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Alan Smith

Azure Stream Analytics brings complex event processing to the Azure cloud platform. This course will teach you how Stream Analytics jobs can be integrated with other Azure services, and used to process event and telemetry streams.

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Azure Stream Analytics brings complex event processing to the Azure cloud platform. This course will teach you how Stream Analytics jobs can be integrated with other Azure services, and used to process event and telemetry streams.

Event-based applications, internet of things projects, and online games can generate a vast amount of event and telemetry data. Querying and analyzing these event streams and being able to provide updates and visualization in real-time will add enormous value to your solutions. In this course, Understanding Azure Stream Analytics, you'll explore the functionality of Azure Stream Analytics, creating SQL-like queries to analyze telemetry and event data. First, you'll learn how to integrate these query jobs with other Azure services so that they can receive telemetry from a driving game, and send the query results to a number of different services. Next, you'll explore data and business intelligence tools to visualize the output data created by stream analytics. Finally, you'll dive into a scenario for this course, which will use telemetry data created during the Global Azure Bootcamp racing game lab to provide real-world telemetry and lap data for examples. By the end of this course, you'll have the necessary knowledge to leverage Azure Stream Analytics in messaging and telemetry.

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Syllabus

Course Overview
Introducing this Course
Understanding Complex Event Processing and Azure Stream Analytics
Querying Data Streams
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Configuring Inputs and Outputs
Analyzing Output Data

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores Azure Stream Analytics, a service that integrates with other Azure services to process event and telemetry streams
Teaches how to use SQL-like queries to analyze telemetry and event data
Covers data visualization and business intelligence tools for analyzing output data
Uses real-world telemetry and lap data from a racing game lab for examples
Part of a series of courses on Azure, indicating comprehensiveness
Taught by Alan Smith, an instructor with expertise in Azure and data analytics

