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.
Process Data from Dirty to Clean
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Process Data from Dirty to Clean
This course is part of Google Data Analytics Professional Certificate
Instructor: Google Career Certificates
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Gain insight into a topic and learn the fundamentals.
4.8
(18,167 reviews)
Beginner level
Recommended experience
Flexible schedule
Approx. 16 hours
Learn at your own pace
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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
See how employees at top companies are mastering in-demand skills
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
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 assignments1 plugin
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
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
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
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
4.9 (5,588 ratings)Offered by
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4.8
18,167 reviews
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Showing 3 of 18167
RH
5
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
OO
5
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
RK
4
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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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.
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.
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.
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Financial aid available,