This is the third course in the Google Data Analytics Certificate. As you continue to build on your understanding of the topics from the first two courses, you’ll be introduced to new topics that will help you gain practical data analytics skills. You’ll learn how to use tools like spreadsheets and SQL to extract and make use of the right data for your objectives, and how to organize and protect your data. 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.
Prepare Data for Exploration
Prepare Data for Exploration
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
(21,605 reviews)
Beginner level
Recommended experience
Flexible schedule
Approx. 19 hours
Learn at your own pace
97%
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What you'll learn
Explain what factors to consider when making decisions about data collection.
Discuss the difference between biased and unbiased data.
Describe databases with references to their functions and components.
Describe best practices for organizing data.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
24 quizzes, 5 assignments
Taught in English
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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
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Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 5 modules in this course
A massive amount of data is generated every single day. In this part of the course, you will discover how this data is generated and how analysts decide which data to use for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for analysis.
What's included
9 videos10 readings5 quizzes1 assignment2 plugins
Before you work with data, you must confirm that it is unbiased and credible. After all, if you start your analysis with unreliable data, you won’t be able to trust your results. In this part of the course, you will learn to identify bias in data and to ensure your data is credible. You’ll also explore open data and the importance of data ethics and data privacy.
What's included
12 videos4 readings4 quizzes2 assignments
When you analyze large datasets, you’ll access much of the data from a database. In this part of the course, you will learn about databases, including how to access them and extract, filter, and sort the data they contain. You’ll also explore metadata to discover its many facets and how analysts use it to better understand their data.
What's included
10 videos13 readings11 quizzes1 assignment
Good organizational skills are a big part of most types of work, especially data analytics. In this part of the course, you will learn best practices for organizing data and keeping it secure. You’ll also understand how analysts use file naming conventions to help them keep their work organized.
What's included
3 videos3 readings3 quizzes1 assignment1 plugin
Having a strong online presence can be a big help for job seekers of all kinds. In this part of the course, you will explore how to manage your online presence. You’ll also discover the benefits of networking with other data analytics professionals.
What's included
7 videos6 readings1 quiz
Instructor
Instructor ratings
4.8 (6,935 ratings)Offered by
Recommended if you're interested in Data Analysis
American Psychological Association
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Showing 3 of 21605
MG
5
Reviewed on Aug 8, 2023
I love how the course it's not limited to teach about the technical skills of a data analyst professional, but it also helps you discover some soft skills that make you a better human resource.
PK
4
Reviewed on Apr 11, 2021
This was a great course and it was in flow with the second course of the specialization. Gave good insights about bias, ethics, and protecting data. It also involved a lot of hands-on activities.
NS
4
Reviewed on Dec 31, 2021
I liked that some assignments had me use SQL and get more comfortable using it. However I would have liked more assignments using SQL and Sheets to get more practice. Otherwise was pretty fun.
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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.