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Google Cloud Training
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets.
This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
Register for this course and see more details by visiting:
OpenCourser.com/course/g7y6xz/exploring
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What's inside
Syllabus
Welcome to From Data to Insights with Google Cloud: Exploring and Preparing your Data
Learn the courses, content, and technologies that are part of this data analyst course series.
Read more
Syllabus
Welcome to From Data to Insights with Google Cloud: Exploring and Preparing your Data
Learn the courses, content, and technologies that are part of this data analyst course series.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Introduces data analytics, which is standard in industry
Uses industry tools, such as BigQuery and Dataprep, which are demanded by employers
Goes over SQL, which is highly relevant to data analytics
Teaches how to optimize queries for better outcomes, which is a useful skill in industry
Includes hands-on exercises to improve learning
Part of a larger series of courses, indicating a comprehensive approach to data analysis
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Reviews summary
Intro to bigquery & data prep
According to learners, this course serves as a solid introduction to using BigQuery and other Google Cloud tools for data analysis and preparation. Students appreciate the clear explanations of SQL basics and how they apply within BigQuery. Many find the hands-on labs to be particularly valuable for practicing concepts. However, some reviewers note that the pace might be a bit fast for absolute beginners with no prior data experience, while others with existing SQL knowledge find the initial database sections basic. The coverage of Dataprep is sometimes seen as less in-depth than BigQuery. Overall, it's considered a strong foundation for the subsequent courses in the series.
Dataprep section could be more detailed.
"The segment on Dataprep felt less comprehensive compared to the BigQuery content."
"Wish there was a bit more depth on using Dataprep for data cleaning."
"Dataprep was interesting but the coverage seemed relatively brief."
Pace varies for different skill levels.
"As a complete beginner to cloud and data, some parts felt a little rushed."
"If you have some SQL background, the initial modules might feel a bit slow, but it picks up."
"Good pace overall, assuming some basic familiarity with data concepts."
SQL and BigQuery querying explained well.
"The explanations on SQL queries specific to BigQuery were very clear and easy to follow."
"I found the sections on exploring data with SQL in BigQuery particularly helpful."
"Even without much prior SQL knowledge, I could understand and write the queries."
Hands-on practice reinforces learning.
"The hands-on labs provided great practice and helped solidify my understanding."
"I really benefited from the practical exercises within BigQuery."
"The lab environment, when it worked, was great for applying concepts immediately."
Provides a solid start for GCP data tools.
"It gives a solid foundation for anyone wanting to learn about data on Google Cloud Platform."
"This course is an excellent introduction to BigQuery and the data landscape in Google Cloud."
"I feel well-prepared to move on to the next course in the specialization."
Some technical issues reported with labs.
"Occasionally ran into technical problems with the lab setup."
"The cloud environment for labs was sometimes slow or buggy."
"Had some minor frustrations getting the labs to run correctly."
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 and Preparing your Data with BigQuery with these
activities:
Connect with experienced data analysts
Show steps
Gain valuable insights and guidance from experienced professionals in the field.
Browse courses on
Mentorship
Show steps
-
Attend industry events or join online communities.
-
Reach out to professionals on LinkedIn or other platforms.
Review machine learning concepts
Show steps
Strengthen foundational knowledge in machine learning to enhance understanding of advanced data analysis techniques.
Browse courses on
Machine Learning
Show steps
-
Review online articles or textbooks on machine learning concepts.
-
Complete practice exercises or quizzes on machine learning algorithms.
Review SQL syntax
Show steps
Brush up on the basics of SQL to prepare for working with BigQuery.
Browse courses on
SQL
Show steps
-
Review online tutorials on SQL basics.
-
Practice writing queries in an online SQL editor.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow along with BigQuery tutorials
Show steps
Gain hands-on experience with BigQuery through guided tutorials to reinforce course concepts.
Browse courses on
BigQuery
Show steps
-
Sign up for a free Google Cloud account.
-
Follow the BigQuery tutorials in the Google Cloud documentation.
Practice data exploration and transformation in BigQuery
Show steps
Develop proficiency in using BigQuery by completing practice exercises.
Browse courses on
BigQuery
Show steps
-
Create a new dataset in BigQuery.
-
Import sample data into the dataset.
-
Write queries to explore and transform the data.
Build a data visualization dashboard
Show steps
Apply your skills to create a meaningful data visualization dashboard that showcases your understanding of data analysis.
Browse courses on
Data Visualization
Show steps
-
Identify a dataset that you are interested in.
-
Design the layout and visualizations for your dashboard.
-
Build the dashboard using a data visualization tool.
Mentor a beginner in SQL and BigQuery
Show steps
Enhance your understanding of the course material by sharing your knowledge and helping others.
Browse courses on
Mentoring
Show steps
-
Identify a beginner who is interested in learning SQL and BigQuery.
-
Schedule regular sessions to provide guidance and support.
-
Provide constructive feedback and encouragement.
Organize course materials for future reference
Show steps
Maximize learning outcomes by organizing and reviewing course materials regularly.
Show steps
-
Create a dedicated folder or notebook for course materials.
-
Organize materials into sections, such as notes, assignments, and quizzes.
-
Review materials periodically to reinforce learning.
Connect with experienced data analysts
Show steps
Gain valuable insights and guidance from experienced professionals in the field.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Attend industry events or join online communities.
- Reach out to professionals on LinkedIn or other platforms.
Review machine learning concepts
Show steps
Strengthen foundational knowledge in machine learning to enhance understanding of advanced data analysis techniques.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review online articles or textbooks on machine learning concepts.
