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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. This lab will teach you how to use the Pipeline Studio in Cloud Data Fusion to build an ETL pipeline. Pipeline Studio exposes the building blocks and built-in plugins for you to build your batch pipeline, one node at a time. You will also use the Wrangler plugin to build and apply transformations to your data that goes through the pipeline.
Register for this course and see more details by visiting:
OpenCourser.com/course/ud837t/building
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What's inside
Syllabus
Building Batch Pipelines in Cloud Data Fusion
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the use of Google Cloud Platform's Pipeline Studio to create an ETL pipeline
Uses the Google Cloud console for practical application
Emphasizes hands-on learning through the use of the Wrangler plugin for transformation building
Suitable for individuals with some familiarity with data pipelines and cloud computing concepts
May require additional resources or external research for beginners
Targeted towards individuals interested in cloud-based data integration and transformation
Save this course
Save Building Batch Pipelines in Cloud Data Fusion 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 Building Batch Pipelines in Cloud Data Fusion with these
activities:
Review ETL concepts and methodologies
Show steps
Refresh your understanding of ETL processes to enhance your ability to design and implement data pipelines.
Browse courses on
ETL
Show steps
-
Review the basics of data integration and ETL processes
-
Understand the different types of data sources and their characteristics
-
Explore common data transformation techniques and best practices
-
Learn about data quality and validation techniques
-
Understand the concepts of data lineage and data governance
Review basic SQL concepts
Show steps
Strengthen your SQL foundation to prepare for the course.
Browse courses on
SQL
Show steps
-
Review basic SQL syntax and data types
-
Practice writing simple SELECT, INSERT, UPDATE, and DELETE queries
-
Understand the concepts of joins, subqueries, and aggregation functions
-
Use an online SQL editor or practice tool to solidify your skills
Participate in a peer-led study group
Show steps
Collaborate with peers to discuss concepts, work through problems, and enhance your understanding through collective learning.
Show steps
-
Form or join a study group with other students enrolled in the course
-
Establish regular meeting times and decide on a meeting format
-
Take turns leading discussions, presenting concepts, and facilitating peer feedback
-
Work together to complete assignments, solve problems, and prepare for assessments
-
Seek support and guidance from each other as needed
Four other activities
Expand to see all activities and additional details
Show all seven activities
Build a Cloud Data Fusion pipeline using a tutorial
Show steps
Follow a guided tutorial to create a pipeline and reinforce your understanding.
Show steps
-
Identify a suitable tutorial
-
Set up your environment and follow the tutorial steps
-
Review the code and concepts explained in the tutorial
-
Experiment with different pipeline configurations
-
Troubleshoot any issues you encounter
Build batch pipelines with Cloud Data Fusion ETL
Show steps
Build batch pipelines to enhance your understanding of data transformation and integration.
Show steps
-
Set up a Cloud Data Fusion environment
-
Create a new batch pipeline
-
Add data sources and data sinks to your pipeline
-
Use transformations to clean and prepare your data
-
Run your pipeline and examine the results
Build a visual data transformation pipeline story
Show steps
Develop a comprehensive visual narrative that showcases your data transformation and visualization skills. This can be done through a dashboard, presentation, or interactive data story.
Browse courses on
Data Transformation
Show steps
-
Gather data from multiple sources
-
Clean and transform the data to highlight insights
-
Design and create visualizations that effectively communicate the data story
-
Integrate the visualizations into a coherent and engaging narrative
-
Publish and share your data story with stakeholders
Contribute to the Cloud Data Fusion open-source community
Show steps
Engage with the open-source community to deepen your understanding and make meaningful contributions.
Show steps
-
Familiarize yourself with the Cloud Data Fusion open-source repositories
-
Identify areas where you can contribute based on your interests and skills
-
Submit bug reports or feature requests
-
Review and comment on code changes proposed by others
-
Contribute your own code changes to improve the project
Review ETL concepts and methodologies
Show steps
Refresh your understanding of ETL processes to enhance your ability to design and implement data pipelines.
Browse courses on
ETL
Show steps
Show steps
Show steps
- Review the basics of data integration and ETL processes
- Understand the different types of data sources and their characteristics
- Explore common data transformation techniques and best practices
- Learn about data quality and validation techniques
- Understand the concepts of data lineage and data governance
Review basic SQL concepts
Show steps
Strengthen your SQL foundation to prepare for the course.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review basic SQL syntax and data types
- Practice writing simple SELECT, INSERT, UPDATE, and DELETE queries
- Understand the concepts of joins, subqueries, and aggregation functions
- Use an online SQL editor or practice tool to solidify your skills
Participate in a peer-led study group
Show steps
Collaborate with peers to discuss concepts, work through problems, and enhance your understanding through collective learning.
