20/09/2023
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Data Visualization and Communication with Tableau by Duke University (Coursera)

Online Courses by Duke University

This Course on Data Visualization with Tableau is offered by Duke University as part of its Excel to MySQL: Analytic Techniques for Business Specialization. The goal of this course is to prepare learners to become an expert at communicating business-relevant practical implications of their data analyses. It teaches them to streamline their analysis by asking the right questions and use Tableau to convey critical findings. Students learn Storyboarding skills and how to visualize the results of data analysis or machine learning models in Tableau, so that it can be better understood by both technical and non-technical stakeholders.

Tableau is the most popular visualization tool in the market. This course explores various Tableau features that can be used to create effective visualizations that convey conclusions clearly and directly. Spread over 5 weeks, the course is approximated to require around 25 hours to complete. It includes a peer-reviewed final project that assesses a student’s learning of the subject. The topics covered in the course are:

  • Creating graphs that are used in business analysis
  • Transforming data in Tableau
  • Designing business dashboards with Tableau
  • Creating and delivering compelling business presentations
  • How to craft the right questions to ensure your analysis projects succeed
  • Writing calculations and equations in Tableau
  • Adapting visualizations to make them maximally communicative

Key Highlights

  • Understand how to structure your data analysis projects to ensure that they lead to actionable advice that can be presented to stakeholders
  • Learn to communicate results and implications of your quantitative analyses visually in a way that non-technical people can understand
  • Publish online business dashboards with Tableau
  • Learn a set of tools and concepts that you can use to optimize your visualizations and your presentation style
  • Series of practice exercises that involves doing analyses on a sample data set

Duration : Approx. 25 hours

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