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Google Cloud Training
In this Google Cloud Labs Series, learners get hands-on practice on the more advanced data integration features available in Cloud Data Fusion, while sharing best practices to build more robust, reusable, dynamic pipelines. Learners get to try out the data lineage feature as well to derive interesting insights into their data’s history. Note: you will have timed access to the online environment. You will need to complete the lab within the allotted time.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers advanced features of a service that is standard in data integration
Taught by instructors from Google Cloud Training, a highly reputable institution
Develops data integration pipelines, which are core skills for data engineers
Examines data lineage, which is a highly relevant topic in data integration
Offers hands-on practice in a timed online environment, which replicates a realistic work setting

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Reviews summary

Effectively learning advanced cloud data fusion

This course is well received by learners and students. One reviewer mentioned that this course could use more in depth exploration of the more common nodes including add-ons in order to get the most out of this ETL tool.
This course provides opportunities for hands-on codeless learning.
"In this Google Cloud Labs Series, learners get hands-on practice on the more advanced data integration features available in Cloud Data Fusion..."
Timed access to online environment.
"Note: you will have timed access to the online environment."
The course could include more common node exploration.
"...se requiere profundizar más para el uso de los nodos mas comunes..."

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 Advanced Codeless Pipelines on Cloud Data Fusion with these activities:
Review data integration concepts
Strengthen foundational knowledge of data integration concepts before starting the course for a smoother learning journey.
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  • Go over the basics of data integration, including its benefits and challenges.
  • Review different data integration tools and technologies, including Cloud Data Fusion.
  • Study data pipeline concepts, such as data ingestion, transformation, and data quality.
Navigate BigQuery using the Google Cloud Console
Familiarize yourself with BigQuery environment to be prepared for assignments and practice
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Show steps
  • Sign in to the Google Cloud Console and create a new BigQuery project
  • Create a dataset and a table
  • Load data into the table
  • Query the data
  • Visualize the data using BigQuery's built-in visualization tool
Join a Study Group
Engage in peer-to-peer learning by joining a study group where you can discuss course concepts, share insights, and support each other.
Show steps
  • Find or start a study group with fellow learners.
  • Meet regularly to discuss course material, work on exercises together, and clarify concepts.
21 other activities
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Complete Cloud Data Fusion tutorials
Gain hands-on experience with Cloud Data Fusion through guided tutorials to reinforce the concepts learned in the course.
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  • Find and follow official Cloud Data Fusion tutorials provided by Google.
  • Work through the tutorials step-by-step, completing all the exercises and activities.
  • Troubleshoot any issues you encounter during the tutorials.
Explore Cloud Data Fusion Tutorials
Enhance your understanding of Cloud Data Fusion by working through official tutorials that provide step-by-step guidance.
Browse courses on Cloud Data Fusion
Show steps
  • Choose a tutorial that aligns with your interests.
  • Follow the instructions carefully.
  • Experiment with the code and configurations provided.
Hands-On Practice: Implementing Data Fusion Pipelines
Bolster your understanding of advanced data integration concepts by getting hands-on experience with Cloud Data Fusion. This activity will solidify your grasp of building robust and reusable pipelines.
Browse courses on Data Integration
Show steps
  • Follow the lab instructions to set up your environment.
  • Create a data integration pipeline using the provided dataset.
  • Explore the data lineage feature to trace the history and relationships of your data.
Complete Codelabs on Cloud Data Fusion
Reinforce your hands-on experience by completing guided codelabs that demonstrate Cloud Data Fusion's capabilities.
Show steps
  • Follow the step-by-step instructions provided in the codelabs.
  • Experiment with different data sources and transformations.
  • Troubleshoot any issues encountered during the exercises.
Join a Study Group for Cloud Data Fusion
Enhance your learning by collaborating with peers, sharing knowledge, and discussing course concepts.
Show steps
  • Find or create a study group for Cloud Data Fusion.
  • Attend regular study sessions and actively participate in discussions.
  • Share your knowledge and help other group members.
Use BigQuery for Business Analysis
Apply hands-on, real-world BigQuery practices from data ingestion to visualization
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Show steps
  • Define the business problem and gather the necessary data
  • Load the data into BigQuery
  • Explore and analyze the data using BigQuery's tools
  • Build a data model to represent the business problem
  • Create visualizations to present the results of the analysis
Join a study group or discussion forum
Engage with peers and experts to discuss course concepts, share knowledge, and get support throughout your learning journey.
Browse courses on Data Integration
Show steps
  • Find and join a study group or discussion forum related to data integration.
  • Participate actively in discussions, ask questions, and share your insights.
  • Collaborate with other members on projects or assignments.
Practice Data Integration Exercises
