hub or event hub pushes data beyond the enforced limits, you will experience throttling and a lag.
 
 The following figure shows a Time Series Insights environment that has an SKU of S1 and a capacity of 3. It can ingress 3 million events per day.
 
@@ -77,11 +77,11 @@ As an example, assume an environment ingests messages from an event hub. The dai
 
 An S1 SKU environment that has a capacity of 3 can ingress only 2,100 events every minute (1 million events per day = 700 events per minute at three units = 2,100 events per minute). 
 
-For a high-level understanding of how flattening logic works, see [Supported JSON shapes](./how-to-shape-query-json.md).
+For a high-level understanding of how flattening logic works, read [Supported JSON shapes](./how-to-shape-query-json.md).
 
 #### Recommended resolutions for excessive throttling
 
-To fix the lag, increase the SKU capacity of your environment. For more information, see [Scale your Time Series Insights environment](time-series-insights-how-to-scale-your-environment.md).
+To fix the lag, increase the SKU capacity of your environment. For more information, read [Scale your Time Series Insights environment](time-series-insights-how-to-scale-your-environment.md).
 
 ### Cause B: initial ingestion of historical data slows ingress
 
@@ -104,9 +104,9 @@ Ensure that the timestamp property name and value conform to the following rules
 
 The easiest way to ensure that your timestamp property name is captured and working properly is to use the Time Series Insights explorer. In the Time Series Insights explorer, using the chart, select a period of time after you entered the timestamp property name. Right-click the selection, and then select the **Explore events** option.
 
-The first column header should be your timestamp property name. Next to the word **Timestamp**, you should see **($ts)**.
+The first column header should be your timestamp property name. Next to the word **Timestamp**, **($ts)** will be displayed.
 
-You should not see the following values:
+The following values will not be displayed:
 
 - *(abc)*: Indicates that Time Series Insights is reading the data values as strings.
 - *Calendar icon*: Indicates that Time Series Insights is reading the data value as *datetime*.

articles/time-series-insights/time-series-insights-environment-mitigate-latency.md

@@ -69,11 +69,11 @@ Alerts can help you to help diagnose and mitigate latency issues caused by your
 
 ## Throttling and ingress management
 
-* If you are being throttled, you will see a value for the *Ingress Received Message Time Lag*, informing you about how many seconds behind your TIme Series Insights environment are from the actual time the message hits the event source (excluding indexing time of appx. 30-60 seconds).  
+* If you are being throttled, you will read a value for the *Ingress Received Message Time Lag*, informing you about how many seconds behind your TIme Series Insights environment are from the actual time the message hits the event source (excluding indexing time of appx. 30-60 seconds).  
 
   *Ingress Received Message Count Lag* should also have a value, allowing you to determine how many messages behind you are.  The easiest way to get caught up is to increase your environment's capacity to a size that will enable you to overcome the difference.  
 
-  For example, if you see that your S1 environment is demonstrating lag of 5,000,000 messages, you might increase the size of your environment to six units for around a day to get caught up.  You could increase even further to catch up faster. The catch-up period is a common occurrence when initially provisioning an environment, particularly when you connect it to an event source that already has events in it or when you bulk upload lots of historical data.
+  For example, if you read that your S1 environment is demonstrating lag of 5,000,000 messages, you might increase the size of your environment to six units for around a day to get caught up.  You could increase even further to catch up faster. The catch-up period is a common occurrence when initially provisioning an environment, particularly when you connect it to an event source that already has events in it or when you bulk upload lots of historical data.
 
 * Another technique is to set an **Ingress Stored Events** alert >= a threshold slightly below your total environment capacity for a period of 2 hours.  This alert can help you understand if you are constantly at capacity, which indicates a high likelihood of latency. 
 
@@ -85,7 +85,7 @@ Alerts can help you to help diagnose and mitigate latency issues caused by your
 
 To reduce throttling or experiencing latency, the best way to correct it is to increase your environment's capacity.
 
-You can avoid latency and throttling by properly configuring your environment for the amount of data you want to analyze. For more information about how to add capacity to your environment, see [Scale your environment](time-series-insights-how-to-scale-your-environment.md).
+You can avoid latency and throttling by properly configuring your environment for the amount of data you want to analyze. For more information about how to add capacity to your environment, read [Scale your environment](time-series-insights-how-to-scale-your-environment.md).
 
 ## Next steps