Merge pull request #113212 from Virginia001/work01

Work01

Author: PRMerger9

articles/time-series-insights/time-series-insights-update-tsm.md

@@ -8,7 +8,7 @@ ms.workload: big-data
 ms.service: time-series-insights
 services: time-series-insights
 ms.topic: conceptual
-ms.date: 03/16/2020
+ms.date: 04/29/2020
 ms.custom: seodec18
 ---
 
@@ -17,7 +17,8 @@ ms.custom: seodec18
 This article describes Time Series Model, the capabilities, and how to start building and updating your own models in the Azure Time Series Insights Preview environment.
 
 > [!TIP]
->  * Go to the [Contoso Wind Farm demo](https://insights.timeseries.azure.com/preview/samples) environment for a live Time Series Model example.
+>
+> * Go to the [Contoso Wind Farm demo](https://insights.timeseries.azure.com/preview/samples) environment for a live Time Series Model example.
 > * Read about the [Azure Time Series Insights Preview explorer](time-series-insights-update-explorer.md) to learn how to navigate your Time Series Model UI.
 > * Learn [How to work with Time Series Model](time-series-insights-update-how-to-tsm.md) using the Time Series Insights web explorer.
 
@@ -46,9 +47,9 @@ These limitations revealed the importance of smart data aggregation and visualiz
 
 [![Time Series Model smart oven charting example](media/v2-update-tsm/time-series-model-smart-oven.png)](media/v2-update-tsm/time-series-model-smart-oven.png#lightbox)
 
-* Time Series Model plays a vital role in queries and navigation because it contextualizes data by allowing comparisons to be drawn across time ranges and between sensor and device kinds. (**A**) 
+* Time Series Model plays a vital role in queries and navigation because it contextualizes data by allowing comparisons to be drawn across time ranges and between sensor and device kinds. (**A**)
 * Data is further contextualized because data persisted in Time Series Model preserves time series query computations as variables and reuses them at query time.
-* Time Series Model organizes and aggregates data for improved visualization and management capabilities. (**B**) 
+* Time Series Model organizes and aggregates data for improved visualization and management capabilities. (**B**)
 
 ### Key capabilities
 
@@ -285,7 +286,7 @@ Time Series Insights types might have many variables that specify formula and co
 
 Each variable can be one of three *kinds*: *numeric*, *categorical*, and *aggregate*.
 
-* **Numeric** kinds work with continuous values. 
+* **Numeric** kinds work with continuous values.
 * **Categorical** kinds work with a defined set of discrete values.
 * **Aggregate** values combine multiple variables of a single kind (either all numeric or all categorical).
 

articles/time-series-insights/time-series-insights-update-use-cases.md

@@ -8,7 +8,7 @@ ms.workload: big-data
 ms.service: time-series-insights
 services: time-series-insights
 ms.topic: conceptual
-ms.date: 02/07/2020
+ms.date: 04/29/2020
 ms.custom: seodec18
 ---
 
@@ -37,13 +37,13 @@ Instantly explore and analyze billions of events to spot anomalies and discover
 
 Most customers agree that the minimal amount of time required to gain insight is one of the standout features of Time Series Insights:
 
-* Time Series Insights requires no upfront data preparation. 
-* It works fast to connect you to billions of events in your Azure IoT Hub or Azure Event Hubs instances in minutes. 
+* Time Series Insights requires no upfront data preparation.
+* It works fast to connect you to billions of events in your Azure IoT Hub or Azure Event Hubs instances in minutes.
 * Once connected, you can visualize and analyze billions of events to spot anomalies and discover hidden trends in your data.
 
 Time Series Insights is intuitive and simple to use. You can interact with your data without writing a single line of code. There’s also no new language you're required to learn, although Time Series Insights provides a granular text-based querying language for advanced users who are familiar with SQL. It also provides select-and-click exploration for novices.
 
-Customers can take advantage of the speed to diagnose asset-related issues quickly. They can perform DevOps analysis to get to the root cause of a bug in an IoT solution. They also can identify areas to flag for further investigation as part of their data science initiatives. 
+Customers can take advantage of the speed to diagnose asset-related issues quickly. They can perform DevOps analysis to get to the root cause of a bug in an IoT solution. They also can identify areas to flag for further investigation as part of their data science initiatives.
 
 There are three primary ways to interact with data stored in Time Series Insights: