Data integrity is critical to successful analysis. In this 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 sample size and understand how to avoid sampling bias. All of these methods will help you ensure your analysis is successful.
The Importance of Integrity
The Importance of Integrity
This course is part of Google Data-Driven Decision Making Specialization
Instructor: Google Career Certificates
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Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Define different types of data integrity and identify risks to data integrity.
Describe the benefits of documenting data cleaning process.
Describe strategies that can be used to address insufficient data.
Describe the benefits of documenting the data cleaning process
Skills you'll gain
Details to know
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Recently updated!
September 2025
Assessments
6 assignments
Taught in English
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This course is part of the Google Data-Driven Decision Making Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Data integrity is critical to successful analysis. In this module, you’ll explore methods and steps that analysts take to check their data for integrity.
What's included
2 videos3 readings1 assignment
In this module, you will learn about the importance of sample size and how to deal with insufficient data. You’ll also learn about pre-cleaning activities that must be performed before running data analysis.
What's included
2 videos2 readings2 assignments
This module explores strategies to test the data and determine the best representative sample size.
What's included
2 videos2 readings1 assignment
This module explores evaluating data reliability and introduces the concept of margin of error.
What's included
1 video1 reading2 assignments
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Frequently asked questions
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.
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.
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.
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