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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 learn to use BigQuery to find data, query the data-to-insights public dataset, and write and execute queries.

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What's inside

Syllabus

Exploring Your Ecommerce Dataset with SQL in Google BigQuery

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Emphasizes application of SQL for data insights in the context of ecommerce
Conducted in a hands-on lab environment, providing practical experience in BigQuery
Taught by Google Cloud Training, recognized experts in cloud computing

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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 Exploring Your Ecommerce Dataset with SQL in Google BigQuery with these activities:
Engage with BigQuery Experts and Mentors
Seek guidance and mentorship from experienced BigQuery professionals or experts to enhance your learning journey.
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  • Attend BigQuery meetups or online events to interact with the community.
  • Connect with BigQuery engineers or data analysts on platforms like LinkedIn.
  • Ask questions, learn about industry best practices, and gain valuable insights.
Review SQL
Brush up on your SQL skills before starting the course to maximize understanding.
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  • Study SQL syntax and commands.
  • Practice writing and executing queries against a sample or pre-populated dataset.
Data Analysis Practice and SQL Challenges
Enhance your data analysis skills and problem-solving abilities by taking on data-driven challenges.
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  • Participate in online coding challenges or hackathons focused on data analysis.
  • Solve puzzles and riddles that require logical thinking and data interpretation.
  • Explore interactive data visualization platforms to analyze real-world datasets.
  • Compare your solutions with others and learn from different approaches.
Five other activities
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Explore BigQuery Documentations and Blogs
Seek supplemental guidance by reviewing official BigQuery documentation and reading blog articles to enhance your understanding of its features and capabilities.
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  • Go through the BigQuery documentation page, focusing on topics relevant to your course.
  • Identify and read in-depth blog articles or tutorials that provide insights and best practices.
  • Take notes or highlight key concepts and examples for future reference.
Practice Querying Data in BigQuery
Solve a set of practice problems and exercises to enhance your ability to query and analyze data using BigQuery.
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  • Start the SQL Interactive Query Tool in the Google Cloud Console.
  • Load a dataset into BigQuery.
  • Write and execute queries to retrieve and aggregate data.
  • Analyze the results obtained from your queries.
Build a Data Analysis Project Using BigQuery
Apply your BigQuery knowledge by working on a project that involves data analysis, query optimization, and visualization.
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  • Identify a real-world problem or use case that can be addressed with data analysis.
  • Gather and clean relevant data from various sources.
  • Design and execute SQL queries to analyze the data and extract insights.
  • Prepare data visualizations and dashboards using BigQuery's BI tools.
  • Present your findings and communicate the insights to stakeholders.
Follow BigQuery Best Practices and Optimization Techniques
Maximize the performance and efficiency of your BigQuery queries by learning about recommended practices and optimization techniques.
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  • Review Google's official documentation on best practices for designing and executing SQL queries.
  • Read articles and blog posts from experts sharing their experiences and tips for optimizing BigQuery performance.
  • Implement these best practices in your own queries to improve query speed and reduce costs.
Develop a Data Analysis Visualization Dashboard
Demonstrate your understanding of data visualization techniques by designing and building an interactive dashboard that communicates insights from a given dataset.
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  • Use a data visualization tool (e.g., Google Data Studio, Tableau) to create a dashboard.
  • Connect the dashboard to a BigQuery dataset or import your own dataset.
  • Design and implement visualizations (e.g., charts, graphs, maps) to represent key insights in the data.
  • Incorporate interactive elements (e.g., filters, drill-downs) to allow users to explore the data interactively.
  • Polish and document your dashboard for presentation.