Show steps
Show steps
Show steps
- Form or join a study group with other students enrolled in the course
- Establish regular meeting times and decide on a meeting format
- Take turns leading discussions, presenting concepts, and facilitating peer feedback
- Work together to complete assignments, solve problems, and prepare for assessments
- Seek support and guidance from each other as needed
Four other activities
Expand to see all activities and additional details
Show all seven activities
Build a Cloud Data Fusion pipeline using a tutorial
Show steps
Follow a guided tutorial to create a pipeline and reinforce your understanding.
Show steps
Show steps
Show steps
- Identify a suitable tutorial
- Set up your environment and follow the tutorial steps
- Review the code and concepts explained in the tutorial
- Experiment with different pipeline configurations
- Troubleshoot any issues you encounter
Build batch pipelines with Cloud Data Fusion ETL
Show steps
Build batch pipelines to enhance your understanding of data transformation and integration.
Show steps
Show steps
Show steps
- Set up a Cloud Data Fusion environment
- Create a new batch pipeline
- Add data sources and data sinks to your pipeline
- Use transformations to clean and prepare your data
- Run your pipeline and examine the results
Build a visual data transformation pipeline story
Show steps
Develop a comprehensive visual narrative that showcases your data transformation and visualization skills. This can be done through a dashboard, presentation, or interactive data story.
Browse courses on
Data Transformation
Show steps
Show steps
Show steps
- Gather data from multiple sources
- Clean and transform the data to highlight insights
- Design and create visualizations that effectively communicate the data story
- Integrate the visualizations into a coherent and engaging narrative
- Publish and share your data story with stakeholders
Contribute to the Cloud Data Fusion open-source community
Show steps
Engage with the open-source community to deepen your understanding and make meaningful contributions.
Show steps
Show steps
Show steps
- Familiarize yourself with the Cloud Data Fusion open-source repositories
- Identify areas where you can contribute based on your interests and skills
- Submit bug reports or feature requests
- Review and comment on code changes proposed by others
- Contribute your own code changes to improve the project
Career center
Learners who complete Building Batch Pipelines in Cloud Data Fusion will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines that collect, transform, and store data for use by data analysts and other stakeholders. They work with a variety of data sources and technologies to ensure that data is accurate, reliable, and accessible. The Building Batch Pipelines in Cloud Data Fusion course will introduce you to the concepts and technologies used in data engineering, such as data integration, data transformation, and data warehousing. This course can help you acquire the skills you need to succeed in this role.
Data Analyst
Data Analyst
Data Analysts analyze data to uncover meaningful insights and trends that drive decision-making within an organization. They use their skills to help businesses understand their customers, improve operations, and make more informed decisions. The Building Batch Pipelines in Cloud Data Fusion course can help you develop the skills you need to succeed in this role, such as data wrangling, data transformation, and data analysis.
Data Scientist
Data Scientist
Data Scientists are responsible for developing and implementing machine learning algorithms to solve business problems. They work with data engineers to access and prepare data, and with data analysts to interpret results. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Data Scientists, as it can teach the fundamentals of data engineering and data analysis. This course can help you build a foundation in data management and prepare you for more advanced roles in data science.
Database Administrator
Database Administrator
Database Administrators are responsible for the installation, configuration, maintenance, and security of databases. They work with database users to ensure that they have access to the data they need and that the database is performing optimally. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Database Administrators, as it can teach the fundamentals of data management and data security. This course can help Database Administrators build a foundation in data management and prepare them for more advanced roles in database administration.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems using data and analysis. They work with stakeholders to understand their needs and develop solutions that meet those needs. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Business Analysts, as it can teach the fundamentals of data analysis and data management. This course may be particularly relevant for Business Analysts who work with data-intensive applications.
