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Prepare Data for Exploration

This is the third course in the Google Data Analytics Certificate. As you continue to build on your understanding of the topics from the first two courses, you’ll be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives, and how to organize and protect your data. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with 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:

- Find out how analysts decide what data to collect for analysis.

- Learn about structured and unstructured data, data types, and data formats.

- Discover how to identify different types of bias in data to help ensure data credibility.

- Explore how analysts use spreadsheets and SQL within databases and data sets.

- Examine open data and the relationship between, and importance of, data ethics and data privacy.

- Gain an understanding of how to access databases and extract, filter, and sort the data they contain.

- Learn best practices for organizing data and keeping it secure.

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What's inside

Syllabus

Data types and structures

A massive amount of data is generated every single day. In this part of the course, you will discover how this data is generated and how analysts decide which data to use for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for analysis.

Data responsibility

Before you work with data, you must confirm that it is unbiased and credible. After all, if you start your analysis with unreliable data, you won’t be able to trust your results. In this part of the course, you will learn to identify bias in data and to ensure your data is credible. You’ll also explore open data and the importance of data ethics and data privacy.

Database essentials

When you analyze large datasets, you’ll access much of the data from a database. In this part of the course, you will learn about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also explore metadata to discover its many facets and how analysts use it to better understand their data.

Organize and protect data

Good organizational skills are a big part of most types of work, especially data analytics. In this part of the course, you will learn best practices for organizing data and keeping it secure. You’ll also understand how analysts use file naming conventions to help them keep their work organized.

Engage in the data community

Having a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you will explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by experienced data analysts from Google, who are recognized for their work in this field

Develops practical data analytics skills, including data extraction, organization, and protection

Builds a strong foundation in data analysis for beginners, providing a clear starting point

Emphasizes data credibility and ethics, ensuring learners can work with reliable data

Includes hands-on exercises and real-world examples, providing practical experience

Requires no prior experience, making it accessible to learners from various backgrounds

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Reviews summary

Data wrangling: preparing a dataset

The course titled "Prepare Data for Exploration" is the third in a series of courses that form the Google Data Analytics Professional Certificate, offered through Coursera. This course focuses on the essential techniques and tools for preparing data for exploration and analysis. It covers a wide range of topics, including data wrangling, data cleaning, data transformation, feature engineering, and dealing with missing values. The course is designed for beginners with little to no prior experience in data analysis, and it provides a practical, hands-on approach to learning the material. Through interactive exercises, quizzes, and assignments, learners gain experience with real-world datasets and industry-standard tools such as Google Sheets, SQL, and Python. The course also emphasizes the importance of understanding the ethical implications of data collection and use, as well as the value of building a professional network and online presence. Upon completion of the course, learners will have a solid foundation in data preparation techniques and be well-equipped to pursue further studies or careers in data analysis.

The course extensively covers various tools and techniques commonly used in data preparation, including Google Sheets, SQL, and Python. I appreciated the practical guidance on how to leverage these tools effectively for data exploration purposes.

"The course extensively covered various tools and techniques commonly used in data preparation, including Google Sheets, SQL, and Python."

"I appreciated the practical guidance on how to leverage these tools effectively for data exploration purposes."

I appreciated the hands-on nature of the course. The assignments and quizzes were well-designed and allowed me to apply the concepts learned in a practical manner. The step-by-step instructions and the provided datasets were instrumental in helping me grasp the techniques effectively.

"I appreciated the hands-on nature of the course."

"The assignments and quizzes were well-designed and allowed me to apply the concepts learned in a practical manner."

"The step-by-step instructions and the provided datasets were instrumental in helping me grasp the techniques effectively."

The course also emphasizes the importance of understanding the ethical implications of data collection and use, as well as the value of building a professional network and online presence.

"The course also emphasizes the importance of understanding the ethical implications of data collection and use, as well as the value of building a professional network and online presence."

The course covered a wide range of topics related to data preparation, including data cleaning, data transformation, feature engineering, and dealing with missing values. This comprehensive approach ensured that I gained a holistic understanding of the subject matter.

"The course covered a wide range of topics related to data preparation, including data cleaning, data transformation, feature engineering, and dealing with missing values."

"This comprehensive approach ensured that I gained a holistic understanding of the subject matter."

