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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. This quickstart shows you how to use Dataflow to read messages published to a Pub/Sub topic, window (or group) the messages by timestamp, and Write the messages to Cloud Storage.
Register for this course and see more details by visiting:
OpenCourser.com/course/wl8qus/stream
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What's inside
Syllabus
Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Offers a quick start guide to Dataflow, which is a powerful tool for stream processing
Taught by Google Cloud Training, a reputable provider of cloud computing education
Provides hands-on experience with Cloud Pub/Sub and Dataflow, which are industry-standard tools for stream processing
Suitable for beginners who want to learn the basics of stream processing with Dataflow
May require prior knowledge of Cloud Pub/Sub and Dataflow, which could be a barrier for complete beginners
Save this course
Save Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start to your list so you can find it easily later:
Save
Save
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 Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start with these
activities:
Review the Dataflow documentation and tutorials
Show steps
Refreshing your knowledge before the course will give you a strong foundation to build upon.
Browse courses on
Dataflow
Show steps
-
Review the official Dataflow documentation
-
Explore tutorials and sample code provided by Google
-
Experiment with the Dataflow API Explorer
-
Identify areas where you need additional support
Identify experienced Dataflow practitioners for mentorship
Show steps
Mentorship can provide you with guidance and support as you build your Dataflow skills.
Show steps
-
Identify potential mentors through your network or online platforms
-
Reach out to potential mentors and introduce yourself
-
Inquire about their willingness to provide mentorship
-
Establish clear expectations and communication channels
-
Initiate regular meetings or discussions
Practice writing Dataflow pipelines in Java or Python
Show steps
Practicing your coding skills before the course will ensure you're ready to actively participate and contribute to discussions.
Browse courses on
Dataflow
Show steps
-
Set up your development environment
-
Write basic Dataflow pipelines
-
Test and debug your pipelines
-
Experiment with different Dataflow features and functions
Four other activities
Expand to see all activities and additional details
Show all seven activities
Work through Dataflow Quickstart challenges
Show steps
Completing the Dataflow challenges will solidify the skills and knowledge you're gaining through the course.
Browse courses on
Dataflow
Show steps
-
Review the Dataflow Quickstart documentation
-
Run the code in a Cloud console
-
Troubleshoot any errors that may occur
-
Experiment with different parameters
-
Review your results and compare with expected behavior
Attend a Dataflow workshop or meetup
Show steps
Attending a workshop or meetup will provide you with networking opportunities and a more hands-on learning experience.
Show steps
-
Identify relevant workshops or meetups
-
Register for the event
-
Prepare for the event by reviewing relevant materials
-
Attend the event and actively participate
-
Follow up with the organizers or attendees after the event
Write a blog post about your experience using Dataflow
Show steps
Writing a blog post will allow you to organize your knowledge of Dataflow, while also contributing to community knowledge-sharing.
Show steps
-
Choose a specific aspect of Dataflow to focus on
-
Research and gather information from reliable sources
-
Outline the blog post's structure
-
Write the blog post
-
Proofread and edit the blog post
-
Publish the blog post on a relevant platform
Contribute to open-source Dataflow projects
Show steps
Contributing to open-source projects will allow you to gain real-world experience with Dataflow while also contributing to the community.
Show steps
-
Identify open-source Dataflow projects that align with your interests
-
Review the project's documentation and codebase
-
Identify areas where you can make a meaningful contribution
-
Reach out to the project maintainers to discuss your ideas
-
Implement your changes and submit a pull request
Review the Dataflow documentation and tutorials
Show steps
Refreshing your knowledge before the course will give you a strong foundation to build upon.
Browse courses on
Dataflow
Show steps
Show steps
Show steps
- Review the official Dataflow documentation
- Explore tutorials and sample code provided by Google
- Experiment with the Dataflow API Explorer
- Identify areas where you need additional support
Identify experienced Dataflow practitioners for mentorship
Show steps
Mentorship can provide you with guidance and support as you build your Dataflow skills.
Show steps
Show steps
Show steps
- Identify potential mentors through your network or online platforms
- Reach out to potential mentors and introduce yourself
- Inquire about their willingness to provide mentorship
- Establish clear expectations and communication channels
- Initiate regular meetings or discussions
Practice writing Dataflow pipelines in Java or Python
Show steps
Practicing your coding skills before the course will ensure you're ready to actively participate and contribute to discussions.
Browse courses on
Dataflow
Show steps
Show steps
Show steps
- Set up your development environment
- Write basic Dataflow pipelines
- Test and debug your pipelines
- Experiment with different Dataflow features and functions
Four other activities
Expand to see all activities and additional details
Show all seven activities
Work through Dataflow Quickstart challenges
Show steps
Completing the Dataflow challenges will solidify the skills and knowledge you're gaining through the course.
Browse courses on
Dataflow
Show steps
Show steps
Show steps
- Review the Dataflow Quickstart documentation
- Run the code in a Cloud console
- Troubleshoot any errors that may occur
- Experiment with different parameters
- Review your results and compare with expected behavior
Attend a Dataflow workshop or meetup
Show steps
Attending a workshop or meetup will provide you with networking opportunities and a more hands-on learning experience.
