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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. The BigQuery processing pipeline queries a public COVID-19 dataset on a schedule, creates charts from the data, then notifies users about the new charts via SendGrid with Events for Cloud Run on GKE
Register for this course and see more details by visiting:
OpenCourser.com/course/gosamb/build
What's inside
Syllabus
Build a BigQuery Processing Pipeline with Events for Cloud Run for Anthos
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Develops cloud computing and IT skills, which are core skills for data analysts and engineers
Examines a public COVID-19 dataset and uses SendGrid, which are highly relevant to data analysis
Offers hands-on labs and interactive materials, providing practical experience
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Save Build a BigQuery Processing Pipeline with Events for Cloud Run for Anthos 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 Build a BigQuery Processing Pipeline with Events for Cloud Run for Anthos with these
activities:
Read 'Big Data: Principles and Best Practices of Scalable Real-Time Data Systems' by Nathan Marz
Show steps
This book provides a comprehensive overview of the principles and best practices of big data systems and can enhance your understanding of the concepts in the course.
View
Big Data: Principles and best practices of...
on Amazon
Show steps
-
Acquire the book through purchase, rental, or library loan
-
Set aside dedicated time for reading and comprehension
-
Take notes or highlight key takeaways
-
Reflect on how the book's concepts relate to the course
Follow the Google Cloud Platform Quickstart guides
Show steps
Following the quickstart guides will help you get started with the Google Cloud Platform quickly and easily.
Browse courses on
Google Cloud Platform
Show steps
-
Choose a quickstart guide for a Google Cloud Platform service
-
Follow the steps in the guide
Run code examples from the course in your own environment
Show steps
Running the code examples in your own environment forces you to build an understanding of how and why they work to obtain the results you expect.
Show steps
-
Identify a code example from the course
-
Clone the example's code to your local computer
-
Review the example locally
-
Run the example on your own
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group or discussion forum for the course
Show steps
Participating in a study group or discussion forum will allow you to collaborate with others, exchange ideas, and reinforce your understanding.
Show steps
-
Find a study group or discussion forum for the course
-
Introduce yourself and participate in discussions
Attend a Google Cloud Platform meetup or event
Show steps
Attending a Google Cloud Platform meetup or event will allow you to learn more about the platform and meet other people who are using it.
Browse courses on
Google Cloud Platform
Show steps
-
Find a Google Cloud Platform meetup or event in your area
-
Register for the event
-
Attend the event
Use a data visualization tool of your choice to create a chart from a public COVID-19 dataset
Show steps
Working with a data visualization tool and a COVID-19 dataset will give you practical experience in using the skills and tools you've learned in the course.
Browse courses on
Data Visualization
Show steps
-
Find a data visualization tool of your choice
-
Choose a public COVID-19 dataset
-
Create a chart in your chosen tool using the data
-
Publish your chart for others to see
Create a collection of your notes, assignments, and resources from the course
Show steps
Organizing your notes and resources will help you retain the information you've learned and make it easier to review later.
Show steps
-
Gather your notes, assignments, and resources from the course
-
Create folders or use a digital tool to organize your materials
Read 'Big Data: Principles and Best Practices of Scalable Real-Time Data Systems' by Nathan Marz
Show steps
This book provides a comprehensive overview of the principles and best practices of big data systems and can enhance your understanding of the concepts in the course.
View
Big Data: Principles and best practices of...
on Amazon
Show steps
Show steps
Show steps
- Acquire the book through purchase, rental, or library loan
- Set aside dedicated time for reading and comprehension
- Take notes or highlight key takeaways
- Reflect on how the book's concepts relate to the course
Follow the Google Cloud Platform Quickstart guides
Show steps
Following the quickstart guides will help you get started with the Google Cloud Platform quickly and easily.
Browse courses on
Google Cloud Platform
Show steps
Show steps
Show steps
- Choose a quickstart guide for a Google Cloud Platform service
- Follow the steps in the guide
Run code examples from the course in your own environment
Show steps
Running the code examples in your own environment forces you to build an understanding of how and why they work to obtain the results you expect.
Show steps
Show steps
Show steps
- Identify a code example from the course
- Clone the example's code to your local computer
- Review the example locally
- Run the example on your own
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group or discussion forum for the course
Show steps
Participating in a study group or discussion forum will allow you to collaborate with others, exchange ideas, and reinforce your understanding.
Show steps
Show steps
Show steps
- Find a study group or discussion forum for the course
- Introduce yourself and participate in discussions
Attend a Google Cloud Platform meetup or event
Show steps
Attending a Google Cloud Platform meetup or event will allow you to learn more about the platform and meet other people who are using it.
Browse courses on
Google Cloud Platform
Show steps
Show steps
Show steps
- Find a Google Cloud Platform meetup or event in your area
- Register for the event
- Attend the event
Use a data visualization tool of your choice to create a chart from a public COVID-19 dataset
Show steps
Working with a data visualization tool and a COVID-19 dataset will give you practical experience in using the skills and tools you've learned in the course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find a data visualization tool of your choice
- Choose a public COVID-19 dataset
- Create a chart in your chosen tool using the data
- Publish your chart for others to see
Create a collection of your notes, assignments, and resources from the course
Show steps
Organizing your notes and resources will help you retain the information you've learned and make it easier to review later.