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Understanding Azure Stream Analytics with these activities:
Review core concepts in event-based application development
Review the fundamental concepts of event-driven applications to enhance your understanding of Azure Stream Analytics.
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  • Revisit articles or tutorials on event-driven architectures.
  • Recall the principles of event streaming and telemetry.
  • Refresh your knowledge on event processing techniques, such as filtering and aggregation.
Review basic SQL concepts
Ensure a strong foundation in SQL, which is a core component of Azure Stream Analytics.
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  • Review online resources or textbooks on basic SQL syntax and concepts.
  • Practice writing simple SQL queries to filter, aggregate, and manipulate data.
Explore Azure Stream Analytics documentation and tutorials
Enhance your understanding of Azure Stream Analytics by exploring official documentation and tutorials.
Show steps
  • Visit the Microsoft Azure Stream Analytics documentation page.
  • Follow step-by-step tutorials to create and manage Stream Analytics jobs.
  • Refer to the Stream Analytics quickstart guide for a hands-on introduction.
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Seek guidance from experienced Azure Stream Analytics professionals
Accelerate your learning by connecting with experienced Azure Stream Analytics professionals who can provide valuable insights and support.
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  • Attend industry events or webinars to network with professionals in the field.
  • Reach out to individuals on LinkedIn or other professional networking platforms.
  • Ask questions and seek advice from mentors to gain different perspectives and learn from their experiences.
Review Intermediate SQL
Reinforce your knowledge of SQL, which will be essential for working with the Azure Stream Analytics platform.
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  • Review SQL syntax and commands
  • Practice writing basic SQL queries
  • Complete online SQL tutorials or exercises
Practice SQL queries on sample data
Build your proficiency in writing SQL queries, which are essential for working with Azure Stream Analytics.
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  • Find a dataset that contains sample event data.
  • Write SQL queries to filter, aggregate, and transform the data.
  • Test your queries and analyze the results.
Follow Microsoft tutorials on Azure Stream Analytics
Gain hands-on experience with Azure Stream Analytics by completing guided tutorials provided by Microsoft.
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  • Visit the Microsoft Learn website and search for Azure Stream Analytics tutorials.
  • Choose a tutorial that aligns with your learning goals.
  • Follow the step-by-step instructions to create and configure Azure Stream Analytics jobs.
Discuss Stream Analytics Best Practices
Engage with other learners to share and discuss best practices for working with Stream Analytics.
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  • Join or create a peer study group
  • Share your experiences and insights
  • Learn from others and contribute to the group discussion
Practice writing SQL-like queries for event analysis
Develop proficiency in creating SQL-like queries for analyzing event and telemetry data in Azure Stream Analytics.
Show steps
  • Set up a practice environment with Azure Stream Analytics.
  • Create sample event streams and define input and output configurations.
  • Write and execute queries to filter, aggregate, and transform event data.
  • Troubleshoot and optimize your queries for efficiency.
Analyze Real-Time Data with Stream Analytics
Gain hands-on experience with Stream Analytics by analyzing real-time data from a sample application.
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  • Set up an Azure Stream Analytics job
  • Configure inputs and outputs for the job
  • Write a Stream Analytics query to analyze the data
  • Deploy and run the job
  • Analyze the results of the job
Mentor junior developers or students in Azure Stream Analytics
Sharpen your knowledge and give back by sharing your expertise with others who are learning Azure Stream Analytics.
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  • Identify opportunities to mentor others through online forums, meetups, or your personal network.
  • Provide guidance, support, and encouragement to aspiring Azure Stream Analytics developers.
  • Share your own experiences and insights to help others overcome challenges and accelerate their learning.
Attend a workshop on Azure Stream Analytics
Immerse yourself in a deeper understanding of Azure Stream Analytics by attending a workshop led by experienced practitioners.
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  • Check online resources or your local community for upcoming Azure Stream Analytics workshops.
  • Register for a workshop that fits your schedule and learning needs.
  • Attend the workshop and actively participate in discussions and hands-on exercises.
Build a Data Visualization Dashboard
Showcase your understanding of Stream Analytics by creating a data visualization dashboard that displays the processed data.
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  • Choose a data visualization tool
  • Connect the tool to the Stream Analytics output
  • Design and create visualizations to represent the data
  • Share and present your dashboard
Design a data visualization dashboard for telemetry data
Demonstrate your understanding of Azure Stream Analytics by designing a data visualization dashboard to display real-time telemetry data.
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  • Identify the key metrics and insights you want to visualize.
  • Select an appropriate data visualization tool or platform.
  • Design the layout and visual elements of the dashboard.
  • Integrate the dashboard with Azure Stream Analytics to receive real-time data.
Explore Advanced Stream Analytics Features
Expand your knowledge by exploring advanced features of Stream Analytics, such as windowing, aggregation, and user-defined functions.
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  • Review Microsoft documentation and tutorials
  • Follow online courses or workshops
  • Experiment with the features in a test environment
Build a simple Azure Stream Analytics pipeline
Apply your knowledge by creating a practical Azure Stream Analytics pipeline that addresses a specific problem or scenario.
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  • Identify a problem or scenario that can be addressed using Azure Stream Analytics.
  • Design an Azure Stream Analytics pipeline that meets the requirements of the problem.
  • Implement the pipeline using the Azure portal or Visual Studio.
  • Test and evaluate the performance of the pipeline.
Build an IoT Solution with Stream Analytics
Challenge yourself by building a real-world IoT solution that uses Stream Analytics to process and analyze device telemetry.
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  • Define the project scope and requirements
  • Set up the IoT devices and sensors
  • Create a Stream Analytics job to process the telemetry
  • Design and build a data visualization dashboard
  • Deploy and monitor the solution
Contribute to open-source projects related to Azure Stream Analytics
Enhance your skills and contribute to the community by participating in open-source projects that focus on Azure Stream Analytics.
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  • Search for open-source repositories on GitHub or other platforms that are related to Azure Stream Analytics.
  • Identify issues or areas where you can make contributions.
  • Create pull requests to propose your changes and collaborate with other contributors.
Build an end-to-end IoT data streaming solution using Azure Stream Analytics
Apply your knowledge of Azure Stream Analytics by developing a comprehensive IoT data streaming solution from scratch.
Show steps
  • Define the IoT scenario and data collection requirements.
  • Design and implement the Azure Stream Analytics job for real-time data processing.
  • Integrate the solution with IoT devices and data sources.
  • Evaluate and optimize the performance of the solution.
  • Optionally, share your project on GitHub or other platforms.
Participate in Azure Stream Analytics hackathons or challenges
Test your skills and learn from others by participating in hackathons or challenges that involve Azure Stream Analytics.
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  • Find upcoming Azure Stream Analytics hackathons or challenges online or through your local community.
  • Form a team or work individually to develop creative solutions.
  • Submit your project and compete for recognition and prizes.

