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Google Cloud Training

This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Redshift and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Redshift, you also learn about similarities and differences between Redshift and BigQuery to help you get started with data warehouses in BigQuery.

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What's inside

Syllabus

BigQuery Architecture and Resource Provisioning
This introductory module summarizes the key details of BigQuery architecture and resource provisioning including how BigQuery utilizes slots to execute SQL queries and workload management in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences between Redshift and BigQuery architecture and resource provisioning to help you get started with BigQuery.
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BigQuery Data Definition Model
This module summarizes the key details of BigQuery’s resource hierarchy and data definition model, including how to create datasets and tables in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences between the Redshift and BigQuery resource hierarchies and primary data types to help you start working with data in BigQuery.
BigQuery and Google Cloud IAM
This module summarizes the key details of the Google Cloud Identity and Access Management (IAM) model, including how roles and permissions are applied to datasets and tables in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in roles and permissions between Redshift and BigQuery to help you start securing and sharing your data in BigQuery.
BigQuery Data Ingestion
This module summarizes the primary options and best practices for ingesting data into BigQuery, including batch data loading, streaming ingestion, and queries to external data sources. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in data ingestion options between Redshift and BigQuery to help you start reading and loading your data into BigQuery.
BigQuery Schema Design and Optimization
This module summarizes common patterns and best practices for designing and optimizing table schemas in BigQuery, including the use of nested and repeated fields, partitioning, and clustering. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in schema usage and design between Redshift and BigQuery to help you start structuring and optimizing your data in BigQuery.
SQL in BigQuery
This module summarizes the key features and operations of the Google Standard SQL dialect used in BigQuery and best practices for optimizing query performance and controlling costs in BigQuery. Drawing upon your knowledge of Redshift, this module also provides a high-level overview of the similarities and differences in the SQL dialects and features between Redshift and BigQuery to help you start running and optimizing queries in BigQuery.

Good to know

Know what's good
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Covers the basics of BigQuery for those who are familiar with SQL-based cloud data warehouses in Redshift
Teaches the basics of BigQuery, from provisioning resources to optimizing query performance
Features hands-on labs to enhance the learning experience

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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 BigQuery Fundamentals for Redshift Professionals with these activities:
Organize and review course materials
Create a comprehensive repository of course materials for easy reference and review.
Show steps
  • Download and organize lecture slides
  • Take detailed notes during live sessions
  • Bookmark relevant resources and articles
  • Create a dedicated folder or notebook for all course materials
Review SQL querying syntax
Ensure a solid foundation in SQL querying syntax before beginning this course on BigQuery.
Show steps
  • Review online tutorials on SQL querying fundamentals
  • Practice writing basic SQL queries
Write a summary of BigQuery architecture
Solidify your understanding of BigQuery architecture by creating a written summary of key concepts.
Browse courses on BigQuery Architecture
Show steps
  • Review the course module on BigQuery architecture
  • Identify the main components and their functions
  • Describe how resource provisioning works in BigQuery
  • Summarize the key differences between BigQuery and Redshift architecture
Four other activities
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Complete interactive BigQuery tutorials
Gain hands-on experience with BigQuery's interface and SQL dialect through guided tutorials.
Show steps
  • Navigate to the BigQuery documentation page
  • Locate and select the 'Tutorials' section
  • Choose a tutorial relevant to your skill level
  • Follow the tutorial steps and complete the exercises
Solve BigQuery SQL practice problems
Enhance your proficiency in BigQuery SQL by solving practice problems.
Browse courses on Query Optimization
Show steps
  • Find online resources or platforms that provide BigQuery SQL practice problems
  • Select problems that align with your skill level and learning objectives
  • Attempt to solve the problems on your own
  • Review solutions and identify areas for improvement
Read 'BigQuery: The Definitive Guide' by Valliappa Lakshmanan
Gain a comprehensive understanding of BigQuery's capabilities and best practices by reading an authoritative book on the subject.
Show steps
  • Purchase or borrow the book
  • Read through the chapters relevant to your learning objectives
  • Take notes and highlight key concepts
Develop a data analysis project
Apply your BigQuery knowledge by designing and executing a data analysis project.
Browse courses on Data Exploration
Show steps
  • Identify a dataset of interest
  • Formulate a research question or hypothesis
  • Design a data analysis plan
  • Execute queries and analyze results
  • Visualize and present your findings