Show steps
Show steps
Show steps
- Gather your notes, assignments, and resources from the course
- Create folders or use a digital tool to organize your materials
Career center
Learners who complete Build a BigQuery Processing Pipeline with Events for Cloud Run for Anthos will develop knowledge and skills
that may be useful to these careers:
BigQuery Engineer
BigQuery Engineer
A BigQuery Engineer uses Google Cloud's BigQuery, a large-scale data warehouse, to manage and query data. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. This skillset is highly relevant to a BigQuery Engineer.
Data Analyst
Data Analyst
A Data Analyst gathers, examines, and interprets data to help organizations make better decisions. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Data Analysts use BigQuery to perform data analysis and visualization.
Data Engineer
Data Engineer
A Data Engineer develops and maintains data infrastructure. This course helps build a foundation for working with large datasets. Data Engineers use BigQuery's powerful analytical engine to develop and maintain data pipelines.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and manages cloud infrastructure. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Cloud Architects can use BigQuery and Events for Cloud Run to design and build scalable and reliable data pipelines.
Cloud Data Engineer
Cloud Data Engineer
A Cloud Data Engineer designs and builds cloud-based data solutions. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Cloud Data Engineers use BigQuery to create and manage data pipelines.
Data Scientist
Data Scientist
A Data Scientist uses data to solve complex problems. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Data Scientists use BigQuery to explore and analyze large datasets.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst uses data to improve business outcomes. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Business Intelligence Analysts rely on BigQuery to perform data analysis and visualization.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course helps build a strong foundation for data management. Database Administrators use BigQuery to manage and maintain large-scale data warehouses.
DevOps Engineer
DevOps Engineer
A DevOps Engineer builds and maintains software systems. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. DevOps Engineers use BigQuery to build and maintain data pipelines and infrastructure.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Software Engineers use BigQuery to build and maintain data pipelines.
Data Warehouse Engineer
Data Warehouse Engineer
A Data Warehouse Engineer designs and builds data warehouses. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Data Warehouse Engineers use BigQuery to build and maintain data warehouses.
Data Architect
Data Architect
A Data Architect designs and builds data architectures. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Data Architects use BigQuery to design and build scalable and reliable data architectures.
Data Integration Engineer
Data Integration Engineer
A Data Integration Engineer integrates data from multiple sources. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Data Integration Engineers use BigQuery to integrate data from multiple sources.
Site Reliability Engineer
Site Reliability Engineer
A Site Reliability Engineer ensures the reliability and performance of software systems. This course builds a BigQuery processing pipeline that queries a public data set, creates charts from the data, and then notifies users about the new charts via SendGrid with Events for Cloud Run. Site Reliability Engineers use BigQuery to monitor and improve the performance of data pipelines and infrastructure.
Information Security Analyst
Information Security Analyst
An Information Security Analyst protects data and systems from unauthorized access. This course helps build a foundation for data security. Information Security Analysts use BigQuery to manage and secure large amounts of data.
For more career information including salaries, visit:
OpenCourser.com/course/gosamb/build
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
Build a BigQuery Processing Pipeline with Events for Cloud Run for Anthos.
Introduces Python programming for data analysis. Covers essential concepts and techniques, complementing the course's focus on Python scripting for BigQuery processing pipelines.
Save
Provides a practical introduction to SQL, a widely used language for data manipulation and analysis. Offers a solid foundation for understanding the SQL queries used in the course's BigQuery processing pipelines.
Save
Provides a comprehensive overview of data-intensive application design principles. Serves as a valuable resource for understanding the underlying concepts behind BigQuery processing pipelines.
Provides a comprehensive overview of data warehousing concepts and technologies. Offers valuable background knowledge for understanding the role of BigQuery as a cloud-based data warehouse.
Offers a thorough foundation in database systems, including advanced topics like data warehousing and query optimization. Provides background knowledge that complements the course's focus on BigQuery, a cloud-based data warehouse.
Provides a deep dive into Spark, a widely adopted framework for Big Data processing. While not directly covered in the course, understanding Spark can enhance the applicability of BigQuery processing techniques.
Takes Python programming for data science to the next level. Offers more advanced techniques and concepts, enhancing the applicability of Python scripting in the course's BigQuery processing pipelines.
Serves as a comprehensive reference for Hadoop, a framework for distributed data processing. Offers insights into the underlying technologies and concepts, complementing the course's emphasis on BigQuery's distributed processing capabilities.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/gosamb/build
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Effort
1 hour 15 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Develops cloud computing and IT skills, which are core skills for data analysts and engineers
Examines a public COVID-19 dataset and uses SendGrid, which are highly relevant to data analysis
Offers hands-on labs and interactive materials, providing practical experience
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