Career center

Learners who complete Exploring Your Ecommerce Dataset with SQL in Google BigQuery will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists are responsible for using data to solve business problems. They use a variety of techniques to identify patterns and trends in data, and they develop models to predict future outcomes. Google BigQuery is a powerful tool for data exploration and analysis, making it an essential tool for Data Scientists. The skills you will learn in this course will help you to become a more effective Data Scientist.
Data Analyst
Data Analysts are responsible for collecting data from various sources and using that data to support decision-making throughout an organization. Google BigQuery is a powerful tool for working with data from many sources, and it is well-suited for tasks such as data exploration and analysis. The skills you will learn in this course will be invaluable for Data Analysts.
Data Engineer
Data Engineers are responsible for designing, building, and maintaining data pipelines. These pipelines are essential for ensuring that data is available to the people who need it in a timely and reliable manner. Google BigQuery is a powerful tool for building data pipelines. This course will provide you with the skills you need to use Google BigQuery to build data pipelines that meet the needs of your organization.
Big Data Architect
A Big Data Architect helps create and maintain data solutions. Their primary concern is managing massive datasets. As such, they rely on programs like Google BigQuery and other SQL technologies. This course provides the foundation needed to query data with Google BigQuery, a useful skill for working with big data.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They are often employed by financial institutions to help make investment decisions. Google BigQuery is a powerful tool for working with large datasets, and it is well-suited for tasks such as financial modeling and forecasting. The skills you will learn in this course will be invaluable for Quantitative Analysts.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software applications. They use a variety of programming languages and tools to create software that meets the needs of users. Google BigQuery is a powerful tool for working with data, and it can be used to create a variety of data-driven applications. The skills you will learn in this course will be helpful for Software Engineers who want to develop data-driven applications.
Business Analyst
Business Analysts help businesses make better decisions by providing data-driven insights. They use a variety of tools and techniques to analyze data and identify trends and patterns. Google BigQuery is a powerful tool for working with data, and it can be used to generate valuable insights for businesses. The skills you will learn in this course will be helpful for Business Analysts who want to use data to improve decision-making.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They ensure that databases are available, reliable, and secure. Google BigQuery is a powerful tool for working with data, and it requires specialized knowledge to manage and maintain. The skills you will learn in this course will be helpful for Database Administrators who want to manage and maintain Google BigQuery databases.
Budget Analyst
Budget Analysts use data to create and manage budgets for organizations. They use a variety of tools and techniques to analyze data, including Google BigQuery. The skills you will learn in this course will be helpful for Budget Analysts who want to use data to create and manage more effective budgets.
Financial Analyst
Financial Analysts use data to make recommendations about investments and financial decisions. They use a variety of tools and techniques to analyze data, including Google BigQuery. The skills you will learn in this course will be helpful for Financial Analysts who want to use data to make better investment decisions.
Market Researcher
Market Researchers study markets and consumer behavior to help businesses make informed decisions. They use a variety of tools and techniques to collect and analyze data, including Google BigQuery. The skills you will learn in this course will be helpful for Market Researchers who want to use data to better understand markets and consumer behavior.
Data Governance Analyst
Data Governance Analysts help organizations manage and protect their data. They develop and implement policies and procedures to ensure that data is used in a responsible and ethical manner. Google BigQuery is a powerful tool for working with data, and it can be used to help organizations manage and protect their data. The skills you will learn in this course will be helpful for Data Governance Analysts who want to use data to improve data governance.
Compliance Analyst
Compliance Analysts help organizations comply with applicable laws and regulations. They develop and implement policies and procedures to ensure that the organization is operating in a compliant manner. Google BigQuery is a powerful tool for working with data, and it can be used to help organizations comply with applicable laws and regulations. The skills you will learn in this course will be helpful for Compliance Analysts who want to use data to improve compliance.
Privacy Analyst
Privacy Analysts help organizations protect the privacy of their customers and employees. They develop and implement policies and procedures to ensure that data is collected, used, and disclosed in a manner that complies with applicable laws and regulations. Google BigQuery is a powerful tool for working with data, and it can be used to help organizations protect the privacy of their data. The skills you will learn in this course will be helpful for Privacy Analysts who want to use data to improve privacy.
Information Security Analyst
Information Security Analysts help organizations protect their data from unauthorized access, use, disclosure, disruption, modification, or destruction. They use a variety of tools and techniques to identify and mitigate security risks, including Google BigQuery. The skills you will learn in this course will be helpful for Information Security Analysts who want to use data to improve information security.

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 Exploring Your Ecommerce Dataset with SQL in Google BigQuery.
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone who wants to learn more about machine learning and how to use it to solve real-world problems.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone who wants to learn more about statistical learning and how to use it to solve real-world problems.
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone who wants to learn more about pattern recognition and machine learning and how to use it to solve real-world problems.
Provides a comprehensive overview of reinforcement learning. It covers a wide range of topics, including Markov decision processes, value functions, and reinforcement learning algorithms. It valuable resource for anyone who wants to learn more about reinforcement learning and how to use it to solve real-world problems.
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn more about deep learning and how to use it to solve real-world problems.
Provides a fun and engaging introduction to SQL. It uses a unique and visual approach to teaching the language, making it easier for beginners to understand the concepts and apply them to real-world problems.
A quick and easy introduction to SQL, this book provides a concise overview of the language's core concepts and syntax. It valuable resource for anyone who wants to learn the basics of SQL quickly and easily.

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