Merge pull request #99112 from Virginia001/work01

Work01

Author: PRMerger15

articles/time-series-insights/time-series-insights-overview.md

@@ -8,21 +8,21 @@ ms.author: dpalled
 manager: cshankar
 ms.workload: big-data
 ms.topic: overview
-ms.date: 11/20/2019
+ms.date: 12/11/2019
 ms.custom: seodec18
 ---
 
 # What is Azure Time Series Insights?
 
-Azure Time Series Insights is built to store, visualize, and query large amounts of time series data, such as that generated by IoT devices. If you want to store, manage, query, or visualize time series data in the cloud, Time Series Insights is likely right for you. 
+Azure Time Series Insights is built to store, visualize, and query large amounts of time series data, such as that generated by IoT devices. If you want to store, manage, query, or visualize time series data in the cloud, Time Series Insights is likely right for you.
 
 [![Time Series Insights flowchart](media/overview/time-series-insights-flowchart.png)](media/overview/time-series-insights-flowchart.png#lightbox)
 
 Time Series Insights has four key jobs:
 
 - It's fully integrated with cloud gateways like Azure IoT Hub and Azure Event Hubs. It easily connects to these event sources and parses JSON from messages and structures that have data in clean rows and columns. It joins metadata with telemetry and indexes your data in a columnar store.
 - Time Series Insights manages the storage of your data. To make sure that data is always easily accessible, it stores your data in memory and SSDs for up to 400 days. You can interactively query billions of events in seconds–on demand.
-- Time Series Insights provides out-of-the-box visualization through the Time Series Insights explorer. 
+- Time Series Insights provides out-of-the-box visualization through the Time Series Insights explorer.
 - Time Series Insights provides a query service, both in the Time Series Insights explorer and by using APIs that are easy to integrate to embed your time series data into custom applications.
 
 If you build an application for internal consumption or for external customers to use, you can use Time Series Insights as a back end. You can use it to index, store, and aggregate time series data. To build a custom visualization and user experience on top, use the [Client SDK](https://github.com/microsoft/tsiclient/blob/master/docs/API.md). Time Series Insights is also equipped with several [Query APIs](how-to-shape-query-json.md) to enable these customized scenarios.
@@ -40,23 +40,23 @@ Azure Time Series Insights captures and stores every new event as a row, and cha
 
 ## Primary scenarios
 
-- Store time series data in a scalable way. 
+- Store time series data in a scalable way.
 
    At its core, Time Series Insights has a database designed with time series data in mind. Because it's scalable and fully managed, Time Series Insights handles the work of storing and managing events.
 
-- Explore data in near real time. 
+- Explore data in near real time.
 
-   Time Series Insights provides an explorer that visualizes all data that streams into an environment. Shortly after you connect to an event source, you can view, explore, and query event data within Time Series Insights. The data helps you to validate whether a device emits data as expected and to monitor an IoT asset for health, productivity, and overall effectiveness. 
+   Time Series Insights provides an explorer that visualizes all data that streams into an environment. Shortly after you connect to an event source, you can view, explore, and query event data within Time Series Insights. The data helps you to validate whether a device emits data as expected and to monitor an IoT asset for health, productivity, and overall effectiveness.
 
 - Perform root-cause analysis and detect anomalies.
 
-   Time Series Insights has tools like patterns and perspective views to conduct and save multistep root-cause analysis. Time Series Insights also works with alerting services like Azure Stream Analytics so that you can view alerts and detected anomalies in near real time in the Time Series Insights explorer. 
+   Time Series Insights has tools like patterns and perspective views to conduct and save multistep root-cause analysis. Time Series Insights also works with alerting services like Azure Stream Analytics so that you can view alerts and detected anomalies in near real time in the Time Series Insights explorer.
 
 - Gain a global view of time series data that streams from disparate locations for multi-asset or site comparison.
 
    You can connect multiple event sources to a Time Series Insights environment. This way you can view data that streams in from multiple, disparate locations together in near real time. Users can take advantage of this visibility to share data with business leaders. They can collaborate better with domain experts who can apply their expertise to help solve problems, apply best practices, and share learnings.
 
-- Build a customer application on top of Time Series Insights. 
+- Build a customer application on top of Time Series Insights.
 
    Time Series Insights exposes REST Query APIs that you can use to build applications that use time series data.
 
@@ -75,7 +75,7 @@ Azure Time Series Insights captures and stores every new event as a row, and cha
 To get started, follow these steps.
 
 1. Provision a Time Series Insights environment in the Azure portal.
-1. Connect to an event source like an IoT hub or an event hub. 
+1. Connect to an event source like an IoT hub or an event hub.
 1. Upload reference data. This isn't an additional service.
 1. See your data in minutes with the Time Series Insights explorer.
 

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

@@ -9,7 +9,7 @@ manager: cshankar
 ms.topic: quickstart
 ms.workload: big-data
 ms.custom: mvc seodec18
-ms.date: 10/24/2019
+ms.date: 12/11/2019
 ---
 
 # Quickstart: Explore the Azure Time Series Insights Preview demo environment

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: 10/25/2019
+ms.date: 12/16/2019
 ms.custom: seodec18
 ---
 
@@ -338,8 +338,8 @@ Variables conform to the following JSON example:
 "Status": {
   "kind": "categorical",
   "value": {
-    "tsx": "toLong($event.[Status].Double)",
-  },
+     "tsx": "toLong($event.[Status].Double)" 
+},
   "interpolation": {
     "kind": "step",
     "boundary": {