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Google Cloud Training
In this Google Cloud Labs Series, learn how to transform your data warehouse using BigQuery, including how to: 1. Use a command line interface to query and load sample data. 2. Create new reporting tables using SQL, JOINS, and UNIONs. 3. Create dataset...
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In this Google Cloud Labs Series, learn how to transform your data warehouse using BigQuery, including how to: 1. Use a command line interface to query and load sample data. 2. Create new reporting tables using SQL, JOINS, and UNIONs. 3. Create dataset partitions that will reduce cost and improve query performance. 4. Create and troubleshoot joins. 5. Load, query, and un-nest semi-structured datasets. 6. Use Data Catalog. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge Google Cloud Lab, and final assessment challenge lab, to receive a digital badge that you can share with your network. 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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Tests your ability to apply your knowledge in an interactive hands-on environment
Taught by Google Cloud, who are recognized for their work in the field
Develops skills that may be highly relevant in an academic setting
Offers hands-on labs and interactive materials
Requires that learners come in with a certain level of background knowledge

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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 Build and Optimize Data Warehouses with BigQuery with these activities:
Organize Course Materials
Organizing your course materials can improve your ability to locate and review important information.
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  • Create a system for organizing your notes, assignments, and other course materials.
  • Review your organized materials regularly to reinforce your understanding.
Refresh CLI fundamentals
Solidify your understanding of the command line interface, which you'll use throughout the course.
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Show steps
  • Review basic commands (ls, cd, mkdir, rm, cp, more, less, cat, tail, head)
  • Navigate the file system using the command line
Review SQL Syntax
Reviewing the fundamentals of SQL syntax can strengthen your foundational knowledge and make learning new concepts easier.
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  • Go over basic SQL commands such as SELECT, INSERT, UPDATE, and DELETE.
  • Practice writing simple SQL queries to retrieve and manipulate data.
Eight other activities
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Join a study group
Connect with other learners to discuss course concepts, share knowledge, and support each other's understanding.
Show steps
  • Find or create a study group with other students taking the same course
  • Meet regularly to review materials, discuss assignments, and prepare for assessments
Explore BigQuery Documentation
Familiarizing yourself with the BigQuery documentation can help you learn more about its features and capabilities.
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  • Visit the BigQuery documentation website.
  • Read through the tutorials and guides to gain an understanding of BigQuery's functionality.
Learn advanced SQL techniques
Enhance your SQL knowledge by exploring more advanced techniques that will be useful for data analysis and transformation in this course.
Browse courses on SQL
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  • Review subqueries, common table expressions (CTEs), and window functions
  • Practice writing complex SQL queries using these techniques
Practice Querying Data
Hands-on practice with querying data can improve your understanding of data manipulation and retrieval.
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  • Use an online SQL editor or download a database management system.
  • Load sample data into your database.
  • Practice writing SQL queries to answer specific questions about the data.
Practice data cleaning and transformation
Refine your data manipulation skills by working through practice exercises that simulate real-world data cleaning and transformation tasks.
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  • Load sample data into BigQuery
  • Remove duplicate records
  • Handle missing values
  • Transform data using SQL functions
Attend an industry workshop on BigQuery
Gain exposure to real-world BigQuery applications and best practices by attending an industry workshop led by experts in the field.
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Show steps
  • Research and identify relevant industry workshops
  • Register and attend the workshop
Build a Simple Data Pipeline
Creating a simple data pipeline can provide practical experience in data transformation and management.
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Show steps
  • Design a data pipeline that involves data extraction, transformation, and loading.
  • Implement the data pipeline using BigQuery and other tools as needed.
  • Test and evaluate the performance of your data pipeline.
Build a data dashboard
Apply your skills to create a data dashboard that visualizes insights from a real-world dataset, showcasing your proficiency in data analysis and presentation.
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Show steps
  • Choose a dataset and define your project goals
  • Design and build your dashboard using a data visualization tool
  • Interpret and communicate insights from your data