Data Architect
Data Architect
Data Architects design and implement data management solutions that meet the needs of an organization. They work with stakeholders to understand their data requirements and develop solutions that are scalable, reliable, and secure. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Data Architects, as it can help them understand the fundamentals of data engineering and data management. This course can help Data Architects build a foundation in data management and prepare them for more advanced roles in data architecture.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with stakeholders to understand their needs and develop solutions that meet those needs. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Software Engineers, as it can teach the fundamentals of data engineering and data management. This course can help Software Engineers build a foundation in data management and prepare them for more advanced roles in software engineering, particularly in roles that involve data-intensive applications.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to help businesses and organizations make informed decisions. They use their skills to identify trends, patterns, and relationships in data. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Statisticians, as it can teach the fundamentals of data analysis and data management. This course can help Statisticians build a foundation in data management and prepare them for more advanced roles in statistics.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze and evaluate financial performance. They work with stakeholders to identify opportunities and develop strategies to improve financial performance. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Financial Analysts, as it can teach the fundamentals of data analysis and data management. This course can help Financial Analysts build a foundation in data management and prepare them for more advanced roles in financial analysis.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve business problems. They work with stakeholders to identify problems and develop solutions that improve efficiency and productivity. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Operations Research Analysts, as it can teach the fundamentals of data analysis and data management. This course can help Operations Research Analysts build a foundation in data management and prepare them for more advanced roles in operations research.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to help stakeholders understand and communicate insights. They work with data analysts and other stakeholders to identify the most effective ways to visualize data. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Data Visualization Specialists, as it can teach the fundamentals of data analysis and data management. This course can help Data Visualization Specialists build a foundation in data management and prepare them for more advanced roles in data visualization.
Data Quality Analyst
Data Quality Analyst
Data Quality Analysts ensure that data is accurate, complete, and consistent. They work with stakeholders to identify data quality requirements and develop solutions that meet those requirements. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Data Quality Analysts, as it can teach the fundamentals of data management and data quality. This course can help Data Quality Analysts build a foundation in data management and prepare them for more advanced roles in data quality.
Market Research Analyst
Market Research Analyst
Market Research Analysts collect, analyze, and interpret data to help businesses understand their customers and make informed decisions. They use their skills to identify market opportunities and develop strategies to reach target audiences. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Market Research Analysts, as it can teach the fundamentals of data analysis and data management. This course can help Market Research Analysts build a foundation in data management and prepare them for more advanced roles in market research.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement policies and procedures to ensure that data is managed in a consistent and reliable manner. They work with stakeholders to identify data governance requirements and develop solutions that meet those requirements. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Data Governance Analysts, as it can teach the fundamentals of data management and data security. This course can help Data Governance Analysts build a foundation in data management and prepare them for more advanced roles in data governance.
Data Warehouse Manager
Data Warehouse Manager
Data Warehouse Managers are responsible for the planning, implementation, and maintenance of data warehouses. They work with stakeholders to identify data warehouse requirements and develop solutions that meet those requirements. The Building Batch Pipelines in Cloud Data Fusion course may be helpful for aspiring Data Warehouse Managers, as it can teach the fundamentals of data management and data warehousing. This course can help Data Warehouse Managers build a foundation in data management and prepare them for more advanced roles in data warehousing.
For more career information including salaries, visit:
OpenCourser.com/course/ud837t/building
Reading list
We've selected nine 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 Batch Pipelines in Cloud Data Fusion.
Provides a comprehensive guide to Apache Spark. It covers everything from the basics of Spark to advanced topics such as optimization and tuning. It valuable resource for anyone who wants to learn more about Spark.
Provides a comprehensive overview of machine learning for data pipelines. It covers everything from the basics of machine learning to advanced topics such as feature engineering and model deployment. It valuable resource for anyone who wants to learn more about machine learning for data pipelines.
Provides a comprehensive overview of big data analytics. It covers everything from the basics of big data to advanced topics such as machine learning and artificial intelligence. It valuable resource for anyone who wants to learn more about big data analytics.
Provides a comprehensive guide to machine learning with R. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning. It also includes case studies and examples from real-world machine learning projects.
Provides a comprehensive guide to deep learning with Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. It also includes case studies and examples from real-world deep learning projects.
Provides a comprehensive guide to natural language processing with Python. It covers topics such as tokenization, stemming, lemmatization, and parsing. It also includes case studies and examples from real-world natural language processing projects.
Provides a comprehensive guide to data visualization with Python. It covers topics such as data exploration, data visualization, and interactive data visualization. It also includes case studies and examples from real-world data visualization projects.
Save
Provides a comprehensive guide to data science with Python. It covers topics such as data exploration, data analysis, and data modeling. It also includes case studies and examples from real-world data science projects.
Provides a comprehensive guide to machine learning for data science. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning. It also includes case studies and examples from real-world machine learning projects.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ud837t/building
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Effort
1 hour 30 minutes
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Teaches the use of Google Cloud Platform's Pipeline Studio to create an ETL pipeline
Uses the Google Cloud console for practical application
Emphasizes hands-on learning through the use of the Wrangler plugin for transformation building
Suitable for individuals with some familiarity with data pipelines and cloud computing concepts
May require additional resources or external research for beginners
Targeted towards individuals interested in cloud-based data integration and transformation
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