Data Visualization
@CMU
Collection of the selected Data Visualization projects undertaken during my time at Carnegie Mellon!
What did I wish to learn from this course at Carnegie Mellon?
In my Data Visualization course at CMU, I was eager to expand my skills and knowledge in this field beyond my existing foundation.
I wanted to learn how to effectively transform complex datasets into compelling visual narratives that communicate insights clearly and persuasively. I aimed to master various data visualization tools and techniques, understand the principles of visual design, and explore the nuances of storytelling through data. I hoped to gain proficiency in selecting the right visualization methods for different types of data and audiences while honing my ability to assess and improve existing visualizations critically.
The first pass:
King County Cumulative Data
2.2: General Government debt-to-GDP Ratio
The general government debt-to-GDP ratio measures the gross debt of the general government as a percentage of GDP. It is a key indicator for the sustainability of government finance. Debt is calculated as the sum of the following liability categories (as applicable): currency and deposits; debt securities, loans; insurance, pensions and standardized guarantee schemes, and other accounts payable. Changes in government debt over time primarily reflect the impact of past government deficits.
3&4: Critique by Design
A series of five steps - finding a data visualization, critiquing the visualization using Stephen Few's Data Visualization Effectiveness profile, wireframing a solution, testing the solution, and finally building the solution. Using Pitchbook's Monitor Report for 2023 Q2, I accomplished the above the steps to reach a redesigned data visualization using Flourish.
The Final DataViz:
Life and Choices - Through the Lens of Your Phone Screen
The final data visualization comprises a series of three parts, encompassing different phases in the process:
Part One is the kick-starter for the final data-viz project in the Storytelling with Data, Fall 2023 class at CMU Heinz. The section will walk you through the broad outline for the project, the story that I'll be trying to convey using various data visualizations and graphics, initial sketches, possible types of visualizations, the data sources, and the medium I'll be using to showcase the final project. This is a WIP, an is subject to changes through the course of developing the final project.
Part Two will guide you through the process of constructing and refining the actual narrative that will take the reader on an enthralling journey. In this section, I explored various techniques for understanding what my readers are seeking. I worked on developing wireframes, and storyboards, and conducting user research to refine my storytelling concept. The artifacts for this stage were created using Figma, Shorthand, Tableau, and Flourish.
Finally, Part Three will showcase the entire story including the data visualizations, text content, imagery, and graphics. A bunch of tools and platforms were utilized to give the story its final form including - Shorthand, Tableau, Flourish, Figma, Pexels, and last but not least the big datasets coming from various reports and other sources.