Stream Analytics

Official Documentation

Service Description

The analysis and evaluation of data stored in fixed memory ("resting") can be performed via HDInsight, for example. However, IoT scenarios often require the evaluation of data streams, i.e., data "in motion." Stream Analytics covers precisely this requirement, enabling analysis of data streams in real-time, i.e., data streams can be monitored, and abnormalities in the data can be detected and reported during operation. Queries on the data streams can be formulated in an SQL-based language. Database specialists therefore have a familiar technology for analyzing data streams.

Getting Started

  1. 7/23/2015, Video, 0:16:48
    Scott loves IoT devices, and today Santosh Balasubramanian hooks up a Raspberry PI to Azure Stream Analytics. Use a SQL-like language to ask questions of your IoT devices and...
  2. 10/6/2015, Video, 0:47:03
    Azure Stream Analytics, is an Azure Service that enables real-time insights over streaming data from devices, sensors, infrastructure, and applications. We recently announced...
  3. 12/5/2016, Video, 0:08:51
    Azure Stream Analytics – adding real-time capabilities to your applications
  4. 1/16/2017, Mva
    If you’d like to learn how to architect solutions in Cortana Intelligence Suite and how to build intelligence into your applications, don’t miss this workshop! Build an...
  5. 9/30/2016, Mva
    Want to set up real-time analytic computations on data streaming from devices, sensors, websites, social media, apps, and more? Check out this demo-filled, hands-on Azure...
  6. 11/21/2016, Mva
    Want to learn about cutting-edge data science technologies—Azure Machine Learning and Azure Stream Analytics? Join experts Christopher Harrison and Jeff Prosise for this...
  7. 5/5/2017, Mva
    Ready to learn more about Internet of Things (IoT)? Join expert Jeremy Foster for this Azure IoT overview, and find out how to get started. Explore the fundamentals of IoT and...
  8. 6/19/2017, Mva
    Ready to take your first steps in IoT device development? Bring your basic programming skills, and get started with this practical exploration of what IoT means and how to use...
  9. 5/28/2015, Video, 0:58:45
    Azure Stream Analytics removes the complexity of stream processing for developers by providing a SQL-like language for authoring queries.Learn how to build queries to perform...



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Azure Documentation

1. Overview
     1.1. What is Stream Analytics?
     1.2. Compare Storm & Stream Analytics
2. Get started
     2.1. Process IoT streaming data
     2.2. Real-time fraud detection
     2.3. Analyze data with Power BI
3. How to
     3.1. Build streaming solutions
          3.1.1. Social media
          3.1.2. Real-time scoring with Machine Learning
          3.1.3. Real-time event processing
          3.1.4. Stream Analytics on IoT Edge (preview)
          3.1.5. Anomaly detection in Azure usage guide (preview)
          3.1.6. High frequency trading simulation with Stream Analytics
          3.1.7. Azure Functions with Azure Stream Analytics
     3.2. Create jobs
          3.2.1. Create inputs
          3.2.2. Test queries and sample input data
          3.2.3. Common query patterns
          3.2.4. Window functions
          3.2.5. Use reference data
          3.2.6. Test queries
          3.2.7. Integrate JavaScript UDFs
          3.2.8. Integrate JavaScript UDAs
          3.2.9. Integrate REST API & Machine Learning
          3.2.10. Create outputs
          3.2.11. Output to Data Lake Store
          3.2.12. Output to Cosmos DB
     3.3. Use Visual Studio tools
          3.3.1. Install
          3.3.2. Get started
          3.3.3. Set up CI/CD pipelines
     3.4. Monitor & optimize
          3.4.1. Add alerts
          3.4.2. Monitor jobs
          3.4.3. Monitor jobs programmatically
          3.4.4. Monitor jobs with PowerShell
          3.4.5. Understand and adjust Streaming Units
          3.4.6. Leverage query parallelization
          3.4.7. Scale to increase throughput
          3.4.8. Scale for Machine Learning functions
     3.5. Manage
          3.5.1. Rotate input & output credentials
          3.5.2. Job reliability during updates
          3.5.3. Configure compatibility level
     3.6. Troubleshoot
          3.6.1. Troubleshooting guide
          3.6.2. Resource health blade
          3.6.3. Job diagram and metrics
          3.6.4. SELECT INTO debugging
          3.6.5. Event ordering considerations
          3.6.6. Event hub reader limits
          3.6.7. Diagnostics logs
     3.7. Automate
          3.7.1. Use the Management .NET SDK
          3.7.2. One-click Azure PowerShell
4. Reference
     4.1. Code samples
     4.2. Azure PowerShell
     4.3. .NET
     4.4. Query language
     4.5. REST
5. Resources
     5.1. Azure Roadmap
     5.2. Blog
     5.3. Feedback forum
     5.4. Forum
     5.5. Pricing
     5.6. Pricing calculator
     5.7. Release notes
     5.8. Service updates
     5.9. Stack Overflow
     5.10. Videos

Online Training Content

Date Title
6/19/2017 edX-Dev225x - Developing IoT Solutions with Azure IoT
5/24/2017 Processing Real-Time Data Streams in Azure
5/5/2017 Introduction to Azure IoT
1/16/2017 Cortana Intelligence Suite End-to-End
11/21/2016 Azure Data Analytics for Developers
9/30/2016 Hands-On with Azure Stream Analytics
6/3/2015 Einführung in Microsoft Azure–Advanced Services

Tools

Tool Description

Videos

Date Title Length
5/10/2017 Azure IoT: A Developers' deep dive 0:29:08
5/10/2017 Real-time sentiment built on the Azure IoT Stack 0:21:49
5/10/2017 Smart buildings: Connecting Buildings to the Cloud 0:26:44
5/10/2017 System performance is a feature: Understanding system health through telemetry (a continuation of real-time sentiment built on the Azure IoT Stack) 0:16:05
5/10/2017 Lambda Architecture for Connected Car Fleet Management 0:00:00
3/1/2017 Geospatial Functions in Azure Stream Analytics 0:10:37
2/2/2017 Geospatial Functions in Azure Stream Analytics 0:10:36
12/5/2016 Streaming Analytics on Microsoft Azure 0:08:51
9/30/2016 Hands-On with Azure Stream Analytics 0:51:42
9/29/2016 Gain real time and predictive insights on your Internet of Things 1:09:52

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