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This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which you will apply the concepts taught using a separate data source; this realistic project gives learners the practice and confidence necessary to connect, explore, and analyze data sources into the future.This course is also part of a certificate:

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This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which you will apply the concepts taught using a separate data source; this realistic project gives learners the practice and confidence necessary to connect, explore, and analyze data sources into the future.This course is also part of a certificate:

Data Analytics and Visualization Certificate

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What's inside

Learning objective

First, learners will learn the tableau interface and becoming familiar with the importance of data visualization in a business setting. then, learners will gain practice building many types of visualizations using different datasets. finally, learn how to combine multiple visualizations into a single dashboard, adding interactive features and instructive text so that business stakeholders can access the information needed to make decisions.

Good to know

Know what's good
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, and possible dealbreakers
Teaches a comprehensive range of Tableau features, from the basics of the interface to advanced data visualization techniques
Emphasizes hands-on practice through interactive videos and a capstone project, enabling students to immediately apply what they learn
Students can enhance their resume by earning a certificate in data analytics and visualization upon completing this course
Supports effective decision-making by teaching students to create interactive dashboards that clearly communicate data insights
Suitable for beginners who seek an introduction to data visualization concepts and Tableau software

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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 and Representation with these activities:
Data Visualization Fundamentals
Enhance understanding of essential data visualization principles and concepts before engaging with Tableau.
Browse courses on Data Visualization
Show steps
  • Review basic chart types and their applications.
  • Understand principles of data visualization and design.
Organize Course Materials
Establish a well-organized system for storing and managing course materials for easy reference and quick retrieval.
Show steps
  • Create a designated folder for course materials.
  • Categorize and sort files logically.
Tableau Tutorial Series
Reinforce understanding of Tableau concepts and techniques through structured and guided tutorials.
Show steps
  • Follow a Tableau tutorial series for beginners.
  • Go through hands-on exercises and examples.
Three other activities
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Show all six activities
Read Storytelling with Data
Enhance understanding of data visualization best practices for communicating insights effectively.
Show steps
  • Read Chapter 1: 'Why Storytelling?'
  • Identify key principles of effective data visualization.
Interactive Vizzes
Experiment with various interactive features in Tableau to enhance dashboard functionality and user engagement.
Show steps
  • Create a dashboard with interactive filters.
  • Add tooltips to provide additional information on hover.
Dashboard Design Project
Apply skills in creating a comprehensive and informative dashboard that meets specific business requirements.
Browse courses on Tableau Dashboard
Show steps
  • Identify the target audience and business question.
  • Design and develop a dashboard.
  • Incorporate interactive features and insightful annotations.

Career center

Learners who complete Data Visualization and Representation will develop knowledge and skills that may be useful to these careers:
Data Visualization Consultant
Data Visualization Consultants help businesses to develop understandable representations of data and metrics. This course helps a Data Visualization Consultant by teaching Tableau, a popular data visualization software package. Learning how to use Tableau and the concepts of data visualization helps a Data Visualization Consultant to best serve their clients.
Data Analyst
Data Analysts provide many of the same services as Data Visualization Consultants, but their primary focus is on analysis. Data Analysts may work for companies in all industries, providing crucial insights based on data.
Business Intelligence Analyst
Business Intelligence Analysts collect and interpret data to help businesses make decisions. Courses that emphasize data visualization can help Business Intelligence Analysts to develop interactive data visualizations that support their analyses.
Data Scientist
Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data. They use this data to help businesses make better decisions. This course can help Data Scientists who wish to use Tableau for their data visualization needs.
Market Research Analyst
Market Research Analysts play a key role in shaping the direction of products and services by helping companies understand what customers want. This course can be valuable to Market Research Analysts who are responsible for visualizing key consumer insights and trends.
Financial Analyst
Financial Analysts help companies make investment decisions and manage their finances. They use data visualization to present complex financial information in a way that is easy to understand.
Marketing Manager
Marketing Managers oversee the development and execution of marketing campaigns. They use data visualization to track the success of their campaigns and to make informed decisions about future marketing efforts.
Product Manager
Product Managers are responsible for the development and launch of new products. They use data visualization to track the progress of their products and to make decisions about future product development.
Software Engineer
Software Engineers design and develop software applications. They may use data visualization to help them understand the requirements of a software application and to track the progress of its development.
Web Developer
Web Developers design and develop websites. They may use data visualization to help them understand the needs of their users and to track the performance of their websites.
Graphic designer
Graphic Designers create visual concepts for a variety of purposes. They may use data visualization to help them develop designs that are both visually appealing and effective at communicating information.
UX Designer
UX Designers are responsible for the user experience of websites and applications. They may use data visualization to help them understand the needs of their users and to design interfaces that are easy to use.
Data Entry Clerk
Data Entry Clerks input data into computer systems. They may use data visualization to help them understand the data they are entering and to identify errors.
Customer Service Representative
Customer Service Representatives help customers with their questions and problems. They may use data visualization to help them understand the needs of their customers and to track the progress of their cases.
Office Administrator
Office Administrators provide administrative support to businesses. They may use data visualization to help them track the progress of their work and to identify areas for improvement.

Reading list

We've selected ten 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 and Representation.
This classic book on data visualization provides a wealth of insights into the principles of effective visual communication. It must-read for anyone who wants to learn more about the art and science of data visualization.
Provides a comprehensive introduction to R, a popular programming language for data science. It covers a wide range of topics, from data manipulation to statistical modeling.
Provides a practical guide to data analysis using Python. It covers a wide range of topics, from data manipulation to machine learning.
Provides a comprehensive introduction to deep learning. It covers a wide range of topics, from neural networks to deep learning applications.
Provides a comprehensive introduction to reinforcement learning. It covers a wide range of topics, from the basics of reinforcement learning to advanced topics such as deep reinforcement learning.
Provides a comprehensive introduction to generative adversarial networks (GANs). It covers a wide range of topics, from the basics of GANs to advanced topics such as GAN applications.
Provides a comprehensive introduction to natural language processing (NLP). It covers a wide range of topics, from the basics of NLP to advanced topics such as NLP applications.
Provides a comprehensive introduction to computer vision. It covers a wide range of topics, from the basics of computer vision to advanced topics such as computer vision applications.

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