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Building Dynamic Pipelines in Cloud Data Fusion Using Macros
Google Cloud Training
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/kgrqeb/building
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
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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Building Dynamic Pipelines in Cloud Data Fusion Using Macros.
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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
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
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
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
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
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
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
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
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
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
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.
For more career information including salaries, visit:
OpenCourser.com/course/kgrqeb/building
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.
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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.
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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.
Provides valuable insights into the principles and techniques of microservice architecture, which is essential for designing dynamic pipelines.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/kgrqeb/building
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Institution
Google Cloud
Instructor
Google Cloud Training
Good to know
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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