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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short videos Get Meaningful Insights with Google BigQuery and BigQuery: Qwik Start - Qwiklabs Preview.
Register for this course and see more details by visiting:
OpenCourser.com/course/h421se/bigquery
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What's inside
Syllabus
BigQuery: Qwik Start - Command Line
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches querying public tables and loading sample data into BigQuery using the Command Line Interface, which is a highly relevant skill in data analysis
Provides a hands-on approach with videos and interactive labs, enhancing learning and retention
Taught by Google Cloud Training, recognized for expertise in BigQuery and data management
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Save BigQuery: Qwik Start - Command Line to your list so you can find it easily later:
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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: Qwik Start - Command Line with these
activities:
Review the basics of SQL
Show steps
Refresh your knowledge of SQL, a fundamental skill for working with data in BigQuery, to ensure a strong foundation for the course.
Browse courses on
SQL
Show steps
-
Review online tutorials or documentation on SQL syntax and commands
-
Practice writing and executing basic SQL queries on a sample dataset
Review fundamental data analysis concepts
Show steps
Refresh your understanding of core data analysis concepts, such as data cleaning, transformation, and visualization, to enhance your ability to work with data in BigQuery.
Browse courses on
Data Analysis
Show steps
-
Review online resources or textbooks on data analysis fundamentals
-
Complete practice exercises or quizzes to test your knowledge
Create a study guide summarizing key concepts from the course
Show steps
Reinforce your understanding of the course material by creating a comprehensive study guide that organizes and summarizes the key concepts.
Show steps
-
Review lecture notes, course materials, and assignments
-
Identify and summarize the most important concepts and topics
-
Organize the information logically and create a structured study guide
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in online forums or discussion groups related to BigQuery
Show steps
Enhance your understanding by engaging with others in online communities, answering questions, and sharing your knowledge about BigQuery.
Browse courses on
BigQuery
Show steps
-
Join online forums or discussion groups focused on BigQuery
-
Actively participate in discussions by asking questions, providing answers, and sharing your insights
-
Collaborate with other members to solve problems and learn from their experiences
Follow online tutorials on BigQuery
Show steps
Expand your knowledge of BigQuery's features and capabilities by following step-by-step tutorials provided by Google or other reputable sources.
Browse courses on
BigQuery
Show steps
-
Identify online tutorials that align with your learning objectives
-
Follow the instructions in the tutorials to complete the exercises and examples
-
Apply what you've learned from the tutorials to your own projects or datasets
Run SQL queries on BigQuery sample datasets
Show steps
Practice writing SQL queries to extract and analyze data from BigQuery datasets to reinforce your understanding of the concepts covered in the course.
Browse courses on
SQL
Show steps
-
Choose a BigQuery sample dataset to work with
-
Write and execute SQL queries to retrieve and filter data from the dataset
-
Analyze the results of your queries
Create a dashboard to visualize data from BigQuery
Show steps
Demonstrate your understanding of BigQuery's data analysis capabilities by creating an interactive dashboard that visualizes insights from a dataset.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and identify the key metrics and insights you want to visualize
-
Use a data visualization tool to create charts, graphs, and other visual representations of the data
-
Design and implement an interactive dashboard that allows users to explore and interact with the data
Develop a small-scale data analysis project using BigQuery
Show steps
Apply the concepts and techniques learned in the course to a real-world data analysis project, solidifying your understanding and building your portfolio.
Browse courses on
BigQuery
Show steps
-
Define a specific data analysis problem or question to be addressed
-
Gather relevant data from BigQuery or other sources and import it into your project
-
Clean and prepare the data for analysis
-
Apply appropriate data analysis techniques and algorithms to extract insights from the data
-
Present and communicate your findings and insights
Review the basics of SQL
Show steps
Refresh your knowledge of SQL, a fundamental skill for working with data in BigQuery, to ensure a strong foundation for the course.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review online tutorials or documentation on SQL syntax and commands
- Practice writing and executing basic SQL queries on a sample dataset
Review fundamental data analysis concepts
Show steps
Refresh your understanding of core data analysis concepts, such as data cleaning, transformation, and visualization, to enhance your ability to work with data in BigQuery.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Review online resources or textbooks on data analysis fundamentals
- Complete practice exercises or quizzes to test your knowledge
Create a study guide summarizing key concepts from the course
Show steps
Reinforce your understanding of the course material by creating a comprehensive study guide that organizes and summarizes the key concepts.
Show steps
Show steps
Show steps
- Review lecture notes, course materials, and assignments
- Identify and summarize the most important concepts and topics
- Organize the information logically and create a structured study guide
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in online forums or discussion groups related to BigQuery
Show steps
Enhance your understanding by engaging with others in online communities, answering questions, and sharing your knowledge about BigQuery.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Join online forums or discussion groups focused on BigQuery
- Actively participate in discussions by asking questions, providing answers, and sharing your insights
- Collaborate with other members to solve problems and learn from their experiences
Follow online tutorials on BigQuery
Show steps
Expand your knowledge of BigQuery's features and capabilities by following step-by-step tutorials provided by Google or other reputable sources.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Identify online tutorials that align with your learning objectives
- Follow the instructions in the tutorials to complete the exercises and examples
- Apply what you've learned from the tutorials to your own projects or datasets
Run SQL queries on BigQuery sample datasets
Show steps
Practice writing SQL queries to extract and analyze data from BigQuery datasets to reinforce your understanding of the concepts covered in the course.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Choose a BigQuery sample dataset to work with
- Write and execute SQL queries to retrieve and filter data from the dataset
- Analyze the results of your queries
Create a dashboard to visualize data from BigQuery
Show steps
Demonstrate your understanding of BigQuery's data analysis capabilities by creating an interactive dashboard that visualizes insights from a dataset.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and identify the key metrics and insights you want to visualize
- Use a data visualization tool to create charts, graphs, and other visual representations of the data
- Design and implement an interactive dashboard that allows users to explore and interact with the data
Develop a small-scale data analysis project using BigQuery
Show steps
Apply the concepts and techniques learned in the course to a real-world data analysis project, solidifying your understanding and building your portfolio.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Define a specific data analysis problem or question to be addressed
- Gather relevant data from BigQuery or other sources and import it into your project
- Clean and prepare the data for analysis
- Apply appropriate data analysis techniques and algorithms to extract insights from the data
- Present and communicate your findings and insights
Career center
Learners who complete BigQuery: Qwik Start - Command Line will develop knowledge and skills
that may be useful to these careers:
Data Architect
Data Architect
Data Architects design and manage data architectures. BigQuery is a cloud-based data warehouse that can be used to store and process large datasets. This course will help Data Architects build a foundation in BigQuery and understand how it can be used to improve their data architectures.