Show steps
Show steps
Show steps
- Identify relevant workshops or meetups
- Register for the event
- Prepare for the event by reviewing relevant materials
- Attend the event and actively participate
- Follow up with the organizers or attendees after the event
Write a blog post about your experience using Dataflow
Show steps
Writing a blog post will allow you to organize your knowledge of Dataflow, while also contributing to community knowledge-sharing.
Show steps
Show steps
Show steps
- Choose a specific aspect of Dataflow to focus on
- Research and gather information from reliable sources
- Outline the blog post's structure
- Write the blog post
- Proofread and edit the blog post
- Publish the blog post on a relevant platform
Contribute to open-source Dataflow projects
Show steps
Contributing to open-source projects will allow you to gain real-world experience with Dataflow while also contributing to the community.
Show steps
Show steps
Show steps
- Identify open-source Dataflow projects that align with your interests
- Review the project's documentation and codebase
- Identify areas where you can make a meaningful contribution
- Reach out to the project maintainers to discuss your ideas
- Implement your changes and submit a pull request
Career center
Learners who complete Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the data infrastructure that supports an organization's data-driven initiatives. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Engineer. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and processing large volumes of data in a streaming environment.
Data Scientist
Data Scientist
Data Scientists use statistical and machine learning techniques to extract insights from data. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Scientist. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and processing large volumes of data in real time.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems and make informed decisions. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Analyst. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and analyzing large volumes of data in real time.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Software Engineer. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in designing and developing real-time data processing systems.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud-based solutions. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Cloud Architect. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in designing and managing cloud-based data processing systems.
Big Data Engineer
Big Data Engineer
Big Data Engineers design, build, and maintain big data systems. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Big Data Engineer. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and processing large volumes of data in a distributed environment.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Machine Learning Engineer. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and processing large volumes of data in real time.
DevOps Engineer
DevOps Engineer
DevOps Engineers automate and manage the software development and deployment process. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a DevOps Engineer. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and automating the deployment of real-time data processing systems.
Data Science Manager
Data Science Manager
Data Science Managers lead and manage teams of data scientists. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Science Manager. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
Data Engineer Manager
Data Engineer Manager
Data Engineer Managers lead and manage teams of data engineers. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Engineer Manager. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
Data Scientist Supervisor
Data Scientist Supervisor
Data Scientist Supervisors supervise and manage teams of data scientists. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Scientist Supervisor. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
Data Analyst Supervisor
Data Analyst Supervisor
Data Analyst Supervisors supervise and manage teams of data analysts. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Data Analyst Supervisor. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
Software Engineering Manager
Software Engineering Manager
Software Engineering Managers lead and manage teams of software engineers. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Software Engineering Manager. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
Cloud Architecture Manager
Cloud Architecture Manager
Cloud Architecture Managers lead and manage teams of cloud architects. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Cloud Architecture Manager. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
Big Data Engineering Manager
Big Data Engineering Manager
Big Data Engineering Managers lead and manage teams of big data engineers. This course's focus on stream processing with Cloud Pub/Sub and Dataflow will help build a foundation for success as a Big Data Engineering Manager. By understanding how to use these technologies to read, window, and write messages from a Pub/Sub topic to Cloud Storage, you'll gain valuable skills in managing and overseeing the development of real-time data processing systems.
For more career information including salaries, visit:
OpenCourser.com/course/wl8qus/stream
Reading list
We've selected seven 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
Stream Processing with Cloud Pub/Sub and Dataflow: Qwik Start.
Machine Learning: A Bayesian and Optimization Perspective provides a comprehensive overview of machine learning from a Bayesian and optimization perspective, including topics such as probability theory, Bayesian inference, and optimization.
Provides a comprehensive overview of stream processing with Apache Flink, including its architecture, features, and use cases. It valuable resource for anyone who wants to learn more about stream processing with Apache Flink and how to use it effectively.
Save
Provides a comprehensive overview of big data processing with Apache Spark, including its architecture, features, and use cases. It valuable resource for anyone who wants to learn more about big data processing with Apache Spark and how to use it effectively.
Provides a comprehensive overview of Hadoop, including its architecture, features, and use cases. It valuable resource for anyone who wants to learn more about Hadoop and how to use it effectively.
Save
Designing Data-Intensive Applications provides a practical guide to designing and building data-intensive applications, including topics such as data modeling, data storage, and data processing.
Large-Scale Machine Learning with Python provides a practical guide to large-scale machine learning with Python, including topics such as data preprocessing, feature engineering, and model training.
Data Science for Business provides practical guidance on how to apply data science techniques to business problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wl8qus/stream
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Effort
30 minutes
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Offers a quick start guide to Dataflow, which is a powerful tool for stream processing
Taught by Google Cloud Training, a reputable provider of cloud computing education
Provides hands-on experience with Cloud Pub/Sub and Dataflow, which are industry-standard tools for stream processing
Suitable for beginners who want to learn the basics of stream processing with Dataflow
May require prior knowledge of Cloud Pub/Sub and Dataflow, which could be a barrier for complete beginners
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