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Curtis Harris

Data visualization is becoming more commonplace every day. In this course, you will learn why data visualization is on the rise; why you should care about data visualization; and learn strategies to be an effective data visualization designer.

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Data visualization is becoming more commonplace every day. In this course, you will learn why data visualization is on the rise; why you should care about data visualization; and learn strategies to be an effective data visualization designer.

As data visualization rises in popularity across companies worldwide, so do poor data visualization practices. In this course, Data Visualization: Best Practices, you will gain the ability to build visually-pleasing charts that effectively communicate your message. First, you will learn the basic concept of data visualization, why the field is growing, and how data viz can make an impact. Next, you will discover a variety of effective chart types and learn the design practices that make them effective. Finally, you will explore how to leverage preattentive attributes in your visualizations in order to enable easy data interpretation. When you are finished with this course, you will have the skills and knowledge of data visualization needed to build visually-appealing, impactful, and effective charts in any data visualization software.

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What's inside

Syllabus

Course Overview
The What and Why of Data Visualization
Data Visualization Concepts and Practices

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops foundational concepts and practices in data visualization, which are core skills for data analysts and data scientists
Taught by Curtis Harris, who are recognized for their work in data visualization and design
Covers a variety of effective chart types and explains the design practices that make them effective
Examines the basic concept of data visualization and explains why the field is growing
Explores how to leverage preattentive attributes in visualizations in order to enable easy data interpretation

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Visualization: Best Practices with these activities:
Excel Skills Review
Review your Excel skills to ensure proficiency in data manipulation and analysis techniques, which are essential for data visualization.
Browse courses on Excel
Show steps
Data Visualization Made Simple
Read this book to gain foundational knowledge on data visualization principles and best practices.
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Setting Up Tableau
Walk through tutorials on installing and setting up Tableau for your projects to ensure the environment is ready for use.
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  • Refer to Tableau documentation
  • Watch online video tutorials
  • Follow step-by-step guides
Five other activities
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Show all eight activities
Creating Effective Charts in Excel
Enhance your proficiency in creating charts in Excel, a commonly used tool for data visualization tasks.
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  • Explore Excel's charting capabilities
  • Customize charts for clarity and impact
Data Cleaning Practice
Practice data cleaning techniques to familiarize yourself with common challenges, improving your ability to work with messy datasets.
Show steps
  • Use real-world datasets with errors
  • Clean data using different techniques
  • Validate cleaned data for accuracy
Interactive Data Visualization Dashboard
Create a data visualization dashboard that demonstrates your understanding of effective visualization techniques.
Show steps
  • Select a dataset
  • Design and build the dashboard
  • Publish and share the dashboard
Data Visualization for Nonprofits
Gain practical experience by volunteering to create data visualizations for nonprofit organizations.
Show steps
  • Identify a suitable nonprofit organization
  • Analyze their data and identify needs
  • Develop and deliver data visualizations
Data Visualization Blog Post
Share your insights on a specific data visualization topic by writing a blog post.
Show steps
  • Choose a topic and research
  • Write and edit the blog post
  • Publish and promote the post