The course instructor did an excellent job of explaining complex concepts in a clear and concise manner. The videos were engaging, and the use of real-life examples helped me understand the concepts better.

"The course instructor did an excellent job of explaining complex concepts in a clear and concise manner."

"The videos were engaging, and the use of real-life examples helped me understand the concepts better."

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 Prepare Data for Exploration with these activities:

Read "Data Analytics Made Accessible" by Anil Maheshwari

Show steps

This book provides a comprehensive overview of data analytics concepts and techniques, making it a valuable resource for anyone looking to build a foundation in this field.

View Big Data: Second Edition on Amazon

Show steps

Purchase or borrow a copy of the book.
Allocate time in your schedule to read the book.
Take notes and highlight important concepts as you read.

Review SQL

Show steps

Help you refresh your understanding of SQL syntax and concepts, making it easier to follow along with the course material.

Browse courses on SQL

Show steps

Review basic SQL commands such as SELECT, INSERT, UPDATE, and DELETE.
Practice writing queries to retrieve data from a database.
Review how to use SQL to create and modify tables.

Refine database fundamentals

Show steps

Reviewing basic database concepts will help you build a better foundation for the more complex topics covered in this course.

Browse courses on SQL

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Review your notes or a textbook on SQL syntax and commands.
Practice writing SQL queries to extract and filter data from simple tables.
Consider taking an online tutorial or completing some practice problems to reinforce your skills.

Six other activities

Expand to see all activities and additional details

Show all nine activities

Form a study group

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Collaborating with peers can enhance your understanding of the course material and provide support.

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Find a group of classmates who are willing to meet regularly to discuss the course material.
Set up a regular meeting time and location.
Take turns leading the discussions and presenting your findings.

Data analysis practice problems

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Completing practice problems will help you develop your ability to apply data analysis techniques and algorithms to real-world scenarios.

Browse courses on Data Analysis

Show steps

Find a set of practice problems online or in a textbook.
Work through the problems step-by-step, following the instructions carefully.
Check your answers against the provided solutions or consult with a tutor or instructor if you get stuck.

Learn advanced SQL techniques

Show steps

Expanding your knowledge of SQL will enable you to handle more complex data analysis tasks.

Browse courses on SQL

Show steps

Find an online tutorial or course that covers advanced SQL topics.
Follow the tutorial step-by-step, practicing the techniques and completing any exercises provided.
Apply your new skills to a real-world data analysis project.

Attend a data analytics workshop

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Workshops provide an opportunity to learn from experts and network with other professionals in the field.

Browse courses on Data Analytics

Show steps

Research upcoming data analytics workshops in your area or online.
Register for a workshop that aligns with your interests and learning goals.
Attend the workshop and actively participate in the activities and discussions.

Build a data visualization dashboard

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Creating a data visualization dashboard will allow you to practice your data analysis skills and present your findings in a clear and visually appealing way.

Browse courses on Data Visualization

Show steps

Choose a dataset that you are interested in analyzing.
Use a data visualization tool to create a dashboard that displays the key insights from your analysis.
Share your dashboard with others and get feedback on your work.

Contribute to an open-source data analytics project

Show steps

Contributing to an open-source project will give you hands-on experience with real-world data analytics problems and allow you to learn from others in the field.

Browse courses on Data Analytics

Show steps

Find an open-source data analytics project that you are interested in contributing to.
Read the project's documentation and familiarize yourself with its codebase.
Make a contribution to the project, such as fixing a bug or adding a new feature.

Career center

Learners who complete Prepare Data for Exploration will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst is a professional who uses data to help organizations make better decisions. They collect, clean, and analyze data to identify trends and patterns that can be used to improve business operations. This course can help you develop the skills you need to be a successful Data Analyst by teaching you how to find, organize, and analyze data. You will also learn about data ethics and privacy, which are important considerations for anyone working with data.

See salaries and explore the career path for Data Analyst

Business Analyst

A Business Analyst is a professional who helps organizations improve their business processes. They work with stakeholders to identify problems, analyze data, and develop solutions. This course can help you develop the skills you need to be a successful Business Analyst by teaching you how to find, organize, and analyze data. You will also learn about data ethics and privacy, which are important considerations for anyone working with data.