Career center

Learners who complete BigQuery Fundamentals for Redshift Professionals will develop knowledge and skills that may be useful to these careers:
Cloud Data Engineer
Cloud Data Engineers design, build, and manage data pipelines and data warehouses in the cloud. They use a variety of cloud computing technologies, including BigQuery, Google Cloud Storage, and Google Kubernetes Engine, to build scalable and reliable data systems. This course provides a comprehensive overview of BigQuery, including its architecture, data model, and SQL dialect. This knowledge is essential for success as a Cloud Data Engineer.
Data Architect
Data Architects design and build the company’s data infrastructure, including data warehouses, databases, and pipelines. They ensure that the data is organized and accessible in a way that meets the needs of the business. This course provides a comprehensive overview of data warehousing, including its architecture, data model, and SQL dialect. This knowledge is essential for success as a Data Architect.
Database Administrator
Database Administrators ensure that the company’s databases are up and running, and that the data stored in them is safe and secure. They perform a variety of tasks, including installing and configuring databases, monitoring performance, and backing up data. This course covers topics such as data warehousing, data modeling, and SQL, all of which are essential skills for success as a Database Administrator.
Information Security Analyst
Information Security Analysts protect the company’s data and computer systems from unauthorized access, use, disclosure, disruption, modification, or destruction. They develop and implement security policies and procedures, and they work with IT staff to ensure that the company’s systems are secure. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as an Information Security Analyst.
Risk Analyst
Risk Analysts identify, assess, and mitigate risks to the company’s business. They develop and implement risk management policies and procedures, and they work with business leaders to ensure that the company’s risks are managed effectively. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as a Risk Analyst.
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They analyze data to identify trends, patterns, and insights, and then communicate these insights to decision-makers in a clear and concise way. This course provides a foundation in data warehousing, data modeling, and SQL, all of which are essential skills for success as a Business Intelligence Analyst.
Data Governance Specialist
Data Governance Specialists ensure that the company’s data is used in a consistent and ethical manner. They develop and implement data governance policies and procedures, and they work with business leaders to ensure that data is used to support the company’s goals. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as a Data Governance Specialist.
Privacy Analyst
Privacy Analysts ensure that the company’s data is collected, used, and stored in a compliant manner. They develop and implement privacy policies and procedures, and they work with business leaders to ensure that the company’s data practices are in compliance with all applicable laws and regulations. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as a Privacy Analyst.
Compliance Analyst
Compliance Analysts ensure that the company’s business practices are in compliance with all applicable laws and regulations. They develop and implement compliance policies and procedures, and they work with business leaders to ensure that the company’s practices are in compliance. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as a Compliance Analyst.
Enterprise Architect
Enterprise Architects design and manage the company’s technology infrastructure, including hardware, software, and networks. They ensure that the company’s technology investments are aligned with the business goals. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as an Enterprise Architect.
Data Scientist
Data Scientists use data to solve business problems and develop new products and services. They use a variety of statistical and machine learning techniques to analyze data and extract insights. This course provides a foundation in data warehousing, data modeling, and SQL, all of which are essential skills for success as a Data Scientist.
Software Engineer
Software Engineers design, develop, and maintain software applications. They use a variety of programming languages and technologies to build software that meets the needs of users. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as a Software Engineer.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends, patterns, and insights that can help businesses make better decisions. They use a variety of tools and techniques to extract meaning from data, including SQL, Python, and machine learning algorithms. This course can help aspiring Data Analysts build a foundation in data warehousing, data modeling, and SQL, all of which are essential skills for success in this role.
Technical Program Manager
Technical Program Managers lead and manage the development and deployment of software applications. They work with engineers, designers, and other stakeholders to ensure that projects are completed on time, within budget, and to the required specifications. This course provides a foundation in data warehousing, data modeling, and SQL, which are all essential skills for success as a Technical Program Manager.
Data Engineer
Data Engineers build, deploy and manage the company’s data infrastructure, including data warehouses, databases, and pipelines. They make sure that the data is usable and accessible to the people who need it, ensuring the reliability and accuracy of the data. A course like BigQuery Fundamentals for Redshift Professionals may be useful for those striving for this role, as it can help build a foundation in data warehousing and data management.

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 BigQuery Fundamentals for Redshift Professionals.
Provides a solid foundation in data warehousing concepts and best practices, offering valuable insights for designing and optimizing data storage in BigQuery.
Offers a comprehensive overview of data-intensive architectures, providing a broader context for understanding the challenges and solutions in BigQuery.
Introduces the concept of data mesh, offering insights into distributed data management and the potential implications for BigQuery.
Provides a practical guide to using data science to transform data into business value. It covers all of the essential topics, including data collection, data analysis, and data visualization.
Provides a guide to using data science for business professionals. It covers all of the essential topics, including data science concepts, data science tools, and data science applications.
Introduces the Google Cloud Platform and its data analytics services, providing additional context for understanding BigQuery's role in the broader cloud ecosystem.
Provides a comprehensive overview of big data management, offering a broader context for understanding BigQuery's role in the data ecosystem.

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