What is data analytics?

Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more. We use and create data everyday, like when we stream a show or song or post on social media. Data analytics is the collection, transformation, and organization of these facts to draw conclusions, make predictions, and drive informed decision-making.

Why start a career in data analytics?

The amount of data created each day is tremendous. Any time you use your phone, look up something online, stream music, shop with a credit card, post on social media, or use GPS to map a route, you’re creating data. Companies must continually adjust their products, services, tools, and business strategies to meet consumer demand and react to emerging trends. Because of this, data analyst roles are in demand and competitively paid. Data analysts make sense of data and numbers to help organizations make better business decisions. They prepare, process, analyze, and visualize data, discovering patterns and trends and answering key questions along the way. Their work empowers their wider team to make better business decisions.

Why enroll in the Google Data Analytics Certificate?

You will learn the skill set required for becoming a junior or associate data analyst in the Google Data Analytics Certificate. Data analysts know how to ask the right question; prepare, process, and analyze data for key insights; effectively share their findings with stakeholders; and provide data-driven recommendations for thoughtful action. You’ll learn these job-ready skills in our certificate program through interactive content (discussion prompts, quizzes, and activities) in under six months, with under 10 hours of flexible study a week. Along the way, you'll work through a curriculum designed with input from top employers and industry leaders, like Tableau, Accenture, and Deloitte. You’ll even have the opportunity to complete a case study that you can share with potential employers to showcase your new skill set. After you’ve graduated from the program, you’ll have access to career resources and be connected directly with employers hiring for open entry-level roles in data analytics.

What background is required?

No prior experience with spreadsheets or data analytics is required. All you need is high-school level math and a curiosity about how things work.

Do you need to be strong at math to succeed in this certificate?

You don't need to be a math all-star to succeed in this certificate. You need to be curious and open to learning with numbers (the language of data analysts). Being a strong data analyst is more than just math, it's about asking the right questions, finding the best sources to answer your questions effectively, and illustrating your findings clearly in visualizations.

What tools and platforms are taught in the curriculum?

You'll learn to use analysis tools and platforms such as spreadsheets (Google Sheets or Microsoft Excel), SQL, presentation tools (Powerpoint or Google Slides), Tableau, Python, and Kaggle.

Which “spreadsheet” platform is being taught?

Learners can self-select which platform they want to use throughout the program: Google Sheets or Microsoft Excel. It’s up to the learner’s preference, and all activities throughout the syllabus can be performed on either platform.

Do you need to take each course in course order?

We highly recommend completing the courses in the order presented because the content in each course builds on information from earlier lessons.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Certificate?

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Process Data from Dirty to Clean

Ends tomorrow! Save on skills that make you shine with 40% off 3 months of Coursera Plus. Save now

Process Data from Dirty to Clean

This course is part of Google Data Analytics Professional Certificate

Instructor: Google Career Certificates

932,575 already enrolled

Included with

Learn more

6 modules

Gain insight into a topic and learn the fundamentals.

18,862 reviews

Beginner level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

98%

Most learners liked this course

6 modules

Gain insight into a topic and learn the fundamentals.

18,862 reviews

Beginner level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

98%

Most learners liked this course

What you'll learn

Define different types of data integrity and identify risks to data integrity.
Apply basic SQL functions to clean string variables in a database.
Develop basic SQL queries for use on databases.
Describe the process of verifying data cleaning results.

Skills you'll gain

Tools you'll learn

Google Sheets

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

21 assignments

Taught in English

91%

of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your Data Analysis expertise

This course is part of the Google Data Analytics Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Google

There are 6 modules in this course

This is the fourth course in the Google Data Analytics Certificate. In this course, you’ll continue to build your understanding of data analytics and the concepts and tools that data analysts use in their work. You’ll learn how to check and clean your data using spreadsheets and SQL, as well as how to verify and report your data cleaning results. 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: - Check for data integrity. - Apply data cleaning techniques using spreadsheets. - Develop basic SQL queries for use on databases. - Use basic SQL functions to clean and transform data. - Verify the results of cleaning data. - Write an effective data cleaning report

Module details

Data integrity is critical to successful analysis. In this part of the course, you’ll explore methods and steps that analysts take to check their data for integrity. This includes knowing what to do when you don’t have enough data. You’ll also learn about random samples and understand how to avoid sampling bias. All of these methods will also help you ensure your analysis is successful.

What's included

8 videos10 readings6 assignments

8 videosTotal 33 minutes

Introduction to data integrity4 minutes
Why data integrity is important3 minutes
Balance objectives with data integrity3 minutes
Deal with insufficient data4 minutes
The importance of sample size3 minutes
Using statistical power5 minutes
Determine the best sample size 5 minutes
Evaluate data reliability6 minutes

10 readingsTotal 68 minutes

Course 4 overview8 minutes
Helpful resources and tips4 minutes
More about data integrity and compliance8 minutes
Well-aligned objectives and data 8 minutes
When you find an issue with your data4 minutes
Calculate sample size8 minutes
When data isn't readily available8 minutes
Sample size calculator8 minutes
All about margin of error8 minutes
Glossary terms from module 14 minutes

6 assignmentsTotal 92 minutes

Test your knowledge on data integrity and analytics objectives8 minutes
Self-Reflection: Pre-cleaning activities20 minutes
Test your knowledge on insufficient data8 minutes
Test your knowledge on testing your data8 minutes
Test your knowledge on margin of error8 minutes
Module 1 challenge40 minutes

Every data analyst wants to analyze clean data. In this part of the course, you’ll learn the difference between clean and dirty data. Then, you’ll practice cleaning data in spreadsheets and other tools.

