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Introduction to Data Analytics on Google Cloud

Google Cloud

This introductory course explores the basics of data analysis, including collection, storage, exploration, visualization, and sharing. This course also introduces Google Cloud's data analytics tools and services.

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This introductory course explores the basics of data analysis, including collection, storage, exploration, visualization, and sharing. This course also introduces Google Cloud's data analytics tools and services.

This introductory course explores the basics of data analysis, including collection, storage, exploration, visualization, and sharing. This course also introduces Google Cloud's data analytics tools and services. Through video lectures, demos, quizzes, and hands-on labs, this course demonstrates how to go from raw data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started.

This course is no longer available. Find something similar by browsing:
Data Analysis Google Cloud Platform Data Visualization BigQuery Looker

What's inside

Syllabus

Course Introduction
Understand the Data Analytics Lifecycle on Google Cloud
Explore Data and Extract Insights by Using BigQuery
Make Data-driven Decisions by Using Looker
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Cements skills in BigQuery, Looker, and Google Cloud
Teaches data analysis skills and the data analytics lifecycle
Provides a foundation for using Google Cloud's analytics tools including Google Cloud's BigQuery and Looker
Covers data collection, storage, exploration, visualization, and reporting
Taught by Google Cloud staff with expertise in data analytics tools including BigQuery and Looker
May require software that learners do not possess

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Reviews summary

Foundational google cloud data analytics

According to learners, this course offers a largely positive introduction to data analytics on Google Cloud. Students particularly praise the hands-on labs and practical demonstrations, especially those involving BigQuery and Looker, which are highlighted as strong points for gaining applicable skills. Many find the lectures to be clear and concise, making complex topics accessible for beginners. While it excels as a starting point, some learners with prior experience caution that the course may feel too introductory and might not delve into advanced techniques. Overall, it provides a solid foundation for navigating the data analytics lifecycle on GCP.
Perfect for those new to data analytics or Google Cloud.
"Highly recommend for anyone new to GCP data tools."
"Prerequisites are minimal, making it accessible for someone just starting out."
"If you are new to data analytics or GCP, this course is a fantastic starting point."
Simplifies complex data analytics concepts for beginners.
"Excellent introduction to data analytics on Google Cloud."
"The instructor explained complex topics simply, making them easy to grasp for a beginner."
"This course delivered exactly what it promised: an intro, covering the basics well."
Provides practical experience with BigQuery and Looker.
"The hands-on labs using BigQuery and Looker were incredibly valuable and helped solidify my understanding."
"I found the BigQuery labs particularly useful for applying what I learned."
"The labs and practical exercises were the best part; they really cemented my knowledge."
Some reviewers encountered minor technical issues with labs.
"Some of the labs were a bit buggy or had slightly outdated screenshots which made following along tricky at times."
"A few labs had minor configuration issues, but I was able to work around them."
"I ran into some issues with the environment setup, which was a bit frustrating."
May be too basic for experienced data professionals.
"For those with some prior data experience, it might feel a bit slow at times."
"I found this course too superficial. I expected more advanced techniques."
"I wished there was more depth on advanced BigQuery features."

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 Introduction to Data Analytics on Google Cloud with these activities:
Explore the Google Cloud Platform
Familiarize yourself with the basics of Google Cloud Platform, its services, and its tools to prepare for this course.
Browse courses on Google Cloud Platform
Show steps
  • Watch the Google Cloud Platform Fundamentals video series
  • Create a free Google Cloud account
  • Explore the Google Cloud Console
Refresh your understanding of data analytics fundamentals
Review the basic principles of data analytics, including data collection, storage, analysis, and visualization. This will help you build a solid foundation for the course content.
Show steps
  • Read through the course syllabus and identify the key concepts covered.
  • Review your notes or textbooks from previous data analytics courses or workshops.
  • Take practice quizzes or solve sample problems related to data analytics basics.
Attend industry events and meetups
Connect with professionals in the data analytics field and learn about the latest trends and advancements. This will help you build your network and stay informed about the industry.
Show steps
  • Research and identify relevant industry events and meetups in your area or online.
  • Attend these events and積極的にengage with other attendees.
  • Follow up with interesting contacts and explore potential collaborations.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice SQL queries in BigQuery
Gain hands-on experience running SQL queries in BigQuery, enhancing your data exploration skills.
Browse courses on BigQuery
Show steps
  • Download a sample dataset into BigQuery
  • Write SQL queries to extract and analyze data
Form a study group with your classmates
Collaborate with your fellow students to reinforce your understanding of the course material and prepare for assessments. This will provide a supportive learning environment and foster a sense of community.
Show steps
  • Connect with other students in your class and form a study group.
  • Meet regularly to discuss course topics, review notes, and work on assignments together.
  • Quiz each other and provide feedback to improve your understanding.
Create data visualizations with Looker
Apply your data analysis skills to create visually engaging and insightful dashboards in Looker, enhancing your communication and decision-making abilities.
Browse courses on Looker
Show steps
  • Connect Looker to your BigQuery dataset
  • Create a dashboard with charts and graphs
  • Share your dashboard with stakeholders
Contribute to open-source data analytics projects
Gain practical experience and showcase your skills by contributing toオープンソースdata analytics projects. This will not only enhance your technical abilities but also demonstrate your commitment to the field.
Show steps
  • Identify open-source data analytics projects that align with your interests and skills.
  • Review the project documentation and identify areas where you can contribute.
  • Submit pull requests with your contributions and actively engage with the project maintainers.