Career center

Learners who complete Build and Optimize Data Warehouses with BigQuery will develop knowledge and skills that may be useful to these careers:
Data Warehouse Architect
Data Warehouse Architects design and manage data warehouses. They have a deep understanding of data warehousing concepts and technologies. This course is highly relevant for Data Warehouse Architects, as it provides hands-on experience with designing and managing a data warehouse in BigQuery.
Data Analyst
Data Analysts analyze data to provide insights to stakeholders within an organization. They use statistical analysis and visualization techniques to uncover trends, patterns, and anomalies in data. This course is highly relevant to Data Analysts, as it provides hands-on experience with SQL, data transformation, and data analysis using BigQuery.
ETL Developer
ETL Developers design and build data pipelines to extract, transform, and load data from various sources into a data warehouse. This course is highly relevant to ETL Developers, as it provides hands-on experience with building data pipelines using BigQuery.
Business Intelligence Analyst
Business Intelligence Analysts gather and analyze data to help businesses make informed decisions. They use data to identify trends, opportunities, and risks, and they present their findings to stakeholders in a clear and concise way. This course can be useful for Business Intelligence Analysts, as it provides a foundation in data querying, analysis, and visualization using BigQuery.
Cloud Architect
Cloud Architects design and manage cloud computing systems. They have a deep understanding of cloud technologies and how to use them to meet business needs. This course may be useful for Cloud Architects who want to use BigQuery for data warehousing and analytics.
Data Management Analyst
Data Management Analysts analyze and manage data to ensure that it is accurate, complete, and consistent. They develop and implement data management policies and procedures. This course may be useful for Data Management Analysts who want to use BigQuery for data warehousing and management.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They use their skills in computer science, mathematics, and statistics to design and implement machine learning algorithms. This course may be useful for Machine Learning Engineers who want to use BigQuery for data storage and analysis.
Data Architect
Data Architects design and manage data architectures. They have a deep understanding of data management concepts and technologies. This course may be useful for Data Architects who want to use BigQuery for data warehousing and analytics.
Database Administrator
Database Administrators are responsible for the maintenance and performance of databases. They ensure that databases are running smoothly and that data is secure and accessible. This course may be useful for Database Administrators who want to use BigQuery for data warehousing and management.
Data Scientist
Data Scientists use data to build machine learning models and solve complex problems. They have a strong foundation in statistics, mathematics, and computer science. This course may be useful for Data Scientists who want to use BigQuery for data storage and analysis.
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They ensure that data is used in a consistent and ethical manner. This course may be useful for Data Governance Analysts who want to use BigQuery for data governance and management.
Big Data Engineer
Big Data Engineers design and manage big data systems. They have a deep understanding of big data technologies and how to use them to meet business needs. This course may be useful for Big Data Engineers who want to use BigQuery for data warehousing and analytics.
Data Integration Specialist
Data Integration Specialists integrate data from various sources into a single, cohesive data warehouse. They have a deep understanding of data integration tools and technologies. This course may be useful for Data Integration Specialists who want to use BigQuery for data integration and management.
Data Engineer
Data Engineers build and maintain data pipelines to store vast amounts of structured and unstructured data. Acting as stewards for data quality and integrity, they help build, deploy, and manage pipelines within the organization. This course may be useful for those in this field, as it covers critical skills such as loading, querying, and managing data in BigQuery.

Reading list

We've selected ten 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 Build and Optimize Data Warehouses with BigQuery.
Provides a practical guide to designing and implementing data warehouses. It covers a wide range of topics, including data modeling, data integration, and data quality.
Provides a foundational overview of data warehousing concepts and best practices. It valuable resource for anyone who is new to data warehousing or who wants to refresh their knowledge.
Provides a practical guide to using data science for business. It covers a wide range of topics, including data mining, machine learning, and data visualization.
Provides a comprehensive overview of big data analytics. It covers a wide range of topics, including data mining, machine learning, and data visualization.
Provides a gentle introduction to machine learning. It covers a wide range of topics, including linear regression, logistic regression, and decision trees.
Provides a comprehensive guide to building data warehouses with Oracle. It covers all aspects of data warehousing, from data modeling and data ingestion to data analysis and reporting.
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of reinforcement learning. It covers a wide range of topics, including Markov decision processes, value functions, and policy gradients.
Provides a comprehensive overview of natural language processing with Python. It covers a wide range of topics, including text classification, text clustering, and machine translation.
Provides a comprehensive overview of computer vision with Python. It covers a wide range of topics, including image classification, object detection, and image segmentation.

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