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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.

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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.

Enroll now

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.
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Module 1: Introduction ​to ​Data ​on Google ​Cloud
Understand the core principles behind Google Cloud and how to leverage them for big data analysis
Module 2: ​Big ​Data ​Tools ​Overview
Learn what are the key big data tools on Google Cloud that you will use to analyze, prepare, and visualize data
Module 3: ​Exploring ​your ​Data ​with SQL
Learn how to query your data with the basics of SQL (Structured Query Language) and practice writing queries in BigQuery
Module 4: ​BigQuery ​Pricing
Understand how pricing works in BigQuery and how you can best optimize your queries
Module 5: ​Cleaning ​and ​Transforming your ​Data
Understand the importance of creating high quality datasets and learn the tools that will help you transform your data
Module 6: Course Summary
Summary of the course key learning points

Good to know

Know what's good
, what to watch for
, 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

Google cloud platform: exploring and preparing your data with bigquery

Learners say this course is a largely positive introduction to exploring and preparing data with Google BigQuery. It includes engaging assignments and hands-on labs that start with the interface and progress to data analysis with SQL. The instructors are clear and knowledgeable, and the course is well-structured and easy to follow. Key features covered include BigQuery, DataPrep, and DataFusion, although some learners wished there was more coverage of Data Fusion. Though aimed at beginners, the course can also benefit experienced analysts and professionals who want to expand their knowledge of Google Cloud Platform and data preparation. Keep in mind, the course material may not be up-to-date, so it's advisable to check with Google Cloud Platform for the latest information.
Great course for beginners to learn the basics of BigQuery
"Good for learning the basics of BigQuery and some SQL data cleansing."
"This course is a brilliant course for anyone who is in the analytics field and is new to GCP and wants to learn."
Knowledgeable and engaging instructors
"Evan was a great instructor."
"I liked it very much! It sets a base to start working with BigQuery!"
Hands-on practice with labs and Qwiklabs
"I love easily Google teaches the concepts with very simple examples!"
"The online courses now became an important part of the world learning."
"The labs are a great way to learn and apply what you're learning."
Limited coverage and outdated information on Data Fusion
"I would remove data fusion part ... and give more insights on bigquery and cloud dataprep"
"cloud fusion was a complete garbage, fully messed hope so my review about that lecture will be solved soon."
"In the BigQuery section if the hyperlinks are not working for you..."
Some of the course material and Qwiklabs are outdated
"It would be better to have more challenging graded exercises and more practice without guidance."
"The links to the datasets don't work."
"The course reference GCP as it was 4 (four) years ago"

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
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
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
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
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
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
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
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
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.

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 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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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.
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.
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.

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