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. Stream Analytics Learning Path
    10/3/2016, Webpage
  2. Handling IoT data with Azure Stream Analytics
    7/23/2015, Video, 0:16:48
  3. Introduction to Azure Stream Analytics
    10/6/2015, Video, 0:47:03
  4. Streaming Analytics on Microsoft Azure
    12/5/2016, Video, 0:08:51
  5. Cortana Intelligence Suite End-to-End
    1/16/2017, Mva
  6. Hands-On with Azure Stream Analytics
    9/30/2016, Mva
  7. Azure Data Analytics for Developers
    11/21/2016, Mva
  8. Introduction to Azure IoT
    5/5/2017, Mva
  9. edX-Dev225x - Developing IoT Solutions with Azure IoT
    6/19/2017, Mva
  10. Deep Dive: Azure Stream Analytics Query Language
    5/28/2015, Video, 0:58:45

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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
     3.2. Create jobs
          3.2.1. Create inputs
          3.2.2. 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 REST API & Machine Learning
          3.2.9. Create outputs
          3.2.10. Output to Azure Functions
          3.2.11. Output to Data Lake Store
          3.2.12. Output to DocumentDB
     3.3. Monitor & optimize
          3.3.1. Add alerts
          3.3.2. Monitor jobs
          3.3.3. Monitor jobs programmatically
          3.3.4. Monitor jobs with PowerShell
          3.3.5. Optimize Streaming Units
          3.3.6. Scale to increase throughput
          3.3.7. Scale for Machine Learning functions
     3.4. Manage
          3.4.1. Rotate input & output credentials
          3.4.2. Job reliability during updates
     3.5. Troubleshoot
          3.5.1. Troubleshooting guide
          3.5.2. Resource health blade
          3.5.3. Job diagram and metrics
          3.5.4. SELECT INTO debugging
          3.5.5. Event order handling
          3.5.6. Event hub reader limits
          3.5.7. Diagnostics logs
     3.6. Automate
          3.6.1. Tools for Visual Studio
          3.6.2. Use the Management .NET SDK
          3.6.3. One-click PowerShell
4. Reference
     4.1. Code samples
     4.2. 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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