Sharpen your data integration skills by completing practice exercises that reinforce what you learn in the course.
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Show steps
  • Follow along with the provided exercises.
  • Experiment with different data sources and transformations.
  • Troubleshoot any issues you encounter.
Organize and review course materials
Enhance understanding by organizing and regularly reviewing course materials, ensuring better retention and recall of key concepts.
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Show steps
  • Gather all the course materials, including lecture notes, assignments, and readings.
  • Create a system for organizing the materials, such as folders or a digital notebook.
  • Review the materials regularly, especially before and after each lecture.
Collaborative Pipeline Development Workshop
Enhance your learning by collaborating with peers in a guided workshop. This activity will provide you with diverse perspectives and foster a deeper understanding of data integration techniques.
Browse courses on Cloud Data Fusion
Show steps
  • Join a workshop led by an experienced facilitator.
  • Work in teams to develop a data integration pipeline.
  • Present your pipeline and gather feedback from peers.
Connect with Cloud Data Fusion Experts
Seek guidance and support from experienced professionals in the field of Cloud Data Fusion.
Show steps
  • Identify potential mentors through online forums or professional networks.
  • Reach out to mentors and express your interest in learning from them.
  • Schedule regular meetings or conversations to discuss Cloud Data Fusion and your career goals.
Discuss BigQuery Features and Best Practices
Engage with peers and discuss industry applications, optimizing BigQuery usage and troubleshooting
Browse courses on BigQuery
Show steps
  • Connect with other students taking the Google Cloud Labs Series
  • Schedule a virtual or in-person meeting
  • Discuss BigQuery features and best practices
  • Share tips and tricks
  • Collaborate on a small project using BigQuery
Write a blog post on Data Lineage
Deepen your understanding of data lineage by creating a blog post that explains its benefits and implementation.
Show steps
  • Research data lineage concepts and techniques.
  • Identify a practical example of data lineage in Cloud Data Fusion.
  • Write a blog post explaining the example and its benefits.
Practice data integration scenarios
Enhance problem-solving skills by practicing data integration scenarios and applying the techniques learned in the course.
Browse courses on Data Integration
Show steps
  • Identify real-world data integration scenarios that you can work on.
  • Design and implement data pipelines using Cloud Data Fusion to address the scenarios.
  • Evaluate the performance of your data pipelines and make improvements as needed.
Create a Data Integration Pipeline Project
Apply your knowledge by creating a real-world data integration pipeline project that demonstrates your skills.
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Show steps
  • Identify a business problem or use case that requires data integration.
  • Design the data integration architecture, including data sources, transformations, and output.
  • Implement the pipeline in Cloud Data Fusion.
  • Test and validate the pipeline.
  • Deploy and monitor the pipeline.
Design and Document a Complex Data Integration Architecture
Deepen your understanding of data integration principles by designing and documenting a complex data integration architecture. This activity will help you apply your knowledge to real-world scenarios.
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Show steps
  • Identify the data sources and their relationships.
  • Design a data integration architecture that meets specific requirements.
  • Document your architecture, including data flow, transformations, and security measures.
Explore Advanced Features in Cloud Data Fusion
Expand your knowledge by following tutorials that cover advanced features such as dynamic schema and data quality rules.
Show steps
  • Find tutorials on Cloud Data Fusion's advanced features.
  • Follow the tutorials to learn about these features.
  • Apply the learned concepts in your own projects.
Build a Data Pipeline with Cloud Data Fusion
Apply your learning by building a real-world data pipeline that integrates multiple data sources and performs complex transformations.
Show steps
  • Define the scope and requirements of your data pipeline.
  • Design the pipeline architecture and data flow.
  • Implement the pipeline using Cloud Data Fusion.
  • Test and validate the pipeline's functionality.
  • Deploy and monitor the pipeline.
Review advanced data integration concepts
Expand knowledge and understanding by reviewing advanced data integration concepts, enriching your comprehension of the subject matter.
Browse courses on Data Integration
Show steps
  • Identify advanced data integration concepts that are relevant to the course.
  • Find resources such as articles, books, or online courses that cover these concepts.
  • Study the materials and take notes to enhance your understanding.
Build a data integration project
Showcase your skills by building a data integration project that solves a real-world problem and demonstrates your understanding of the course concepts.
Browse courses on Data Integration
Show steps
  • Define the scope and objectives of your project.
  • Gather and prepare the necessary data for your project.
  • Design and implement a data pipeline using Cloud Data Fusion to integrate the data.
  • Analyze the results of your data integration and draw insights.
  • Present your project and findings to others.
Mentor junior data engineers
Solidify your understanding by sharing your knowledge and skills with others, reinforcing your own comprehension and enhancing your communication abilities.
Browse courses on Data Integration
Show steps
  • Identify opportunities to mentor junior data engineers, such as through online forums or volunteering.
  • Provide guidance and support to mentees on data integration topics.
  • Share your experiences and insights to help mentees learn and grow.

