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Dean Savovic
In this 1-hour long project-based course, you will learn how to (stream and process events with Azure Stream Analytics, data Ingestion with Event Hubs, processing data with Stream Analytics Jobs).
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/s1fkwh/performing
What's inside
Syllabus
Project Overview
In this project, you will learn the concepts of event processing and streaming data and how this applies to Events Hubs and Azure Stream Analytics. You will then set up a stream analytics job to stream data and learn how to query the incoming data to perform analysis of the data. Finally, you will learn how to manage and monitor running jobs.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Course focuses on trending technology: stream and process events with Azure Stream Analytics
Appropriate for those who are entry-level in the field of streaming data processing
Beginners can learn the basics of event processing and streaming data
There are hands-on, practical projects to solidify learning
Additional courses may be required to dive deeper into the subject
Save this course
Save Performing Real Time Analytics with Stream Analytics to your list so you can find it easily later:
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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 Performing Real Time Analytics with Stream Analytics with these
activities:
Review Stream Analytics concepts
Show steps
Revisit the core concepts of Stream Analytics to ensure a solid foundation.
Browse courses on
Stream Analytics
Show steps
-
Review the official documentation on Stream Analytics.
-
Watch introductory videos or tutorials on Stream Analytics.
Join a study group or forum
Show steps
Collaborate with peers to discuss concepts, ask questions, and share knowledge about Stream Analytics.
Show steps
-
Identify and join online study groups or forums dedicated to Stream Analytics.
-
Participate actively in discussions and ask for help when needed.
Analyze sample data using Stream Analytics Explorer
Show steps
Gain hands-on experience by analyzing streaming data using the Stream Analytics Explorer.
Show steps
-
Obtain sample data or create your own.
-
Load the data into the Stream Analytics Explorer.
-
Write queries to explore and analyze the data.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create a stream analytics job
Show steps
Apply your understanding of Stream Analytics by creating a job to process and analyze streaming data.
Show steps
-
Design the schema for your input data.
-
Configure the input source and output sink for your job.
-
Define the queries to process the data.
-
Deploy and test your job.
Attend a workshop or webinar on Stream Analytics
Show steps
Enhance your knowledge and skills by attending a workshop or webinar led by experts in Stream Analytics.
Show steps
-
Research upcoming workshops or webinars on Stream Analytics.
-
Register and attend the event.
Follow tutorials on advanced Stream Analytics features
Show steps
Enhance your skills by exploring advanced topics and techniques in Stream Analytics.
Show steps
-
Identify specific areas where you want to improve your knowledge.
-
Search for and enroll in online tutorials or courses.
Contribute to open-source projects related to Stream Analytics
Show steps
Enhance your understanding and make a meaningful contribution by participating in open-source projects related to Stream Analytics.
Show steps
-
Identify open-source projects that align with your interests.
-
Review the documentation and contribute code or documentation.
Participate in a hackathon or competition involving Stream Analytics
Show steps
Challenge yourself and showcase your skills by participating in a hackathon or competition that focuses on Stream Analytics.
Show steps
-
Identify relevant hackathons or competitions.
-
Form a team or participate individually.
Review Stream Analytics concepts
Show steps
Revisit the core concepts of Stream Analytics to ensure a solid foundation.
Browse courses on
Stream Analytics
Show steps
Show steps
Show steps
- Review the official documentation on Stream Analytics.
- Watch introductory videos or tutorials on Stream Analytics.
Join a study group or forum
Show steps
Collaborate with peers to discuss concepts, ask questions, and share knowledge about Stream Analytics.
Show steps
Show steps
Show steps
- Identify and join online study groups or forums dedicated to Stream Analytics.
- Participate actively in discussions and ask for help when needed.
Analyze sample data using Stream Analytics Explorer
Show steps
Gain hands-on experience by analyzing streaming data using the Stream Analytics Explorer.
Show steps
Show steps
Show steps
- Obtain sample data or create your own.
- Load the data into the Stream Analytics Explorer.
- Write queries to explore and analyze the data.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create a stream analytics job
Show steps
Apply your understanding of Stream Analytics by creating a job to process and analyze streaming data.
Show steps
Show steps
Show steps
- Design the schema for your input data.
- Configure the input source and output sink for your job.
- Define the queries to process the data.
- Deploy and test your job.
Attend a workshop or webinar on Stream Analytics
Show steps
Enhance your knowledge and skills by attending a workshop or webinar led by experts in Stream Analytics.
Show steps
Show steps
Show steps
- Research upcoming workshops or webinars on Stream Analytics.
- Register and attend the event.
