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Data Visualization


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.

In-Class Activity One:
King County Cumulative Data

2.1: Working with web-based visualization tools and data - OECD

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.

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