Career center

Learners who complete Building Advanced Codeless Pipelines on Cloud Data Fusion will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers are responsible for designing, building, and maintaining data pipelines. They work closely with data scientists and analysts to ensure that the data used for analysis is accurate, complete, and timely. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Engineers learn how to use Cloud Data Fusion to build more robust, reusable, dynamic pipelines.
Business Analyst
Business Analysts are responsible for understanding the business needs of an organization and translating those needs into technical requirements. They work with stakeholders to gather and analyze data and develop solutions to business problems. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Business Analysts learn how to use Cloud Data Fusion to build more effective data pipelines that meet the needs of the business.
Data Architect
Data Architects are responsible for designing and managing the architecture of data systems. They work with stakeholders to understand their data needs and design systems that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Architects learn how to use Cloud Data Fusion to build more scalable, reliable, and secure data systems.
Data Scientist
Data Scientists are responsible for using data to solve business problems. They work with data engineers and analysts to collect, clean, and analyze data. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Scientists learn how to use Cloud Data Fusion to build more efficient and effective data pipelines.
Data Integration Specialist
Data Integration Specialists are responsible for designing and implementing data integration solutions. They work with stakeholders to understand their data integration needs and develop solutions that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Integration Specialists learn how to use Cloud Data Fusion to build more scalable, reliable, and secure data integration solutions.
Cloud Architect
Cloud Architects are responsible for designing and managing the architecture of cloud computing systems. They work with stakeholders to understand their cloud needs and design systems that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Cloud Architects learn how to use Cloud Data Fusion to build more scalable, reliable, and secure cloud systems.
Data Governance Specialist
Data Governance Specialists are responsible for developing and implementing data governance policies and procedures. They work with stakeholders to understand their data governance needs and develop policies and procedures that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Governance Specialists learn how to use Cloud Data Fusion to build more effective data governance policies and procedures.
Data Security Analyst
Data Security Analysts are responsible for protecting the security of data. They work with stakeholders to understand their data security needs and develop policies and procedures to protect data. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Security Analysts learn how to use Cloud Data Fusion to build more secure data pipelines.
DevOps Engineer
DevOps Engineers are responsible for building and maintaining the software development and deployment process. They work with stakeholders to understand their software development and deployment needs and develop processes that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help DevOps Engineers learn how to use Cloud Data Fusion to build more efficient and effective software development and deployment processes.
IT Manager
IT Managers are responsible for managing the IT infrastructure of an organization. They work with stakeholders to understand their IT needs and develop plans to meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help IT Managers learn how to use Cloud Data Fusion to build more efficient and effective IT systems.
Data Quality Analyst
Data Quality Analysts are responsible for assessing the quality of data. They work with stakeholders to understand their data quality needs and develop metrics to measure data quality. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Quality Analysts learn how to use Cloud Data Fusion to build more effective data quality pipelines.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software systems. They work with stakeholders to understand their software needs and develop systems that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Software Engineers learn how to use Cloud Data Fusion to build more efficient and effective software systems.
Systems Analyst
Systems Analysts are responsible for analyzing and designing business systems. They work with stakeholders to understand their business needs and design systems that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Systems Analysts learn how to use Cloud Data Fusion to build more efficient and effective business systems.
Database Administrator
Database Administrators are responsible for managing the databases of an organization. They work with stakeholders to understand their data needs and design databases that meet those needs. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Database Administrators learn how to use Cloud Data Fusion to build more scalable, reliable, and secure databases.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data. They work with stakeholders to understand their data needs and develop insights from data. The Building Advanced Codeless Pipelines on Cloud Data Fusion course can help Data Analysts learn how to use Cloud Data Fusion to build more efficient and effective data pipelines.

Reading list

We've selected 11 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 Advanced Codeless Pipelines on Cloud Data Fusion.
Comprehensive overview of machine learning in Chinese. It would be a valuable resource for Chinese-speaking learners who want to learn more about the algorithms and techniques used in data integration.
Provides a comprehensive overview of data manipulation with R. It would be a valuable resource for learners who want to learn more about the tools and techniques used in data integration.
Provides a comprehensive overview of data analysis with Python. It would be a valuable resource for learners who want to learn more about the tools and techniques used in data integration.
Provides a comprehensive overview of data mining. It would be a valuable resource for learners who want to learn more about the algorithms and techniques used in data integration.
Provides a business-oriented introduction to data science. It would be useful for learners who want to understand how data science can be used to solve business problems.
Practical guide to machine learning in Chinese. It would be useful for Chinese-speaking learners who want to gain a practical understanding of the tools and techniques used in data integration.
Comprehensive overview of deep learning in Chinese. It would be a valuable resource for Chinese-speaking learners who want to learn more about the algorithms and techniques used in data integration.
Provides a practical introduction to data visualization. It would be useful for learners who want to learn more about how to communicate data insights effectively.
Provides a comprehensive guide to data integration with Microsoft Azure. It covers topics such as data modeling, data cleansing, and data governance. It valuable resource for anyone who wants to learn more about data integration with Microsoft Azure.
Provides a comprehensive overview of data warehousing. It covers topics such as data modeling, data storage, and data retrieval. It valuable resource for anyone who wants to learn more about data warehousing.
Provides a comprehensive overview of data integration tools and techniques. It covers topics such as data extraction, data transformation, and data loading. It valuable resource for anyone who wants to learn more about data integration tools and techniques.

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