Follow tutorials on advanced Stream Analytics features
Show steps
Enhance your skills by exploring advanced topics and techniques in Stream Analytics.
Show steps
Show steps
Show steps
- Identify specific areas where you want to improve your knowledge.
- Search for and enroll in online tutorials or courses.
Contribute to open-source projects related to Stream Analytics
Show steps
Enhance your understanding and make a meaningful contribution by participating in open-source projects related to Stream Analytics.
Show steps
Show steps
Show steps
- Identify open-source projects that align with your interests.
- Review the documentation and contribute code or documentation.
Participate in a hackathon or competition involving Stream Analytics
Show steps
Challenge yourself and showcase your skills by participating in a hackathon or competition that focuses on Stream Analytics.
Show steps
Show steps
Show steps
- Identify relevant hackathons or competitions.
- Form a team or participate individually.
Career center
Learners who complete Performing Real Time Analytics with Stream Analytics will develop knowledge and skills
that may be useful to these careers:
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses make informed decisions. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Statistics.
Data Analyst
Data Analyst
Data Analysts gather, clean, and analyze data to identify trends and patterns, which helps businesses make informed decisions. This course in Performing Real Time Analytics with Stream Analytics will help build a foundation in streaming data and event processing, which are essential skills for Data Analysts.
Data Engineer
Data Engineer
Data Engineers design and build systems for storing, processing, and analyzing data. This course will help build a foundation in streaming data and event processing, which are essential skills for Data Engineers.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visualizations of data to help people understand it more easily. This course will help you gain experience with Azure Stream Analytics, which can be used to analyze data in real time and create visualizations.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make better decisions. This course will help you gain experience with Azure Stream Analytics, which can be used to analyze data in real time and identify trends and patterns.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud-based solutions for businesses. This course will help you gain experience with Azure Stream Analytics, which is a cloud-based service for real-time data processing and analysis.
Risk Analyst
Risk Analyst
Risk Analysts analyze data to identify and mitigate risks. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Risk Management.
Data Scientist
Data Scientist
Data Scientists use their knowledge of statistics, mathematics, and programming to extract insights from data. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Data Science.
Marketing Analyst
Marketing Analyst
Marketing Analysts analyze data to understand customer behavior and make marketing decisions. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Marketing.
Sales Analyst
Sales Analyst
Sales Analysts analyze data to understand sales trends and make sales decisions. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Sales.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Operations Research.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Finance.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will help you gain experience with Azure Stream Analytics, which can be used to build real-time data processing and analysis applications.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models. This course will help build a foundation in streaming data and event processing, which are becoming increasingly important in the field of Machine Learning.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. This course will help you gain experience with Azure Stream Analytics, which can be used to analyze data in real time and identify customer needs.
For more career information including salaries, visit:
OpenCourser.com/course/s1fkwh/performing
Reading list
We've selected eight 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
Performing Real Time Analytics with Stream Analytics.
Provides a comprehensive overview of browser networking, including the different protocols and techniques that are used to transfer data between browsers and servers. It valuable resource for anyone who wants to learn more about the performance of browser networking.
Provides a practical guide to building microservices, a popular architectural style for building distributed applications. It valuable resource for anyone who wants to learn more about the design and implementation of microservices.
Provides a comprehensive overview of data-intensive text processing with MapReduce, a popular programming model for processing large datasets. It valuable resource for anyone who wants to learn more about the challenges and techniques involved in processing text data with MapReduce.
Provides a practical guide to machine learning with R, a popular programming language for data science. It valuable resource for anyone who wants to learn more about the challenges and techniques involved in machine learning with R.
Provides a practical guide to deep learning with Python, a popular programming language for deep learning. It valuable resource for anyone who wants to learn more about the challenges and techniques involved in deep learning with Python.
Provides a comprehensive overview of natural language processing with Python, a popular programming language for natural language processing. It valuable resource for anyone who wants to learn more about the challenges and techniques involved in natural language processing with Python.
Provides a practical guide to computer vision with Python, a popular programming language for computer vision. It valuable resource for anyone who wants to learn more about the challenges and techniques involved in computer vision with Python.
Provides a comprehensive overview of speech and language processing, a popular field in natural language processing. It valuable resource for anyone who wants to learn more about the challenges and techniques involved in speech and language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/s1fkwh/performing
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Effort
1 hour
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Dean Savovic
Language
English
Good to know
Course focuses on trending technology: stream and process events with Azure Stream Analytics
Appropriate for those who are entry-level in the field of streaming data processing
Beginners can learn the basics of event processing and streaming data
There are hands-on, practical projects to solidify learning
Additional courses may be required to dive deeper into the subject
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