Understanding Azure Stream Analytics from Pluralsight

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.

What's inside

Syllabus

Course Overview

Introducing this Course

Understanding Complex Event Processing and Azure Stream Analytics

Querying Data Streams

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

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

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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

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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

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Enhance your understanding of Azure Stream Analytics by exploring official documentation and tutorials.

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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

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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

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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

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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

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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

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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

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Develop proficiency in creating SQL-like queries for analyzing event and telemetry data in Azure Stream Analytics.

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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Apply your knowledge of Azure Stream Analytics by developing a comprehensive IoT data streaming solution from scratch.

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Understanding Azure Stream Analytics

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