- Complete practice exercises or quizzes on machine learning algorithms.
Review SQL syntax
Show steps
Brush up on the basics of SQL to prepare for working with BigQuery.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review online tutorials on SQL basics.
- Practice writing queries in an online SQL editor.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow along with BigQuery tutorials
Show steps
Gain hands-on experience with BigQuery through guided tutorials to reinforce course concepts.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Sign up for a free Google Cloud account.
- Follow the BigQuery tutorials in the Google Cloud documentation.
Practice data exploration and transformation in BigQuery
Show steps
Develop proficiency in using BigQuery by completing practice exercises.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Create a new dataset in BigQuery.
- Import sample data into the dataset.
- Write queries to explore and transform the data.
Build a data visualization dashboard
Show steps
Apply your skills to create a meaningful data visualization dashboard that showcases your understanding of data analysis.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify a dataset that you are interested in.
- Design the layout and visualizations for your dashboard.
- Build the dashboard using a data visualization tool.
Mentor a beginner in SQL and BigQuery
Show steps
Enhance your understanding of the course material by sharing your knowledge and helping others.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Identify a beginner who is interested in learning SQL and BigQuery.
- Schedule regular sessions to provide guidance and support.
- Provide constructive feedback and encouragement.
Organize course materials for future reference
Show steps
Maximize learning outcomes by organizing and reviewing course materials regularly.
Show steps
Show steps
Show steps
- Create a dedicated folder or notebook for course materials.
- Organize materials into sections, such as notes, assignments, and quizzes.
- Review materials periodically to reinforce learning.
Career center
Learners who complete Exploring and Preparing your Data with BigQuery will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
In the role of a Data Analyst, you will be primarily responsible for collecting, cleaning, and analyzing data to help organizations make informed decisions. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need to succeed in this role. The course covers topics such as SQL, BigQuery, and Dataprep, which are essential tools for data analysts.
Data Scientist
Data Scientist
Working as a Data Scientist involves using scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course, Exploring and Preparing your Data with BigQuery, may be useful as it can help you build a foundation in data analysis and data preparation, which are important aspects of data science. The course covers topics such as SQL, BigQuery, and Dataprep, which are commonly used by data scientists.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining the infrastructure that supports data storage, processing, and analysis. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills needed for this role. The course covers topics such as BigQuery, which is a cloud-based data warehouse that is often used by data engineers for data storage and analysis.
Business Analyst
Business Analyst
As a Business Analyst, you will be analyzing business needs and processes to improve efficiency and effectiveness. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by business analysts to extract insights from data.
Database Administrator
Database Administrator
A Database Administrator is responsible for managing and maintaining database systems. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as BigQuery, which is a cloud-based data warehouse that is often used by database administrators for data storage and management.
Data Architect
Data Architect
A Data Architect is responsible for designing and managing the architecture of data systems. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as BigQuery, which is a cloud-based data warehouse that is often used by data architects for data storage and analysis.
Software Engineer
Software Engineer
As a Software Engineer, you will be designing, developing, and maintaining software systems. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by software engineers for data-related tasks.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst is responsible for using mathematical and statistical models to analyze data and make predictions. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by quantitative analysts for data-related tasks.
Market Researcher
Market Researcher
As a Market Researcher, you will be conducting research to understand market trends and customer behavior. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by market researchers for data-related tasks.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data to make recommendations on investments and financial decisions. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by financial analysts for data-related tasks.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by operations research analysts for data-related tasks.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by actuaries for data-related tasks.
Statistician
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, and interpret data. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by statisticians for data-related tasks.
Data Management Specialist
Data Management Specialist
A Data Management Specialist is responsible for managing and maintaining data assets. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as BigQuery, which is a cloud-based data warehouse that is often used by data management specialists for data storage and management.
Data Privacy Analyst
Data Privacy Analyst
A Data Privacy Analyst is responsible for ensuring that data is collected, used, and stored in a compliant manner. This course, Exploring and Preparing your Data with BigQuery, may be useful for developing the skills you need for this role. The course covers topics such as SQL, which is a commonly used language for data analysis and is often used by data privacy analysts for data-related tasks.
For more career information including salaries, visit:
OpenCourser.com/course/g7y6xz/exploring
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 and Preparing your Data with BigQuery.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and statistical modeling. It valuable resource for anyone who wants to learn more about statistical learning.
Save
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about pattern recognition and machine learning.
Provides a comprehensive overview of the Pandas library for data analysis in Python. It covers a wide range of topics, including data manipulation, data visualization, and statistical modeling. It valuable resource for anyone who wants to learn more about Pandas.
Provides a comprehensive overview of the Python programming language for data analysis. It covers a wide range of topics, including data manipulation, data visualization, and statistical modeling. It valuable resource for anyone who wants to learn more about Python for data analysis.
Save
Provides a comprehensive overview of machine learning for beginners. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn more about machine learning.
Provides a comprehensive overview of the RStudio integrated development environment (IDE) for R. It covers a wide range of topics, including data manipulation, data visualization, and statistical modeling. It valuable resource for anyone who wants to learn more about RStudio.
Provides a comprehensive overview of deep learning with Python. 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 with Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/g7y6xz/exploring
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Effort
1 week of study, 5-7 hours/week
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Transcript
Français
This course belongs to a
collection
called
From Data to Insights with Google Cloud. It's comprised of five courses:
- Géopolitique de l'Europe
- Applying Machine Learning to your Data with Google Cloud
- Achieving Advanced Insights with BigQuery
- Creating New BigQuery Datasets and Visualizing Insights
- Exploring and Preparing your Data with BigQuery (viewing)
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