Foundations: Data, Data, Everywhere from Coursera

This is the first course in the Google Data Analytics Certificate. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks using the best tools and resources.

Learners who complete this certificate program will be equipped to apply for introductory-level jobs as data analysts. No previous experience is necessary.

By the end of this course, learners will:

- Gain an understanding of the practices and processes employed by a junior or associate data analyst in their day-to-day job.

- Learn about key analytical skills (data cleaning, data analysis, data visualization) and tools (spreadsheets, SQL, R programming, Tableau) that you can add to your professional toolbox.

- Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process.

- Evaluate the role of analytics in the data ecosystem.

- Conduct an analytical thinking self-assessment.

- Explore job opportunities available to you upon program completion, and learn about best practices you can leverage during your job search.

What's inside

Syllabus

Introducing data analytics and analytical thinking

Data helps us make decisions in both everyday life and in business. In this part of the course, you’ll learn how data analysts use a variety of tools and skills to inform those decisions. You’ll also get to know more about this course and the overall program expectations.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides learners with both theoretical and practical knowledge of data analytics

The hands-on component of the course prepares learners for the practical aspects of data analysis

Taught by Google Data Analysts, ensuring learners are taught by experts in the field

Delves into the data analysis process, familiarizing learners with the different stages and methodologies involved

Provides opportunities for learners to gain hands-on experience through the use of common data analysis tools, such as spreadsheets, SQL, and Tableau

Focuses on the analytical thinking skills and job responsibilities that are essential for junior data analysts

Reviews summary

Comprehensive introduction to data analytics fundamentals

According to students, this course is a highly effective starting point for anyone new to data analytics, providing a clear and comprehensive introduction to the field. Learners appreciate its focus on foundational concepts like the data life cycle and analytical thinking. The course effectively introduces key tools such as spreadsheets, SQL, R programming, and Tableau, laying a strong groundwork for future learning without expecting prior experience. However, some learners note it remains high-level, emphasizing breadth over depth, which may not satisfy those seeking deep dives or extensive hands-on coding in specific tools. It’s ideal for setting the stage for a career in data analytics, with many finding the career insights helpful.

Offers valuable insights into data analyst roles and job search strategies.

"I especially found the sections on analytical thinking and job opportunities insightful for my career path."

"It helped me understand what a data analyst does day-to-day and how this certificate can help me land a job."

"The course explores job opportunities and shares best practices for the job search, which I found very helpful."

Covers essential data analysis concepts, tools, and processes comprehensively.

"It truly sets the stage for the rest of the Google certificate. I found the content on data life cycle and analytical thinking very foundational."

"I particularly liked the overview of different tools like spreadsheets, SQL, and Tableau – it gave me a good sense of what to learn next."

"The content is very practical and directly applicable to what a junior analyst does. It's a solid foundation."

Provides a clear and gentle introduction for those new to data analytics.

"I had no prior experience and this course made complex concepts easy to understand. Highly recommend for beginners."

"A great starting point for anyone looking to enter the data field. The pace was just right for someone new to the subject."

"This course is perfect for complete beginners. It covers a broad range of topics without getting too deep, which is exactly what I needed."

May be too slow or repetitive for those with prior data or tech experience.

"Too basic. If you have any prior experience with data or even basic Excel, much of this will be review."

"For me, with a little tech background, it felt a bit slow or repetitive in parts, covering common sense concepts."

"I was hoping for more practical application or deeper dives into the tools mentioned, much of it was very elementary."

Introduces tools without providing deep, practical hands-on application.

"It felt a bit too high-level at times. I wish there were more hands-on exercises for SQL or R, instead of just talking about them."

"I didn't feel like I gained any tangible skills just from this course. Don't expect to master tools, it needs more actual 'doing'."

"Good as an intro, but for me, it lacked the practical application I was hoping for to truly learn the tools."

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 Foundations: Data, Data, Everywhere with these activities:

Review previous data analytics experience

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Reviewing your previous experiences will help fill in any gaps in your knowledge and refresh you on the basics before diving into the course.

Browse courses on Data Preparation

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Think back to projects or tasks you've worked on that involved data analysis.
Identify the specific skills and concepts you used in those projects.
Refresh your understanding of those concepts by reviewing online resources or taking practice quizzes.

Complete online tutorials on data analysis tools

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Guided tutorials can help you quickly learn the basics of the key data analysis tools used by Google data analysts, which will give you a strong foundation for the course.

Browse courses on Spreadsheets

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Identify the specific data analysis tools that are covered in the course.
Find online tutorials or courses that cover those tools.
Follow the tutorials and complete the exercises.
Apply what you've learned by working on small data analysis projects.

Engage in discussion forums with other learners

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Engaging with other learners through discussion forums can help you clarify your understanding of the course material, learn from others' experiences, and build a network of connections.