See salaries and explore the career path for Business Analyst

Data Scientist

A Data Scientist is a professional who uses data to solve complex problems. They use statistical and machine learning techniques to build models that can predict future outcomes. This course can help you develop the skills you need to be a successful Data Scientist by teaching you how to find, organize, and analyze data. You will also learn about data ethics and privacy, which are important considerations for anyone working with data.

See salaries and explore the career path for Data Scientist

Database Administrator

A Database Administrator is a professional who manages and maintains databases. They ensure that data is stored and organized in a way that makes it easy to access and use. This course can help you develop the skills you need to be a successful Database Administrator by teaching you how to access databases and extract, filter, and sort the data they contain. You will also learn about data ethics and privacy, which are important considerations for anyone working with data.

See salaries and explore the career path for Database Administrator

Software Engineer

A Software Engineer is a professional who designs, develops, and maintains software applications. They use their knowledge of programming languages and software development tools to create software that meets the needs of users. This course may be helpful for Software Engineers who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for developing software applications that use data.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

A Quantitative Analyst is a professional who uses mathematical and statistical models to analyze financial data. They use their knowledge of finance and mathematics to make investment decisions. This course may be helpful for Quantitative Analysts who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for developing financial models.

See salaries and explore the career path for Quantitative Analyst

Market Researcher

A Market Researcher is a professional who conducts research to understand consumer behavior. They use surveys, interviews, and other research methods to collect data about consumer needs and wants. This course may be helpful for Market Researchers who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for understanding consumer behavior.

See salaries and explore the career path for Market Researcher

Product Manager

A Product Manager is a professional who is responsible for the development and marketing of a product. They work with engineers, designers, and marketers to create a product that meets the needs of users. This course may be helpful for Product Managers who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for understanding user needs and developing successful products.

See salaries and explore the career path for Product Manager

Data Engineer

A Data Engineer is a professional who designs and builds data pipelines. They work with data scientists and other data professionals to ensure that data is available and accessible for analysis. This course may be helpful for Data Engineers who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for building data pipelines.

See salaries and explore the career path for Data Engineer

Statistician

A Statistician is a professional who uses statistical methods to collect, analyze, and interpret data. They work with researchers and other professionals to solve problems and make informed decisions. This course may be helpful for Statisticians who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for solving problems and making informed decisions.

See salaries and explore the career path for Statistician

Epidemiologist

An Epidemiologist is a professional who studies the distribution and determinants of disease in populations. They use statistical methods to analyze data and identify risk factors for disease. This course may be helpful for Epidemiologists who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for studying the distribution and determinants of disease.

See salaries and explore the career path for Epidemiologist

Financial Analyst

A Financial Analyst is a professional who analyzes financial data to make investment decisions. They use their knowledge of finance and economics to make recommendations on which stocks, bonds, and other investments to buy or sell. This course may be helpful for Financial Analysts who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for making investment decisions.

See salaries and explore the career path for Financial Analyst

Actuary

An Actuary is a professional who uses mathematical and statistical methods to assess risk. They work with insurance companies and other financial institutions to develop and manage insurance policies. This course may be helpful for Actuaries who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for assessing risk.

See salaries and explore the career path for Actuary

Operations Research Analyst

An Operations Research Analyst is a professional who uses mathematical and statistical methods to improve the efficiency of operations. They work with businesses and organizations to solve problems and make decisions. This course may be helpful for Operations Research Analysts who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for solving problems and making decisions.

See salaries and explore the career path for Operations Research Analyst

Data Mining Analyst

A Data Mining Analyst is a professional who uses data mining techniques to find patterns and trends in data. They work with businesses and organizations to identify opportunities and solve problems. This course may be helpful for Data Mining Analysts who want to learn more about data analysis. The course will teach you how to find, organize, and analyze data, which can be useful for finding patterns and trends in data.

See salaries and explore the career path for Data Mining Analyst

Reading list

We've selected 11 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 Prepare Data for Exploration.

Data Science for Business

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Provides a comprehensive overview of data science concepts and techniques. It covers topics such as data mining, machine learning, and statistical modeling. It valuable resource for learners who want to gain a deeper understanding of the field of data science.

Prepare Data for Exploration

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Data wrangling: preparing a dataset

Activities

Career center

Reading list

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