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

本课程是 Google Data Analytics 专业证书的一部分

位教师：Google Career Certificates

933,726 人已注册

包含在中

了解更多

6个模块

深入了解一个主题并学习基础知识。

18,870 条评论

初级等级

推荐体验

灵活的计划

2 周在 10 小时一周

自行安排学习进度

98%

大多数学生喜欢此课程

6个模块

深入了解一个主题并学习基础知识。

18,870 条评论

初级等级

推荐体验

灵活的计划

2 周在 10 小时一周

自行安排学习进度

98%

大多数学生喜欢此课程

您将学到什么

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.

您将获得的技能

您将学习的工具

Google Sheets

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

21 项作业

授课语言：英语（English）

积累 Data Analysis 领域的专业知识

本课程是 Google Data Analytics 专业证书专项课程的一部分

在注册此课程时，您还会同时注册此专业证书。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
通过 Google 获得可共享的职业证书

该课程共有6个模块

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

单元详情

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.

涵盖的内容

8个视频10篇阅读材料6个作业

8个视频总计33分钟

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

10篇阅读材料总计68分钟

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

6个作业总计92分钟

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

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.

涵盖的内容

10个视频10篇阅读材料6个作业1个插件

10个视频总计66分钟

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

10篇阅读材料总计72分钟

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

6个作业总计184分钟

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

1个插件总计10分钟

Principles of data integrity 10分钟

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.

涵盖的内容

9个视频7篇阅读材料5个作业1个插件

9个视频总计49分钟

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

7篇阅读材料总计42分钟

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

5个作业总计195分钟

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

1个插件总计10分钟

Data-cleaning with SQL functions10分钟

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!

涵盖的内容

6个视频5篇阅读材料4个作业

6个视频总计28分钟

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

5篇阅读材料总计26分钟

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

4个作业总计76分钟

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

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.

涵盖的内容

3个视频2篇阅读材料

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

涵盖的内容

1个视频3篇阅读材料

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

授课教师评分

(5,797个评价)

Google Career Certificates

Google

386 门课程16,646,662 名学生

提供方

Google

学生评论

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

显示 3/18870 个

已于 Oct 27, 2023审阅

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

已于 Jul 7, 2025审阅

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...

已于 Oct 26, 2021审阅

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

查看更多评论