Browse courses on Data Analytics

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Join the discussion forums for the course.
Actively participate in the discussions by asking questions, answering questions, and sharing your insights.
Connect with other learners who share your interests and collaborate on projects.

Four other activities

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Solve data analysis practice problems

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Solving practice problems will help you develop your data analysis skills and prepare you for the challenges you'll face in the course.

Browse courses on Data Cleaning

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Find online resources or textbooks that provide data analysis practice problems.
Start with easier problems and gradually work your way up to more challenging ones.
Check your answers against the provided solutions and identify areas where you need improvement.
Review the concepts and techniques you're struggling with and practice them more.

Mentor other learners in the course

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Mentoring other learners can help you reinforce your understanding of the course material, develop your leadership skills, and make a positive contribution to the community.

Browse courses on Data Analytics

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Identify learners who are struggling with the course material or who are new to data analytics.
Offer to help them by answering their questions, providing guidance, and sharing your resources.
Meet with your mentees regularly to provide support and encouragement.

Develop a data analysis portfolio

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Creating a portfolio of your data analysis work will not only showcase your skills to potential employers, but also help you reflect on your progress and identify areas for growth.

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Identify a few data analysis projects you've worked on that demonstrate your skills and knowledge.
Develop a website or online portfolio to showcase your projects.
Write detailed descriptions of each project, including the problem you solved, the data you used, the methods you employed, and the results you achieved.
Include visualizations and other supporting materials to illustrate your work.

Contribute to open-source data analysis projects

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Contributing to open-source data analysis projects can help you develop your skills, learn from others, and make a positive impact on the community.

Browse courses on Data Analytics

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Identify open-source data analysis projects that align with your interests and skills.
Start by contributing in small ways, such as fixing bugs or adding documentation.
Gradually take on more challenging tasks, such as developing new features or refactoring code.

Career center

Learners who complete Foundations: Data, Data, Everywhere will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst is responsible for collecting and analyzing data to help businesses make better decisions. This course teaches you the skills needed to perform data analysis and communication. You'll learn how to clean data, analyze data, and visualize data using a variety of tools. You'll also learn how to communicate your findings to stakeholders. This course is a great way to get started in a career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

A Business Analyst works with businesses to improve their performance. They use data analysis to identify problems and opportunities, and they develop recommendations for improvement. This course teaches you the skills needed to be a Business Analyst. You'll learn how to collect and analyze data, and you'll learn how to develop and communicate recommendations. This course is a great way to get started in a career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Data Scientist

A Data Scientist uses data to solve problems and make predictions. They use a variety of techniques, including machine learning and artificial intelligence. This course teaches you the skills needed to be a Data Scientist. You'll learn how to collect and analyze data, and you'll learn how to develop and communicate models. This course is a great way to get started in a career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Market Researcher

A Market Researcher collects and analyzes data about markets and consumers. They use this data to help businesses make better decisions about products, services, and marketing campaigns. This course teaches you the skills needed to be a Market Researcher. You'll learn how to collect and analyze data, and you'll learn how to develop and communicate insights. This course is a great way to get started in a career as a Market Researcher.

See salaries and explore the career path for Market Researcher

Statistician

A Statistician uses data to make inferences about the world. They use a variety of techniques, including probability and statistics. This course teaches you the skills needed to be a Statistician. You'll learn how to collect and analyze data, and you'll learn how to develop and communicate models. This course is a great way to get started in a career as a Statistician.

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Financial Analyst

A Financial Analyst uses data to make decisions about investments. They use a variety of techniques, including financial modeling and analysis. This course teaches you the skills needed to be a Financial Analyst. You'll learn how to collect and analyze data, and you'll learn how to develop and communicate models. This course is a great way to get started in a career as a Financial Analyst.

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Operations Research Analyst

An Operations Research Analyst uses data to improve the efficiency and effectiveness of organizations. They use a variety of techniques, including optimization and simulation. This course teaches you the skills needed to be an Operations Research Analyst. You'll learn how to collect and analyze data, and you'll learn how to develop and communicate models. This course is a great way to get started in a career as an Operations Research Analyst.

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Software Engineer

A Software Engineer designs, develops, and maintains software systems. They use a variety of programming languages and techniques. This course teaches you the skills needed to be a Software Engineer. You'll learn how to design, develop, and test software systems. This course is a great way to get started in a career as a Software Engineer.

See salaries and explore the career path for Software Engineer

Computer Scientist

A Computer Scientist conducts research in the field of computer science. They use a variety of techniques, including algorithms, data structures, and artificial intelligence. This course teaches you the skills needed to be a Computer Scientist. You'll learn about the fundamental principles of computer science, and you'll learn how to design and develop software systems. This course is a great way to get started in a career as a Computer Scientist.

See salaries and explore the career path for Computer Scientist