Visual Analytics with Tableau
This third course of the specialization explores the capabilities of Tableau in the areas of charting, dates, table calculations and mapping. Students will gain a deeper understanding of the visual analytics tools Tableau has to offer. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course provides an introduction to the Tableau software and its use in visual analytics. Students will learn how to create interactive visualizations, analyze data, and create dashboards.
This course provides an introduction to the Tableau software and its use in visual analytics. Students will learn how to create interactive visualizations, analyze data, and create dashboards. Through hands-on activities, students will gain an understanding of the Tableau interface, how to connect to data sources, and how to create visualizations. They will also learn how to use Tableau to analyze data and create interactive dashboards. By the end of the course, students will have the skills to create visualizations and dashboards to help them better understand their data.
[Applications]
This course provides an introduction to visual analytics with Tableau. It covers the fundamentals of Tableau, including data connections, data preparation, and creating visualizations.
After completing this course, students should be able to apply the concepts and techniques learned to create meaningful visualizations with Tableau. They should be able to use Tableau to explore and analyze data, create interactive dashboards, and share their insights with others. Additionally, they should be able to use Tableau to create data-driven stories and presentations.
[Career Paths]
Visual Analytics with Tableau is a course designed to teach learners how to use Tableau to create interactive visualizations and dashboards.
1. Business Intelligence Analyst: Business Intelligence Analysts use Tableau to analyze data and create visualizations to help organizations make better decisions. They are responsible for developing and maintaining data models, creating reports, and providing insights to stakeholders. As the demand for data-driven decision making increases, the need for Business Intelligence Analysts is expected to grow.
2. Data Scientist: Data Scientists use Tableau to analyze large datasets and uncover patterns and trends. They are responsible for developing algorithms and models to extract insights from data, and for creating visualizations to communicate their findings. As data becomes increasingly important in the business world, the demand for Data Scientists is expected to grow.
3. Data Visualization Designer: Data Visualization Designers use Tableau to create visually appealing and informative visualizations. They are responsible for designing and developing interactive dashboards and visualizations that help stakeholders understand data. As organizations become more data-driven, the need for Data Visualization Designers is expected to increase.
4. Tableau Developer: Tableau Developers use Tableau to create custom applications and dashboards. They are responsible for developing and maintaining Tableau applications, and for creating custom visualizations and dashboards. As organizations become more reliant on data, the need for Tableau Developers is expected to grow.
[Education Paths]
Visual Analytics with Tableau is a course designed to help learners develop the skills necessary to create interactive visualizations and dashboards with Tableau. The course covers topics such as data preparation, data visualization, and dashboard design.
1. Bachelor of Science in Data Science: Data Science is a rapidly growing field that combines mathematics, computer science, and statistics to analyze and interpret large datasets. A Bachelor of Science in Data Science will provide learners with the skills necessary to work with data, develop algorithms, and create visualizations. Additionally, learners will gain an understanding of the developing trends in data science, such as machine learning and artificial intelligence.
2. Master of Science in Business Analytics: Business Analytics is a field that focuses on the use of data to make decisions and improve business operations. A Master of Science in Business Analytics will provide learners with the skills necessary to analyze data, develop predictive models, and create visualizations. Additionally, learners will gain an understanding of the developing trends in business analytics, such as big data and cloud computing.
3. Master of Science in Data Visualization: Data Visualization is a field that focuses on the use of data to create visual representations of information. A Master of Science in Data Visualization will provide learners with the skills necessary to create interactive visualizations and dashboards with Tableau. Additionally, learners will gain an understanding of the developing trends in data visualization, such as augmented reality and virtual reality.
4. Doctor of Philosophy in Data Science: Data Science is a rapidly growing field that combines mathematics, computer science, and statistics to analyze and interpret large datasets. A Doctor of Philosophy in Data Science will provide learners with the skills necessary to work with data, develop algorithms, and create visualizations. Additionally, learners will gain an understanding of the developing trends in data science, such as machine learning and artificial intelligence.
Pros & Cons
1. Efficient learning of Tableau concepts.
2. Hands-on aspect for practical experience.
3. Covers dual layer maps, dual axis, and calculated fields.
1. Superficial and lacks advanced content.
2. Course title doesn't match the actual content.
3. Short duration with minimal quantity of material.
4. Lack of clear practice tasks or exercises.
5. Technical quality and editing issues.
6. Repetitive lectures with unnecessary recaps.
7. Incomplete instructions for assignments.
8. Inadequate teaching of Tableau mechanics.
9. Unclear directions and inconsistent data files.
10. Balancing theory over practical Tableau instruction.
Course Provider
Provider Coursera's Stats at AZClass
Visual Analytics with Tableau explores Tableau's capabilities in the areas of graphing, dates, tabular calculations, and graphing. Learners can take an in-depth exploration of Tableau's charting, date, tabular calculation, and drawing tools. They can create custom and fast tabular calculations, parameters and different types of charts such as scatter charts, Gantt charts, histograms and bullet charts. They can also learn about discrete and continuous dates, how to connect to multiple data sources, and how to create custom maps. Additionally, learners can learn how to use Tableau to analyze data and create visualizations to help them make informed decisions.
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