Let's talk about this feature of Azure called stream analytics and how to detect an anomaly before it becomes a failure. Data stream is a set of data that is coming through and is very transient, it's not sitting in a traditional SQL database. If we had so, we can just run a batch job and run SQL query over that data and extract whatever insights we want under that data. But what if we have data that is just passing through an event hub? How do we run queries, get reports, raise alerts if something becomes unusual?

Azure Stream Analytics is a fully managed Platform as a Service (PaaS) that supports thousands of mission-critical customer applications powered by real-time insights. Out-of-the-box integration with numerous other Azure services enables developers and data engineers to build high-performance, hot-path data pipelines within minutes. The key tenets of Stream Analytics include Ease of use, Developer productivity, and Enterprise readiness. Today, we're announcing several new features that further enhance these key tenets. Let's take a closer look at these features: Rollout of these preview features begins November 4th, 2019.

Azure Stream Analytics is a fully managed Platform as a Service (PaaS) that supports thousands of mission-critical customer applications powered by real-time insights. Out-of-the-box integration with numerous other Azure services enables developers and data engineers to build high-performance, hot-path data pipelines within minutes. The key tenets of Stream Analytics include Ease of use, Developer productivity, and Enterprise readiness. Today, we're announcing several new features that further enhance these key tenets. Let's take a closer look at these features: Rollout of these preview features begins November 4th, 2019.

Azure Stream Analytics is a fully managed serverless offering on Azure. With the new Anomaly Detection functions in Stream Analytics, the whole complexity associated with building and training custom machine learning (ML) models is reduced to a simple function call resulting in lower costs, faster time to value, and lower latencies.

Built-in machine learning (ML) models for anomaly detection in Azure Stream Analytics significantly reduces the complexity and costs associated with building and training machine learning models. This feature is now available for public preview worldwide both in the cloud and on IoT Edge. Azure Stream Analytics is a fully managed serverless PaaS offering on Azure that enables customers to analyze and process fast moving streams of data, and deliver real-time insights for mission critical scenarios. Developers can use a simple SQL language (extensible to include custom code) to author and deploy powerful analytics processing logic that can scale-up and scale-out to deliver insights with milli-second latencies. Many customers use Azure Stream Analytics to continuously monitor massive amounts of fast-moving streams of data in order to detect issues that do not conform to expected patterns and prevent catastrophic losses. This in essence is anomaly detection.

Learn how to build a sentiment analysis solution for social media analytics by bringing real-time Twitter events into Azure Event Hubs. In this scenario, you write an Azure Stream Analytics query to analyze the data. Then you either store the results for later use or use a dashboard and Power BI to provide insights in real time. Social media analytics tools help organizations understand trending topics. Trending topics are subjects and attitudes that have a high volume of posts in social media.

This post is authored by Scott Haynie, Senior Software Engineer, and Senja Filipi, Software Engineer, at Microsoft. Telemetry plays an important role when you operationalize new experiences/apps that span the web, mobile and IoT, including new gadgets such as the Microsoft HoloLens. The abundance of data that is made available can help developers monitor and track system health and usage patterns, and provide important new insights into how users interact with your application. Tapping into this wealth of information can really help you align your customers' experiences with their needs and expectations. At the Ignite 2016 Innovation Keynote, we showed the future of home improvement as envisioned by Lowe's and Microsoft.

An Event Hub that enables the ingestion of data from the HoloLens client application. A Stream Analytics job that consumes the telemetry data, analyzes it real time, and writes the insights derived into Power BI, as an output. An Event Hub that enables the ingestion of data from the HoloLens client application. A Stream Analytics job that consumes the telemetry data, analyzes it real time, and writes the insights derived into Power BI, as an output.

This article is designed to help you quickly set up a simple Azure Stream Analytics job, with Azure Machine Learning integration. We will use a sentiment analytics Machine Learning model from the Cortana Intelligence Gallery to analyze streaming text data, and determine the sentiment score in real time. The information in this article can help you understand scenarios such as real-time sentiment analytics on streaming Twitter data, analyze records of customer chats with support staff, and evaluate comments on forums, blogs, and videos, in addition to many other real-time, predictive scoring scenarios. This article offers a sample CSV file with text as input in Azure Blob storage, shown in the following image. The job applies the sentiment analytics model as a user-defined function (UDF) on the sample text data from the blob store.

Airlines around the world are eager to take advantage of rapidly emerging technologies to improve their passengers' experience and become more efficient. But while executives recognize the opportunities, they know they can't do it alone. The two industry leaders in aircraft engines and technology are collaborating to offer carriers their expertise and ideas in a business where cutting 1 percent of fuel usage amounts to 250,000 in annual savings per plane. A recent PricewaterhouseCoopers report estimates digital tools in aircraft maintenance could save more than 100 million a year for a large carrier with a fleet of about 500 planes. "Our TotalCare maintenance program was revolutionary in the '90s, so we're pioneers ourselves, and by collaborating with a fellow pioneer like Microsoft, we can absolutely bring innovative digital solutions to airlines now," says Alex Dulewicz, head of marketing for services at Rolls-Royce's civil aerospace division.