Database Designer
Database Designer
Database Designers design and implement databases. BigQuery is a cloud-based data warehouse that can be used to store and process large datasets. This course will help Database Designers build a foundation in BigQuery and understand how it can be used to improve their database designs.
Data Governance Specialist
Data Governance Specialist
Data Governance Specialists ensure that data is used in a consistent and ethical manner. BigQuery is a cloud-based data warehouse that can be used to store and process large datasets. This course will help Data Governance Specialists build a foundation in BigQuery and understand how it can be used to improve their data governance practices.
Data Scientist
Data Scientist
Data Scientists use scientific methods and algorithms to extract knowledge and insights from data. BigQuery can help Data Scientists store, process, and analyze large datasets, making it an essential tool for this role. This course will introduce Data Scientists to BigQuery and help them build a foundation in using it.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. BigQuery can help Business Analysts store, process, and analyze large datasets, making it an essential tool for this role. This course will introduce Business Analysts to BigQuery and help them build a foundation in using it.
Data Analyst
Data Analyst
A Data Analyst uses data to make informed decisions by identifying patterns and trends. With BigQuery, Data Analysts can leverage their SQL skills to query large datasets and gain insights from data. This course will help build a foundation in BigQuery, which can be valuable in this role.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases, ensuring that data is secure, reliable, and accessible. BigQuery is a cloud-based, fully managed data warehouse. This course will introduce Database Administrators to BigQuery and help them understand how it can be used to store and manage data.
Data Engineer
Data Engineer
Data Engineers design, construct, and maintain the infrastructure that stores and processes data. They also ensure that data is accurate, consistent, and secure. This course will introduce Data Engineers to BigQuery, a cloud-based data warehousing solution that can help them store and process large datasets.
Systems Analyst
Systems Analyst
Systems Analysts design, implement, and maintain computer systems. BigQuery can be used to store and process large datasets, making it valuable for Systems Analysts who work with data-intensive systems. This course will help Systems Analysts build a foundation in BigQuery and understand how it can be used to improve their systems.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. BigQuery can be used to store and process large datasets, making it valuable for Software Engineers who work with data-intensive applications. This course will help Software Engineers build a foundation in BigQuery and understand how it can be used to improve their applications.
Marketing Manager
Marketing Manager
Marketing Managers plan and execute marketing campaigns. BigQuery can be used to track campaign performance and identify opportunities for improvement. This course will help Marketing Managers build a foundation in BigQuery and understand how it can be used to improve their campaigns.
Customer Success Manager
Customer Success Manager
Customer Success Managers ensure that customers are satisfied with their products or services. BigQuery can be used to track customer usage and identify opportunities for improvement. This course will help Customer Success Managers build a foundation in BigQuery and understand how it can be used to improve their customer success.
Sales Manager
Sales Manager
Sales Managers manage sales teams and track sales performance. BigQuery can be used to track sales data and identify opportunities for improvement. This course will help Sales Managers build a foundation in BigQuery and understand how it can be used to improve their sales performance.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. BigQuery can be used to track project progress and identify risks. This course will help Project Managers build a foundation in BigQuery and understand how it can be used to improve their projects.
Product Manager
Product Manager
Product Managers manage the development and launch of new products. BigQuery can be used to track product usage and identify opportunities for improvement. This course will help Product Managers build a foundation in BigQuery and understand how it can be used to improve their products.
For more career information including salaries, visit:
OpenCourser.com/course/h421se/bigquery
Reading list
We've selected six 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: Qwik Start - Command Line.
Provides a comprehensive overview of Hadoop, a popular open-source framework for big data processing. It valuable resource for anyone who wants to learn more about Hadoop.
Provides a comprehensive overview of Spark, a popular open-source framework for big data processing. It valuable resource for anyone who wants to learn more about Spark.
Provides a broad overview of data science and its applications. It covers a wide range of topics, from data mining to data visualization.
Provides a collection of recipes for solving common machine learning problems with Python. It valuable resource for anyone who wants to learn more about machine learning with Python.
Provides a gentle introduction to machine learning. It valuable resource for anyone who wants to learn more about machine learning.
Provides a gentle introduction to data science. It valuable resource for anyone who wants to learn more about data science.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/h421se/bigquery
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Effort
30 minutes
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Teaches querying public tables and loading sample data into BigQuery using the Command Line Interface, which is a highly relevant skill in data analysis
Provides a hands-on approach with videos and interactive labs, enhancing learning and retention
Taught by Google Cloud Training, recognized for expertise in BigQuery and data management
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