Career center

Learners who complete Understanding Azure Stream Analytics will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers build and maintain the infrastructure and systems that store and process data. Azure Stream Analytics is a cloud-based data streaming platform that can be invaluable for Data Engineers who need to analyze and process real-time data streams.
IT Architect
IT Architects design and implement IT systems and infrastructure. Azure Stream Analytics is a cloud-based data streaming platform that can be used as part of an IT architecture to process and analyze real-time data.
Software Engineer
Software Engineers design, develop, and maintain software applications. Azure Stream Analytics can be integrated with other Azure services to create complex event-driven applications, making it a valuable tool for Software Engineers who want to develop real-time applications.
Data Scientist
Data Scientists use scientific methods and data analysis techniques to extract knowledge from data. Azure Stream Analytics can be used as a tool for Data Scientists to analyze real-time data streams to identify trends, patterns, and anomalies.
Data Analyst
As a Data Analyst, you will be working with large datasets to extract meaningful insights and help businesses make better decisions. Azure Stream Analytics is a powerful tool for Data Analysts, enabling them to analyze real-time data streams to identify trends, patterns, and anomalies.
DevOps Engineer
DevOps Engineers bridge the gap between development and operations, ensuring that software is developed and deployed efficiently. Azure Stream Analytics can be used by DevOps Engineers to create automated pipelines for processing and analyzing real-time data.
Security Analyst
Security Analysts protect computer systems and networks from security threats. Azure Stream Analytics can be used to monitor and analyze security data in real-time, helping Security Analysts to identify and respond to security threats quickly.
System Administrator
System Administrators manage and maintain computer systems and networks. Azure Stream Analytics is a cloud-based service that can be used to monitor and analyze system performance in real-time, making it a useful tool for System Administrators.
Quality Assurance Analyst
Quality Assurance Analysts test software applications to ensure that they meet quality standards. Azure Stream Analytics can be used to monitor and analyze application performance in real-time, helping Quality Assurance Analysts to identify and fix issues quickly.
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models to solve business problems. Azure Stream Analytics can be used as a data source for training machine learning models, and to analyze the results of those models in real-time.
Network Engineer
Network Engineers design, implement, and maintain computer networks. Azure Stream Analytics can be used to analyze network traffic in real-time, helping Network Engineers to identify and troubleshoot network issues.
Project Manager
Project Managers plan and execute projects to achieve specific goals. Azure Stream Analytics can be used by Project Managers to track project progress and identify risks in real-time, helping them to make better decisions and keep projects on track.
Business Analyst
Business Analysts work with businesses to understand their needs and develop solutions to meet those needs. Azure Stream Analytics can provide Business Analysts with real-time insights into business processes, helping them to identify areas for improvement and make better decisions.
Product Manager
Product Managers are responsible for the development and launch of new products. Azure Stream Analytics can provide Product Managers with real-time insights into customer behavior and product usage, helping them to make better decisions about product development and marketing.
Database Administrator
As a Database Administrator, you will be involved with managing data systems, such as designing and implementing databases, ensuring security and data integrity, and administering database software. Azure Stream Analytics can help you in this field by allowing you to process complex event streams and analyze data in real-time, which is essential for managing large and complex databases.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Understanding Azure Stream Analytics.
Provides a comprehensive overview of data-intensive applications and their design. It covers topics such as data modeling, data storage, and data processing.
Provides a comprehensive overview of Spark and its use in big data processing. It covers topics such as data storage, data processing, and data analysis.
Designing Data-Intensive Applications comprehensive guide to designing and building data-intensive applications, including those that use event streaming.
Provides a comprehensive overview of Python and its use in data analysis. It covers topics such as data cleaning, data exploration, and data visualization.
Provides a comprehensive overview of R and its use in data science. It covers topics such as data cleaning, data exploration, and data visualization.
Provides a comprehensive guide to stream processing with RxJava. It covers topics such as data ingestion, query processing, and data management.

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