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Reza Salehi

Do you need to process live data streams from sensors, custom apps, IoT devices, and logs? Do you need to immediately respond to anomalies and patterns in live data streams? Are you familiar with T-SQL? If so, Azure Stream Analytics is for you.

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Do you need to process live data streams from sensors, custom apps, IoT devices, and logs? Do you need to immediately respond to anomalies and patterns in live data streams? Are you familiar with T-SQL? If so, Azure Stream Analytics is for you.

Processing live data streams in real time can be challenging and expensive. In this course, Building Streaming Data Pipelines in Microsoft Azure, you will gain the ability to effectively use Azure Stream Analytics for your live data processing needs. First, you will learn to configure stream and reference inputs for the service. Next, you will discover how to process your data using the Stream Analytics Query Language. Finally, you will explore how to visualize Azure Stream Analytics output with Microsoft Power BI. When you are finished with this course, you will have the skills and knowledge of Azure Stream Analytics needed to turn your live stream data into meaningful, actionable information.

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What's inside

Syllabus

Course Overview
Azure Stream Analytics Overview
Configure Azure Stream Analytics with Event Hub and Blob Storage Inputs
Query Data Using Azure Stream Analytics
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Implement Azure Stream Analytics Data Visualization with PowerBI
Anomaly Detection in Azure Stream Analytics
Analyzing Stream Data Using Azure Data Explorer

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops core foundational skills and knowledge in working with live data, event hubs, databases, and log analysis in Microsoft Azure
Builds familiarity with T-SQL, which is standard in the software engineering industry
Taught by Reza Salehi, a recognized instructor
Examines tools and skills that are highly relevant in industry
Teaches skills that are useful for both personal and professional growth
Covers an array of topics including building streaming data pipelines, anomaly detection, and data visualization

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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 Building Streaming Data Pipelines in Microsoft Azure with these activities:
Course Resource Compilation
Organize and review important course materials, ensuring you have a comprehensive understanding of the key concepts.
Show steps
  • Create a dedicated folder or notebook to store course materials.
  • Regularly add lecture notes, slides, assignments, and any other relevant resources to the repository.
  • Review the compiled materials periodically to reinforce your learning.
Stream Processing with Azure Stream Analytics
Gain a solid foundation in Stream Analytics by reading a comprehensive book dedicated to the subject.
Show steps
  • Obtain a copy of the book.
  • Read through the chapters related to the course curriculum.
T-SQL Practice
Reinforce your understanding of T-SQL by following tutorials and completing exercises.
Show steps
  • Find online tutorials on T-SQL fundamentals.
  • Work through the tutorials, completing exercises and examples.
  • Refer to the T-SQL documentation for additional guidance.
Four other activities
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Show all seven activities
Stream Analytics Discussion Group
Engage in discussions with peers to exchange knowledge, ask questions, and clarify concepts related to Stream Analytics.
Show steps
  • Join an online forum or discussion group dedicated to Stream Analytics.
  • Participate in discussions, asking thoughtful questions and responding to others.
  • Use the group to troubleshoot any challenges you encounter.
Stream Analytics Query Exercises
Enhance your proficiency in writing Stream Analytics queries by solving practice problems.
Show steps
  • Access the Microsoft Learn module on Stream Analytics queries.
  • Attempt the hands-on exercises within the module.
  • Review the solutions provided and learn from your mistakes.
Anomaly Detection Pipeline
Develop a hands-on understanding of anomaly detection by building a real-world pipeline in Stream Analytics.
Show steps
  • Design the architecture of your anomaly detection pipeline.
  • Implement the pipeline using Stream Analytics.
  • Test and refine the pipeline to optimize its accuracy.
Stream Analytics Code Snippets Library
Build your own repository of code snippets to enhance your understanding and retention of Stream Analytics concepts.
Show steps
  • Design and develop common Stream Analytics functions and queries.
  • Document and organize the code snippets in a systematic manner.
  • Share your library with peers or contribute to open source communities.

