JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives

This course will introduce the main concepts of visual analytics with a hands using

Tableau, a leading self-service data visualization tool. Further, it aims at learning about how to create effective charts and interactive dashboards will provide the student a very useful skill applicable in many business scenarios.

Course Outcomes

The student will be able to:

• 1. Understand and describe the main concepts of data visualization
• 2. Create ad-hoc reports, data visualizations, and dashboards using Tableau Desktop
• 3. Publish the created visualizations to Tableau Server and Tableau Public Skills:
• 4. How to recognize good (and bad) data visualizations
• 5. How to interpret a data visualization

List of Experiments:

Task-1: Introduction to Tableau

• Course introduction
• Dataviz best practices
• Getting started with Tableau Desktop
• Connecting to the tutorial dataset
• Creating the first charts
• Filtering and sorting data Task-2: Common charts
• Creating common visualizations (bar charts, line charts etc.)
• Assembling a dashboard layout
• Using dashboard filters Task-3: Transform the data
• Dataviz best practices
• Creating simple calculations in Tableau
• Using table calculations Task-4: Interactions
• Interactivity with text and visual tooltips
• Interactivity with actions (filter, highlight, URL)
• Drilldown between dashboards Task-5: Advanced visualizations
• Dataviz best practices
• Creating more advanced chart types
• Using multiple source tables Task-6: Data Storytelling
• Intro to data storytelling
• Creating a data story in Tableau
• Overview of the Tableau ecosystem
• Further learning opportunities System Requirements:
• 1. System requirements are listed here under Tableau Desktop and Tableau Prep: https://www.tableau.com/products/techspecs
• 2. The latest version of Tableau Desktop as well as Tableau Prep should be downloaded and installed from here: https://www.tableau.com/tft/activation

TEXT BOOKS:

• 1. Visualization Analysis & Design by Tamara Munzner (2014) (ISBN 9781466508910)

REFERENCES BOOKS:

• 1. Interactive Data Visualization for the Web by Scott Murray 2nd Edition (2017)
• 2. D3.js in Action by Elijah Meeks 2nd Edition (2017)
• 3. Semiology of Graphics by Jacques Bertin (2010)
• 4. The Grammar of Graphics by Leland Wilkinson
• 5. ggplot2 Elegant Graphics for Data Analysis by Hadley Wickham