Career center

Learners who complete Data Visualization: Best Practices will develop knowledge and skills that may be useful to these careers:
Business Intelligence Analyst
A Business Intelligence Analyst is responsible for collecting, analyzing, and presenting data to help businesses make better decisions. This course will give you the skills and knowledge you need to succeed as a Business Intelligence Analyst with its comprehensive coverage of data visualization best practices. In this role, you will use these best practices to create visuals that communicate key insights and trends.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data in order to help businesses make better decisions. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to use best practices to visualize data in a way that communicates key insights and trends.
Tableau Developer
Tableau Developers are responsible for designing, building, and maintaining data visualizations using Tableau software. This course will give you the skills and knowledge you need to succeed in this role by teaching you the best practices of data visualization as well as the concepts and practices vital to Tableau.
Data Journalist
Data Journalists are responsible for using data to tell stories. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both engaging and informative.
Statistician
Statisticians are responsible for collecting, analyzing, and interpreting data in order to provide insights. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both accessible and impactful.
Quantitative Analyst
Quantitative Analysts are responsible for using mathematical and statistical models to analyze data. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both clear and insightful.
Market Researcher
Market Researchers are responsible for collecting and analyzing data about customers and markets. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both informative and persuasive.
Academic Researcher
Academic Researchers are responsible for conducting research and publishing their findings. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both clear and persuasive.
Information Architect
Information Architects are responsible for designing and organizing the structure and presentation of information. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to use best practices to visualize data in a way that makes it easy for users to find and understand.
Financial Analyst
Financial Analysts are responsible for analyzing financial data and making recommendations about investments. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both clear and informative.
Data Scientist
Data Scientists are responsible for using data to solve business problems. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to properly visualize data in order to make informed decisions.
User Experience (UX) Designer
UX Designers are responsible for designing user interfaces that are both visually appealing and easy to use. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to use best practices to visualize data in a way that is both engaging and informative.
Consultant
Consultants are responsible for providing expert advice to clients. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that is both clear and persuasive.
Data Visualization Analyst
A Data Visualization Analyst is responsible for gathering and visually representing data in a way that is both accessible and impactful. By using the best practices you learn in Data Visualization: Best Practices, you will be able to generate comprehensive visualizations to help your company understand what their data is revealing. In this role, you will be responsible for choosing the best charts and designs for the type of data you are asked to visualize. This course will give you the skills and knowledge you need to succeed.
Product Manager
Product Managers are responsible for planning, developing, and marketing products. This course will give you the skills and knowledge you need to succeed in this role by teaching you how to visualize data in a way that helps you make better decisions about your products.

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Visualization: Best Practices.
This classic work on data visualization must-read for anyone who wants to learn about the principles of effective visual communication. Tufte provides a wealth of examples and case studies to illustrate how to design charts and graphs that are both informative and visually appealing.
Provides a comprehensive introduction to data visualization, covering the basics of visual perception, data types, and chart types. It also offers practical guidance on how to design effective visualizations and communicate data clearly.
Must-read for anyone who wants to learn how to create beautiful and informative visualizations with ggplot2. Wickham covers all the basics, from choosing the right chart type to adding interactivity.
Provides a comprehensive introduction to R, a popular programming language for data science. Wickham covers everything from the basics of R to advanced topics like machine learning and data visualization.
Provides a comprehensive introduction to Python, a popular programming language for data science. Raschka covers everything from the basics of Python to advanced topics like machine learning and data visualization.
Provides a clear and concise overview of the different types of data visualizations and how to choose the right chart for the right data. Few also offers practical guidance on how to design effective visualizations that are both informative and visually appealing.
Provides a clear and concise overview of the principles of dashboard design. Few covers everything from choosing the right layout to designing effective visualizations.
This practical guide to data visualization provides step-by-step instructions on how to create effective visualizations using a variety of software tools. Sosulski covers all the basics, from choosing the right chart type to adding interactivity and storytelling.
Provides a comprehensive guide to designing and building effective dashboards. Wexler covers everything from choosing the right data to selecting the right visualization.
Provides a hands-on introduction to data visualization using Python and JavaScript. VanderPlas covers everything from the basics of data visualization to creating interactive dashboards.
Provides a practical guide to how to use data visualization to tell stories and communicate insights. Knaflic covers all the basics, from gathering data to choosing the right visuals to presenting your findings.
Great introduction to Power BI, a popular data visualization software. Alexander covers all the basics, from getting started with Power BI to creating interactive dashboards.
Great introduction to Google Data Studio, a free data visualization software. Miller covers all the basics, from creating dashboards to adding interactive elements.
Great introduction to data visualization for beginners. Zhuhadar covers all the basics, from choosing the right chart type to adding interactivity.

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