Career center

Learners who complete Building Streaming Data Pipelines in Microsoft Azure will develop knowledge and skills that may be useful to these careers:
Data Analyst
As a Data Analyst, you will be responsible for collecting, processing, and analyzing data. You will use data to solve business problems and make informed decisions. This course can help you build a foundation in data processing and analysis techniques that are essential for success in this role. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Business Intelligence Analyst
As a Business Intelligence Analyst, you will be responsible for using data to make informed decisions. You will work with businesses to identify their needs and develop solutions that meet those needs. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Data Engineer
As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines. You will work with data from a variety of sources and use a variety of tools and techniques to transform and integrate data. This course can help you build a strong foundation in the Azure Stream Analytics service. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Cloud Engineer
As a Cloud Engineer, you will be responsible for designing, building, and maintaining cloud computing solutions. You will work with a variety of cloud providers and technologies to develop solutions that meet the needs of your clients. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Software Engineer
As a Software Engineer, you will be responsible for designing, building, and maintaining software applications. You will work with a variety of programming languages and technologies to develop solutions that meet the needs of your clients. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Data Scientist
As a Data Scientist, you will be responsible for using data to solve business problems. You will use a variety of statistical and machine learning techniques to analyze data and develop solutions. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Systems Administrator
As a Systems Administrator, you will be responsible for managing and maintaining computer systems. You will work with a variety of operating systems and technologies to ensure that systems are available and performant. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Database Administrator
As a Database Administrator, you will be responsible for managing and maintaining databases. You will work with a variety of database technologies to ensure that databases are available and performant. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Data Architect
As a Data Architect, you will be responsible for designing and managing data architectures. You will work with a variety of data sources and technologies to develop solutions that meet the needs of your clients. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Network Administrator
As a Network Administrator, you will be responsible for managing and maintaining computer networks. You will work with a variety of networking technologies to ensure that networks are available and performant. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Security Analyst
As a Security Analyst, you will be responsible for identifying and mitigating security risks. You will work with a variety of security technologies and techniques to protect your organization from cyber attacks. This course can help you build a strong foundation in Azure Stream Analytics and its applications. The course covers topics such as configuring stream and reference inputs for Azure Stream Analytics, processing data using the Stream Analytics Query Language, and visualizing Azure Stream Analytics output with Microsoft Power BI.
Product Manager
As a Product Manager, you will be responsible for developing and managing products. You will work with a variety of stakeholders to identify customer needs, develop product roadmaps, and launch new products. This course may be useful for you if you are interested in learning about Azure Stream Analytics and its applications.
Sales Manager
As a Sales Manager, you will be responsible for leading and managing a sales team. You will work with a variety of stakeholders to develop sales strategies, set sales targets, and track sales results. This course may be useful for you if you are interested in learning about Azure Stream Analytics and its applications.
Project Manager
As a Project Manager, you will be responsible for planning, executing, and closing projects. You will work with a variety of stakeholders to ensure that projects are completed on time, within budget, and to the satisfaction of the stakeholders. This course may be useful for you if you are interested in learning about Azure Stream Analytics and its applications.
Marketing Manager
As a Marketing Manager, you will be responsible for developing and executing marketing campaigns. You will work with a variety of stakeholders to identify target markets, develop marketing messages, and track campaign results. This course may be useful for you if you are interested in learning about Azure Stream Analytics and its applications.

Reading list

We've selected 11 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 Building Streaming Data Pipelines in Microsoft Azure.
Provides a comprehensive overview of the Hadoop ecosystem, including HDFS, MapReduce, and other components relevant to streaming data analysis.
Provides a comprehensive introduction to Apache Flink, a popular open-source stream processing framework. It covers topics such as data ingestion, query development, output options, and troubleshooting.
Provides a solid foundation in SQL, a language commonly used in Azure Stream Analytics, helping you develop a strong understanding of data querying and manipulation.
Since Azure Stream Analytics can be integrated with Power BI, this book offers a comprehensive guide to data visualization techniques using Power BI, enhancing your ability to present and analyze streaming data.
Provides a comprehensive overview of Apache Spark Streaming, a popular distributed streaming platform. It covers topics such as data ingestion, query development, output options, and troubleshooting.
Provides a comprehensive overview of RxJS, a powerful library for building reactive applications, which can be useful for understanding the reactive programming concepts used in Azure Stream Analytics.
Provides a comprehensive overview of Microsoft Power BI, a popular business intelligence tool. It covers topics such as data ingestion, query development, output options, and troubleshooting.
Provides a comprehensive overview of Apache Kafka, a popular distributed streaming platform. It covers topics such as data ingestion, query development, output options, and troubleshooting.
Provides a comprehensive overview of SQL, a popular language for data analysis. It covers topics such as data ingestion, query development, output options, and troubleshooting.
While not directly related to Azure Stream Analytics, this in-depth guide to Apache Kafka, a widely used distributed streaming platform, provides valuable context and insights into the broader landscape of stream processing.
Provides a high-level overview of the challenges and best practices in designing and building data-intensive applications, offering valuable insights for anyone working with streaming data.

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