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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 examine how Dataprep can be used on complicated data structures in BigQuery.

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What's inside

Syllabus

Automating your BigQuery Data Pipeline with Cloud Dataprep

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Automates the BigQuery data pipeline with Cloud Dataprep, a valuable skill in data management and analysis
Leverages Google Cloud console for the lab component, providing hands-on experience with tools and platforms used in the industry
Designed for learners with knowledge of BigQuery and data manipulation, making it suitable for intermediate to advanced learners
May require prior experience in working with structured and semi-structured data, which may limit accessibility for beginners

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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 Automating your BigQuery Data Pipeline with Cloud Dataprep with these activities:
Review SQL basics
Revisit SQL to strengthen your foundation and ensure a smoother learning experience in this course.
Browse courses on SQL
Show steps
  • Review online tutorials or documentation on SQL syntax and concepts.
  • Practice writing basic SQL queries using an online SQL editor or tool.
Join a Study Group or Discussion Forum
Engage with other learners to share knowledge, discuss concepts, and clarify doubts.
Show steps
  • Identify online or in-person study groups or discussion forums related to this course.
  • Join the group and actively participate in discussions.
  • Ask questions, share insights, and collaborate with other learners.
Explore Dataprep tutorials
Familiarize yourself with the capabilities of Dataprep by following guided tutorials provided by Google Cloud.
Browse courses on Dataprep
Show steps
  • Visit the Google Cloud Dataprep documentation and explore the available tutorials.
  • Complete the tutorial on transforming complex data structures in BigQuery.
  • Optional: Explore additional tutorials on topics that align with your interests or learning goals.
Four other activities
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Show all seven activities
Practice Data Transformation Exercises
Reinforce your understanding of data transformation techniques by completing hands-on exercises.
Browse courses on Data Transformation
Show steps
  • Find online resources or platforms that provide data transformation exercises.
  • Select exercises that cover topics relevant to this course, such as working with nested and complex data structures.
  • Complete the exercises and review your results to identify areas for improvement.
Read 'Data Wrangling with Python'
Expand your knowledge of data wrangling techniques with a comprehensive book that covers Python-based solutions.
Show steps
  • Obtain a copy of the book.
  • Read through the chapters relevant to data wrangling and transformation.
  • Optional: Complete the exercises and examples provided in the book.
Develop a Data Pipeline with Cloud Dataprep
Apply your skills to a practical project by creating a data pipeline that utilizes Cloud Dataprep for data transformation.
Browse courses on Data Pipeline
Show steps
  • Define the scope and purpose of your data pipeline.
  • Design the data flow and transformation logic using Cloud Dataprep.
  • Implement and test the data pipeline.
  • Document and share your findings.
Contribute to the Cloud Dataprep Community
Deepen your understanding of Dataprep and contribute to the community by participating in open-source projects.
Show steps
  • Explore open-source projects related to Cloud Dataprep on platforms like GitHub.
  • Identify areas where you can contribute, such as bug fixes or feature enhancements.
  • Submit your contributions and engage with the community.

Career center

Learners who complete Automating your BigQuery Data Pipeline with Cloud Dataprep will develop knowledge and skills that may be useful to these careers:
Big Data Engineer
A Big Data Engineer is responsible for designing and managing big data systems. With the help of Cloud Dataprep, this course could help you to automate your BigQuery data pipeline. This could lead to a more efficient and streamlined data management process.
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data. This course could help you to automate your BigQuery data pipeline and improve the quality of your data analysis.
Data Engineer
A Data Engineer is responsible for designing and managing data pipelines. This course could help you to automate your BigQuery data pipeline in order to more efficiently manage your data.
Data Scientist
A Data Scientist is responsible for developing and applying statistical models to data. This course could help you to automate your BigQuery data pipeline and improve the accuracy of your models.
Database Administrator
A DBA is responsible for managing and maintaining databases. This course could help you to automate your BigQuery data pipeline and improve the performance of your database.
DevOps Engineer
A DevOps Engineer is responsible for bridging the gap between development and operations. This course may help you to automate your BigQuery data pipeline, which could help you to streamline your DevOps processes.
Software Engineer
A Software Engineer is responsible for designing and developing software applications. This course may help you to automate your BigQuery data pipeline, which in turn could help streamline your software development process.
Systems Engineer
A Systems Engineer is responsible for designing and managing computer systems. This course may help you to automate your BigQuery data pipeline, which could help ensure that your systems are running at peak efficiency.
Data Architect
A Data Architect is responsible for designing and managing data architectures. This course may help you to automate your BigQuery data pipeline, which could help you to create a more efficient and scalable data architecture.
Network Administrator
A Network Administrator is responsible for managing and maintaining computer networks. This course may help you to automate your BigQuery data pipeline, which could help to improve the efficiency of your network.
Cloud Architect
A Cloud Architect is responsible for designing and managing cloud computing systems. This course may help you to automate your BigQuery data pipeline, which could help to improve the performance of your cloud applications.
Information Security Analyst
An Information Security Analyst is responsible for protecting information from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may help you to automate your BigQuery data pipeline, which could help you to improve the security of your data.
Cybersecurity Analyst
A Cybersecurity Analyst is responsible for protecting computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may help you to automate your BigQuery data pipeline, which could help you to improve the cybersecurity of your organization.
IT Project Manager
An IT Project Manager is responsible for planning and managing IT projects. This course may help you to automate your BigQuery data pipeline, which could help you to ensure that your projects are delivered on time and within budget.
Business Analyst
A Business Analyst is responsible for understanding and analyzing business processes. This course may help you to automate your BigQuery data pipeline, which could help you to gain insights into your business and improve your decision-making.

Reading list

We've selected seven 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 Automating your BigQuery Data Pipeline with Cloud Dataprep.
Provides a comprehensive guide to designing and building data-intensive applications. It's a valuable resource for anyone who wants to learn more about how to design and build scalable, reliable, and efficient data-intensive applications.
Provides a comprehensive guide to using Apache Airflow to build and manage data pipelines. It's a valuable resource for anyone who wants to learn more about how to use Airflow to automate and orchestrate data processing tasks.
Provides a comprehensive guide to machine learning with Python. It's a valuable resource for anyone who wants to learn more about how to use Python to develop and deploy machine learning models.
Provides a comprehensive guide to deep learning. It's a valuable resource for anyone who wants to learn more about the fundamentals of deep learning.
Provides a comprehensive guide to machine learning from a probabilistic perspective. It's a valuable resource for anyone who wants to learn more about the fundamentals of machine learning.

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