In this first course of this specialization, you will discover what data visualization is, and how we can use it to better see and understand data. Using Tableau, we’ll examine the fundamental concepts of data visualization and explore the Tableau interface, identifying and applying the various tools Tableau has to offer. By the end of the course you will be able to prepare and import data into Tableau and explain the relationship between data analytics and data visualization. This course is designed for the learner who has never used Tableau before, or who may need a refresher or want to explore Tableau in more depth. No prior technical or analytical background is required. The course will guide you through the steps necessary to create your first visualization from the beginning based on data context, setting the stage for you to advance to the next course in the Specialization.
제공자:
Data Visualization with Tableau 특화 과정캘리포니아 대학교 데이비스 캠퍼스이 강좌에 대하여
Must be comfortable working with data and datasets.
배울 내용
Install Tableau Public Software and create a visualization
Examine and navigate the Tableau Public workspace
Practice and connect to different data sources
Examine ways to define your project
귀하가 습득할 기술
- Tableau Software
- Data Virtualization
- Data Visualization (DataViz)
- Visualization (Computer Graphics)
Must be comfortable working with data and datasets.
제공자:
캘리포니아 대학교 데이비스 캠퍼스
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
강의 계획표 - 이 강좌에서 배울 내용
Data Visualization and Its Importance
In this module, you will be able to define what data visualization is and discuss why it’s so important. You will listen to an interview with Dr. Ben Shneiderman, a modern pioneer of data visualization. You will be able to define interactive visualization and install Tableau Public so you can start to get acquainted with it for the next module. You will be able to make a simple viz so you can clearly see what skills are used in the process.
Getting to Know Tableau for Data Visualization
In this module, you will be able to identify and describe the various parts that make up the welcome screen, worksheet screen, and dashboard screen.
Let's Make a Viz!
In this module, you’ll be able to identify potential questions to answer with a given dataset. You will be able to make three different charts: a line chart, a tree map, and a bar chart. You will be able to create a dashboard with those charts, and be able to add some simple dashboard interactions.
Tableau Community Projects and Visualization Best Practices
In this module, you will be able to discuss where to get help. You will also be able to discuss where to go for inspiration and how to get involved in the Tableau community. You will be able to discuss and apply 5 data visualization best practice and participate in a #MakeoverMonday project.
검토
- 5 stars64.76%
- 4 stars25.55%
- 3 stars6.04%
- 2 stars1.75%
- 1 star1.87%
FUNDAMENTALS OF VISUALIZATION WITH TABLEAU의 최상위 리뷰
Pretty good introduction specially for those with no experience with Tableau like me. Truly covered the real basics. Looking forward to learn much complex visualizations on the succeeding courses.
Best course to start with when it comes to Tableau. The modules have been properly arranged and easy to go through. All the basics have been covered about the fundamentals of Tableau.
very simple and conveniently it was explained. Its explains the complete visualization part. If some more lessons are present in this Tableu course then you should select another course
The course has indeed added to my skill set and has helped me build a foundation for further career opportunities in the field of Data Visualization. Highly recommended for beginners.
Data Visualization with Tableau 특화 과정 정보
In 2020 the world will generate 50 times the amount of data as in 2011. And 75 times the number of information sources (IDC, 2011). Being able to use this data provides huge opportunities and to turn these opportunities into reality, people need to use data to solve problems.
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