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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to use macros in Data Fusion that introduce dynamic variables to plugin configurations so that you can specify the variable substitutions at runtime.
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Provides learners with a hands-on learning experience through self-paced labs that take place in the Google Cloud Console
Teaches learners how to use macros in Data Fusion, which allows for the introduction of dynamic variables to plugin configurations and the specification of variable substitutions at runtime
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Intended for learners with some experience in data engineering, as it assumes familiarity with Data Fusion

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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 Dynamic Pipelines in Cloud Data Fusion Using Macros with these activities:
Review Python basics
This activity will refresh your knowledge of Python fundamentals, ensuring that you have a solid foundation for the course.
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Show steps
  • Review Python syntax and data structures.
  • Practice writing simple Python programs.
Watch Video Tutorials on Data Fusion Macros
Watch video tutorials on Data Fusion macros to gain a visual understanding of how they are used in practice.
Browse courses on Data Fusion
Show steps
  • Search for video tutorials on Data Fusion macros
  • Watch the tutorials and take notes
  • Practice using macros in your own Data Fusion projects
Review Data Fusion Documentation on Macros
Review the official Data Fusion documentation on macros to reinforce your understanding of their functionality and best practices.
Browse courses on Data Fusion
Show steps
  • Access the Data Fusion documentation
  • Read the sections on macros
  • Take notes on key concepts and examples
Nine other activities
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Show all 12 activities
Follow tutorials on Data Fusion macros
This activity will guide you through the use of macros in Data Fusion, allowing you to gain hands-on experience and deepen your understanding.
Show steps
  • Find tutorials on Data Fusion macros.
  • Follow the tutorials step-by-step.
  • Try out the examples provided in the tutorials.
Practice Using Macros in Data Fusion Lab
Practice using macros in the Data Fusion lab environment to reinforce your understanding and solidify your skills.
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Show steps
  • Set up the Data Fusion lab environment
  • Follow the lab instructions to create macros
  • Run your macros and observe the results
  • Experiment with different macro configurations
Practice Creating Dynamic Variables in Data Fusion
Practice creating dynamic variables in Data Fusion to improve your understanding of how to use them in plugin configurations.
Browse courses on Data Fusion
Show steps
  • Create a new Data Fusion pipeline
  • Add a plugin to the pipeline
  • Create a dynamic variable in the plugin configuration
  • Run the pipeline and observe the results
  • Experiment with different dynamic variable configurations
Practice using macros in Data Fusion pipelines
This activity will provide you with an opportunity to apply your knowledge of macros by building your own Data Fusion pipelines.
Show steps
  • Design a Data Fusion pipeline that utilizes macros.
  • Implement the pipeline.
  • Test the pipeline and analyze the results.
Mentor Junior Data Engineers on Macros
Mentor junior data engineers on how to use macros effectively in Data Fusion, sharing your knowledge and helping them grow their skills.
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Show steps
  • Identify opportunities to mentor junior data engineers
  • Share your knowledge and experience on macros
  • Provide guidance and support
  • Review their work and provide feedback
Create a Data Fusion Project Using Macros
Create a Data Fusion project that utilizes macros to automate tasks and improve efficiency.
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Show steps
  • Design your Data Fusion project
  • Identify opportunities to use macros
  • Create and configure macros
  • Implement macros in your pipelines
  • Test and evaluate your project
Build a Data Fusion pipeline that leverages macros
This activity will challenge you to create a real-world Data Fusion pipeline that leverages macros, solidifying your understanding and showcasing your skills.
Show steps
  • Define the problem or business need.
  • Design the Data Fusion pipeline architecture.
  • Implement the pipeline using macros.
  • Test and evaluate the pipeline.
  • Document the pipeline.
Attend a Data Fusion meetup or workshop
This activity will connect you with other professionals in the field, providing you with opportunities to learn from their experiences and exchange ideas.
Browse courses on Data Fusion
Show steps
  • Research upcoming Data Fusion meetups or workshops.
  • Register and attend the event.
  • Network with other attendees.
Contribute to the Data Fusion open-source community
This activity will give you hands-on experience with Data Fusion and allow you to contribute to its development, deepening your understanding of the technology and its applications.
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Show steps
  • Find a Data Fusion open-source project.
  • Identify an area where you can contribute.
  • Submit a pull request.
  • Review and discuss your contribution with the community.

Career center

Learners who complete Building Dynamic Pipelines in Cloud Data Fusion Using Macros will develop knowledge and skills that may be useful to these careers:
Data Engineer
A Data Engineer plans, designs, builds, tests, deploys, maintains, and monitors data pipelines and related infrastructure. They may also analyze and interpret data, and develop and implement data science solutions. This course may be useful for a Data Engineer because it teaches how to use macros in Data Fusion that introduce dynamic variables to plugin configurations so that you can specify the variable substitutions at runtime.
Data Analyst
A Data Analyst uses their knowledge of data and analytical techniques to transform raw data into meaningful insights and reports. They may also work with stakeholders to identify data needs, develop data models, and create visualizations.
Cloud Architect
A Cloud Architect designs, builds, and manages cloud computing systems. They may also work with stakeholders to identify cloud needs, develop cloud strategies, and implement cloud solutions.
Software Engineer
A Software Engineer designs, develops, tests, and maintains software systems. They may also work with stakeholders to identify software needs, develop software requirements, and implement software solutions.
Database Administrator
A Database Administrator manages and maintains databases. They may also work with stakeholders to identify database needs, develop database strategies, and implement database solutions.
Data Scientist
A Data Scientist uses their knowledge of data and machine learning techniques to develop and implement data science solutions. They may also work with stakeholders to identify data science needs, develop data science models, and create data science visualizations.
Machine Learning Engineer
A Machine Learning Engineer uses their knowledge of machine learning techniques to develop and implement machine learning solutions. They may also work with stakeholders to identify machine learning needs, develop machine learning models, and create machine learning visualizations.
Business Analyst
A Business Analyst uses their knowledge of business and analytical techniques to analyze business needs, identify business problems, and develop business solutions.
Project Manager
A Project Manager plans, organizes, and executes projects. They may also work with stakeholders to identify project needs, develop project plans, and implement project solutions.
Technical Writer
A Technical Writer creates and maintains technical documentation. They may also work with stakeholders to identify documentation needs, develop documentation plans, and implement documentation solutions.

Reading list

We've selected six 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 Dynamic Pipelines in Cloud Data Fusion Using Macros.
Provides a deep dive into the principles and practices of designing data-intensive applications, offering a solid foundation for understanding the broader context of data pipelines.
Covers best practices and techniques for writing clear and efficient Python code, which is essential for building and maintaining data pipelines.
Provides a comprehensive overview of data engineering and how to use Python to build data pipelines. It covers topics such as data ingestion, data transformation, data movement, and data analysis.
Provides a comprehensive overview of data pipelines and how to build them using Google Cloud Platform. It covers topics such as data ingestion, data transformation, data movement, and data analysis.
Provides a comprehensive overview of data lakes and how to use them to build data-driven applications. It covers topics such as data ingestion, data storage, data processing, and data analysis.

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