Career center

Learners who complete Introduction to Data Analytics on Google Cloud will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use data analysis and modeling techniques to analyze data that can help organizations make informed business decisions. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for a Data Analyst to have. Through video lectures, demos, quizzes, and hands-on labs, this course provides a great foundation for a future Data Analyst.
See salaries and explore the career path for Data Analyst
Data Scientist
Data Scientists analyze and interpret large amounts of data, and then make predictions or recommendations based on their findings. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are the essential skills for Data Scientists. This course also introduces Google Cloud's data analytics tools and services that Data Scientists should be familiar with.
See salaries and explore the career path for Data Scientist
Business Analyst
Business Analysts use data analysis and modeling techniques to analyze data that can help organizations make informed business decisions. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all essential skills for Business Analysts to have. Through video lectures, demos, quizzes, and hands-on labs, this course provides a great foundation for a future Business Analyst.
See salaries and explore the career path for Business Analyst
Data Engineer
Data Engineers develop and maintain data infrastructure, which includes designing, building, and testing data pipelines and data warehouses. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. Having some knowledge of these concepts is helpful for Data Engineers to have, but may not be essential.
See salaries and explore the career path for Data Engineer
Machine Learning Engineer
Machine Learning Engineers develop and maintain machine learning models, which can be used to make predictions or recommendations based on data. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. While Machine Learning Engineers need to be able to perform these skills, they may not be as central to the role as they are for other Data Science roles.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
Software Engineers analyze user needs, design, develop, test, and maintain software systems. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. Data analysis skills are becoming increasingly important for Software Engineers, and this course would be a helpful introduction if this is a career someone wanted to pursue.
See salaries and explore the career path for Software Engineer
Statistician
Statisticians collect, analyze, interpret, and present data, and make predictions based on their analysis. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are the essential functions of a Statistician, and this course provides a great foundation for a future career in this field.
See salaries and explore the career path for Statistician
Market Researcher
Market Researchers collect, analyze, and interpret data about consumer behavior and market trends. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for Market Researchers to have. This course would be a great introduction to the field.
See salaries and explore the career path for Market Researcher
Financial Analyst
Financial Analysts use data analysis and modeling techniques to analyze financial data and make investment recommendations. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all essential skills for Financial Analysts to have. This course would be a helpful introduction to the field.
See salaries and explore the career path for Financial Analyst
Operations Research Analyst
Operations Research Analysts use data analysis and modeling techniques to improve the efficiency of business operations. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for Operations Research Analysts to have. This course could be a great introduction to the field.
See salaries and explore the career path for Operations Research Analyst
Actuary
Actuaries use data analysis and modeling techniques to assess risk and uncertainty, and to develop financial plans. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for Actuaries to have. This course could be a great introduction to the field.
See salaries and explore the career path for Actuary
Economist
Economists use data analysis and modeling techniques to study economic issues, such as inflation, unemployment, and economic growth. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for Economists to have. This course could be a great introduction to the field.
See salaries and explore the career path for Economist
Epidemiologist
Epidemiologists use data analysis and modeling techniques to study the distribution and determinants of disease. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for Epidemiologists to have. This course could be a great introduction to the field.
See salaries and explore the career path for Epidemiologist
Biostatistician
Biostatisticians use data analysis and modeling techniques to design and analyze studies, and to interpret and communicate the results. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. These are all important skills for Biostatisticians to have. This course could be a great introduction to the field.
See salaries and explore the career path for Biostatistician
Data Visualization Specialist
Data Visualization Specialists create visual representations of data, such as charts, graphs, and maps. This introductory course explores the basics of data analysis, collection, storage, exploration, visualization, and sharing. While this course focuses on data visualization, it also covers the other essential steps in the data analysis process, which would be helpful for a Data Visualization Specialist.
See salaries and explore the career path for Data Visualization Specialist

Reading list

We've selected five 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 Introduction to Data Analytics on Google Cloud.
Cover image
Optimizing DAX
Save
Covers data analytics in action. It provides real-world examples of how data analytics is used to solve business problems.
Optimizing DAX: Improving DAX performance in...
Paperback
$$$
Optimizing DAX: Improving DAX performance in...
Kindle Edition
$$$
Cover image
Hadoop: The Definitive Guide
Save
Covers data analysis with Hadoop. It covers all the basics, and it does so in a way that is easy to understand.
Hadoop: The Definitive Guide: Storage and Analysis...
Paperback
$$
Hadoop: The Definitive Guide
Kindle Edition
$$
Hadoop: The Definitive Guide
Paperback
$$
Hadoop: The Definitive Guide
Paperback
$$
Cover image
Data Science for Business
Save
A strategic approach to data science for business, providing a clear and concise overview of the key concepts and techniques of data science.
Data Science for Business: What You Need to Know...
Paperback
$$
Data Science for Business: What You Need to Know...
Kindle Edition
$$
Cover image
Big Data
Save
A comprehensive guide to big data principles and best practices, providing a deep dive into the key concepts and techniques of big data systems.
Big Data: Principles and best practices of scalable...
Paperback
$$
(Deutsch) Big Data: Entwicklung und Programmierung von...
Perfect Paperback
$$$
Big Data: Principles and best practices of scalable...
Kindle Edition
$$
Cover image
Machine Learning with PyTorch and Scikit-Learn
Save
A guide to machine learning in Python, covering the basics of machine learning, including how to use Python libraries for machine learning.
Machine Learning with PyTorch and Scikit-Learn:...
Kindle Edition
$$

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Course image
Time
53 hours
Level
Introductory
Via
Pluralsight
Instructor
Google Cloud
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Cements skills in BigQuery, Looker, and Google Cloud
Teaches data analysis skills and the data analytics lifecycle
Provides a foundation for using Google Cloud's analytics tools including Google Cloud's BigQuery and Looker
Covers data collection, storage, exploration, visualization, and reporting
Taught by Google Cloud staff with expertise in data analytics tools including BigQuery and Looker
May require software that learners do not possess
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