What's included

10 videos10 readings6 assignments1 plugin

10 videosTotal 66 minutes

Clean it up!3 minutes
Why data cleaning is critical6 minutes
Angie: I love cleaning data1 minute
Recognize and remedy dirty data5 minutes
Data-cleaning tools and techniques6 minutes
Clean data from multiple sources6 minutes
Data-cleaning features in spreadsheets8 minutes
Optimize the data-cleaning process14 minutes
Different data perspectives10 minutes
Even more data-cleaning techniques7 minutes

10 readingsTotal 72 minutes

What is dirty data?8 minutes
Common data-cleaning pitfalls8 minutes
Step-by-Step guide: Data-cleaning features in spreadsheets8 minutes
Step-by-Step: Optimize the data-cleaning process 8 minutes
Workflow automation8 minutes
Step-by-Step: Different data perspectives8 minutes
Step-by-Step: Even more data-cleaning techniques8 minutes
Working with .csv files4 minutes
Develop your approach to cleaning data8 minutes
Glossary terms from module 24 minutes

6 assignmentsTotal 184 minutes

Test your knowledge on data cleaning8 minutes
Hands-On Activity: Cleaning data with spreadsheets60 minutes
Test your knowledge on the first steps toward clean data8 minutes
Hands-On Activity: Clean data with spreadsheet functions60 minutes
Test your knowledge on cleaning data in spreadsheets8 minutes
Module 2 challenge40 minutes

1 pluginTotal 10 minutes

Principles of data integrity 10 minutes

Knowing a variety of ways to clean data can make a data analyst’s job much easier. In this part of the course, you’ll use SQL to clean data from databases. In particular, you’ll explore how SQL queries and functions can be used to clean and transform your data before an analysis.

What's included

9 videos7 readings5 assignments1 plugin

9 videosTotal 49 minutes

Use SQL to clean data1 minute
Sally: For the love of SQL3 minutes
Understand SQL capabilities3 minutes
Spreadsheets versus SQL4 minutes
Widely used SQL queries6 minutes
Evan: Having fun with SQL 3 minutes
Clean string variables using SQL13 minutes
Advanced data-cleaning functions, part 16 minutes
Advanced data-cleaning functions, part 29 minutes

7 readingsTotal 42 minutes

How a junior data analyst uses SQL4 minutes
SQL dialects and their uses8 minutes
Review: Set up your BigQuery account8 minutes
Review: Get started with BigQuery8 minutes
Optional: Upload the customer dataset to BigQuery4 minutes
Optional: Upload the store transactions dataset to BigQuery8 minutes
Glossary terms from module 32 minutes

5 assignmentsTotal 195 minutes

Hands-On Activity: Processing time with SQL60 minutes
Hands-On Activity: Clean data using SQL60 minutes
Test your knowledge on SQL queries10 minutes
Self-Reflection: Challenges with SQL20 minutes
Module 3 challenge45 minutes

1 pluginTotal 10 minutes

Data-cleaning with SQL functions10 minutes

When you clean data, you make changes to the original dataset. It’s important to verify the changes you make are accurate and to let your teammates know about the changes. In this part of the course, you’ll learn to verify that data is clean and report your data cleaning results. With verified clean data, you’re ready to begin analyzing!

What's included

6 videos5 readings4 assignments

6 videosTotal 28 minutes

Verify and report results3 minutes
Confirm data-cleaning meets business expectations5 minutes
Verification of data cleaning8 minutes
Capture cleaning changes6 minutes
Why documentation is important3 minutes
Feedback and cleaning2 minutes

5 readingsTotal 26 minutes

Step-by-Step: Verification of data cleaning8 minutes
Data-cleaning verification checklist4 minutes
Embrace changelogs8 minutes
Advanced functions for speedy data cleaning4 minutes
Glossary terms from module 42 minutes

4 assignmentsTotal 76 minutes

Test your knowledge on manual data cleaning8 minutes
Self-Reflection: Creating a changelog20 minutes
Test your knowledge on documenting the cleaning process8 minutes
Module 4 challenge40 minutes

Creating an effective resume will help you in your data analytics career. In this part of the course, you’ll learn all about the job application process. Your focus will be on building a resume that highlights your strengths and relevant experience.

What's included

3 videos2 readings

Review the course glossary and prepare for the next course in the Google Data Analytics Certificate program.

What's included

1 video3 readings

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Instructor ratings

(5,797 ratings)

Google Career Certificates

Google

386 Courses16,612,077 learners

Offered by

Google

Learner reviews

5 stars
85.13%
4 stars
12.19%
3 stars
1.84%
2 stars
0.42%
1 star
0.39%

Showing 3 of 18862

Reviewed on Oct 27, 2023

Fun, concise, and on point course walking new folks through (or a great review for not so new folks) the process of identification, basic change management, and reporting for dataset validation

Reviewed on Jul 7, 2025

Great way of teaching, her lectures were outstaning and engaging, understood each and every concepts very clearly. Thank you Google and Coursera team for making us to interact with such personality...

Reviewed on Nov 5, 2022

Sally is the best instructor in this course so far. The content itself started of great but I feel it didn't cover enough data cleaning techniques in the second half of the course. Still recommend!

View more reviews