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4/13/2018 Stream Analytics New Feature Azure Stream Analytics is now available for Azure IoT Edge. This empowers developers to deploy near-real-time analytical intelligence closer to IoT devices so that they can unlock the full value of device-generated data. It's designed for customers who require low latency, resiliency, efficient use of bandwidth, and compliance. Link Link Details
4/12/2018 Stream Analytics New Feature Following the release of JavaScript user-defined functions, Azure Stream Analytics now supports JavaScript user-defined aggregates (UDAs). With UDAs, you can run your own stateful computations: time-weighted averages, cumulative density, array cumulation, and much more. Link Link Details
4/12/2018 Stream Analytics New Feature The need to manage the stability of production code while promoting improvements and code updates as quickly as possible means that development teams spend a lot of time building continuous integration and continuous delivery (CI/CD) processes. To better help these teams, Azure Stream Analytics tools for Visual Studio now include native support for CI/CD. Customers can perform automated builds, test scripts, and deploy them with the Stream Analytics Visual Studio projects, by using the newly released NuGet package. With this capability, it becomes easy to set up CI/CD pipelines for Stream Analytics jobs in the developer’s environment, as well as within other automated processes. Link Link Details
4/12/2018 Stream Analytics New Feature Azure Functions is a "serverless" compute service in Azure. It helps users run code on demand without having to explicitly provision or manage infrastructure. It lets users implement code that is triggered by events occurring in Azure or third-party services. This ability of Azure Functions to respond to triggers makes it a natural output target for Azure Stream Analytics. Link Link Details
4/12/2018 Stream Analytics New Feature Bandwidth issues and message size limitations are the key reasons why customers need support for compression input formats. Azure Stream Analytics now offers support for GZIP and Deflate streams. Link Link Details
4/12/2018 Stream Analytics New Feature Customers build a variety of streaming applications by using Azure Stream Analytics, such as IoT, connected car and automotive telematics, and smart elevators. This work requires processing of telemetry streams from each asset or source by itself—all in the same job, without merging the timeline from events that belong to different devices or sources. The reason is that their clocks might be drastically out of sync. Substream support in Stream Analytics helps customers process telemetry streams with simple language constructs. A new keyword, OVER, extends the TIMESTAMP BY clause for this purpose. Link Link Details
4/12/2018 Stream Analytics Region Update Azure Stream Analytics is available in three additional regions: UK West, Canada Central, and Canada East. With this announcement, Stream Analytics is now available in 26 Azure regions worldwide. Link Link Details
4/12/2018 Stream Analytics New Feature The built-in machine learning–based operator ANOMALYDETECTION is designed to help customers of Azure Stream Analytics who monitor data from applications or devices in real time, and who need help to easily detect events or observations that do not conform to an expected pattern. Link Link Details
4/12/2018 Stream Analytics New Feature With Azure Stream Analytics, customers can combine the power of JavaScript with the simplicity and pervasiveness of SQL. Historically, Stream Analytics let developers express their real-time query logic by using a simple SQL-like language. To support more expressive custom code and help customers implement advanced scenarios, Stream Analytics now supports user-defined functions (UDFs) via JavaScript. With this feature, customers can write their custom code in JavaScript, and easily invoke it as part of their real-time stream processing query. Link Link Details
4/12/2018 Stream Analytics New Feature Azure Stream Analytics customers can now easily build solutions for scenarios such as connected cars, fleet management, and mobile asset tracking. Developers can use built-in geospatial functions in their stream-processing logic to define geographical areas. Developers can evaluate incoming geospatial data for containment, proximity, and overlap, and then generate alerts or start necessary workflows. These geospatial capabilities are in alignment with the GeoJSON specification. Link Link Details

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