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Tableau Workshop

Tableau for data visualization and analysis

Table of Contents
  1. About The Workshop
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Authors
  8. Acknowledgements

About The Workshop

This workshop introduces participants to the fundamentals of Tableau, a powerful tool for data visualization and analysis. Participants will learn how to create interactive and insightful visualizations using Tableau.

Workshop Materials Link

Getting Started

This workshop utilizes Tableau, an industry-leading data visualization tool that helps you understand your data and present it beautifully.

Dependencies

  • Tableau Desktop (Trial or Full Version)

Installation

  1. Download the workshop materials from the GitHub repository.
    • git clone https://github.com/matheusmaldaner/WorkshopArchive/Tableau.git
  2. Navigate to the Tableau Public Download Page and download the appropriate version for your operating system. (You can download Tableau Pro as well if you sign up with UF)

Usage

  1. Launch Tableau Desktop.
  2. Open the Provided Dataset or Connect Tableau to Your Own Data Source:
    • If using the provided dataset train.csv, follow these steps:
      • Open Tableau Desktop.
      • Click on "Connect to Data" or "To a File" depending on your Tableau version.
      • Navigate to the location where your train.csv file is stored.
      • Select the file and click "Open" or "Connect" to load it into Tableau.
  3. Open the workshop-instructions.md file provided in this repository for detailed instructions on using Tableau with the Titanic dataset.
  4. Create interactive visualizations using Tableau's intuitive interface.
  5. Explore various visualization types, filters, and calculations to gain insights from your data.

Roadmap

  1. Introduction to Tableau and its features.
  2. Basics of creating visualizations (Bar charts, Line charts, Pie charts, etc.).
  3. Advanced visualization techniques (Maps, Dashboards, Storytelling).
  4. Hands-on exercises and real-world use cases.
  5. Tips and tricks for effective data visualization.

Authors

Kyle Weiner - Github

Acknowledgements

  • Data Science and Informatics for hosting the workshop.

Thank you