Process Data from Dirty to Clean

This course is part of Google Data Analytics Professional Certificate

Instructor: Google Career Certificates

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902,331 already enrolled

6 modules

Gain insight into a topic and learn the fundamentals.

18,764 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.

18,764 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

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

21 assignments

Taught in English

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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

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 videos Total 33 minutes

Introduction to data integrity 4 minutes
Why data integrity is important 3 minutes
Balance objectives with data integrity 3 minutes
Deal with insufficient data 4 minutes
The importance of sample size 3 minutes
Using statistical power 5 minutes
Determine the best sample size 5 minutes
Evaluate data reliability 6 minutes

10 readings Total 68 minutes

Course 4 overview 8 minutes
Helpful resources and tips 4 minutes
More about data integrity and compliance 8 minutes
Well-aligned objectives and data 8 minutes
When you find an issue with your data 4 minutes
Calculate sample size 8 minutes
When data isn't readily available 8 minutes
Sample size calculator 8 minutes
All about margin of error 8 minutes
Glossary terms from module 1 4 minutes

6 assignments Total 92 minutes

Test your knowledge on data integrity and analytics objectives 8 minutes
Self-Reflection: Pre-cleaning activities 20 minutes
Test your knowledge on insufficient data 8 minutes
Test your knowledge on testing your data 8 minutes
Test your knowledge on margin of error 8 minutes
Module 1 challenge 40 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 videos Total 66 minutes

Clean it up! 3 minutes
Why data cleaning is critical 6 minutes
Angie: I love cleaning data 1 minute
Recognize and remedy dirty data 5 minutes
Data-cleaning tools and techniques 6 minutes
Clean data from multiple sources 6 minutes
Data-cleaning features in spreadsheets 8 minutes
Optimize the data-cleaning process 14 minutes
Different data perspectives 10 minutes
Even more data-cleaning techniques 7 minutes

10 readings Total 72 minutes

What is dirty data? 8 minutes
Common data-cleaning pitfalls 8 minutes
Step-by-Step guide: Data-cleaning features in spreadsheets 8 minutes
Step-by-Step: Optimize the data-cleaning process 8 minutes
Workflow automation 8 minutes
Step-by-Step: Different data perspectives 8 minutes
Step-by-Step: Even more data-cleaning techniques 8 minutes
Working with .csv files 4 minutes
Develop your approach to cleaning data 8 minutes
Glossary terms from module 2 4 minutes

6 assignments Total 184 minutes

Test your knowledge on data cleaning 8 minutes
Hands-On Activity: Cleaning data with spreadsheets 60 minutes
Test your knowledge on the first steps toward clean data 8 minutes
Hands-On Activity: Clean data with spreadsheet functions 60 minutes
Test your knowledge on cleaning data in spreadsheets 8 minutes
Module 2 challenge 40 minutes

1 plugin Total 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 videos Total 49 minutes

Use SQL to clean data 1 minute
Sally: For the love of SQL 3 minutes
Understand SQL capabilities 3 minutes
Spreadsheets versus SQL 4 minutes
Widely used SQL queries 6 minutes
Evan: Having fun with SQL 3 minutes
Clean string variables using SQL 13 minutes
Advanced data-cleaning functions, part 1 6 minutes
Advanced data-cleaning functions, part 2 9 minutes

7 readings Total 42 minutes

How a junior data analyst uses SQL 4 minutes
SQL dialects and their uses 8 minutes
Review: Set up your BigQuery account 8 minutes
Review: Get started with BigQuery 8 minutes
Optional: Upload the customer dataset to BigQuery 4 minutes
Optional: Upload the store transactions dataset to BigQuery 8 minutes
Glossary terms from module 3 2 minutes

5 assignments Total 195 minutes

Hands-On Activity: Processing time with SQL 60 minutes
Hands-On Activity: Clean data using SQL 60 minutes
Test your knowledge on SQL queries 10 minutes
Self-Reflection: Challenges with SQL 20 minutes
Module 3 challenge 45 minutes

1 plugin Total 10 minutes

Data-cleaning with SQL functions 10 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 videos Total 28 minutes

Verify and report results 3 minutes
Confirm data-cleaning meets business expectations 5 minutes
Verification of data cleaning 8 minutes
Capture cleaning changes 6 minutes
Why documentation is important 3 minutes
Feedback and cleaning 2 minutes

5 readings Total 26 minutes

Step-by-Step: Verification of data cleaning 8 minutes
Data-cleaning verification checklist 4 minutes
Embrace changelogs 8 minutes
Advanced functions for speedy data cleaning 4 minutes
Glossary terms from module 4 2 minutes

4 assignments Total 76 minutes

Test your knowledge on manual data cleaning 8 minutes
Self-Reflection: Creating a changelog 20 minutes
Test your knowledge on documenting the cleaning process 8 minutes
Module 4 challenge 40 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

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Google Career Certificates

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Reviewed on Oct 26, 2021

Good content overall. However it will be nice to have the glossary for each week not mixed up with those from previous as it makes it hard to navigate and know which new words need to be learnt

Reviewed on Sep 22, 2025

I think this is the most important course in the Google Data Analytics course series. It has equipped me with practical skills for making data reliable for analysis and data-driven decision-making..

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!

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