Long Tien Bui

Tableu & R Shiny Dashboard

Data Visualisation Developer · FIT5147, Monash University | Aug 2023 – Oct 2023

Data Science Remuneration R Shiny dashboard

Overview

An interactive narrative visualisation built in R Shiny that unpacks the multifaceted landscape of Data Science compensation in 2023. The dashboard was designed to challenge common misconceptions about the profession and give aspiring, current, and educational stakeholders a coherent view of where the field is heading.

Read proposal

What was the challenge?

Data Science is one of the most in-demand careers, yet public understanding of salaries, specialisations, geographical distribution, and remote-work norms is fragmented and often misleading. The challenge was to turn a large remuneration dataset into a clear, engaging story that audiences with different goals could all get value from.

What I did

  • Explored and cleaned a 2023 Data Science salary dataset, identifying key dimensions — job title, experience level, country, remote ratio, and salary.
  • Designed a narrative-driven Shiny dashboard with coordinated views: donut charts for job-title distribution, tree maps for remote-work ratios, choropleth maps for global distribution, and a word cloud for required skills and qualifications.
  • Applied visualisation design principles — visual hierarchy, colour consistency, and interactive filters — so users could explore the data at their own pace.
  • Framed the dashboard around four key messages: job titles & specialisations, geographical spread, remote-work prevalence, and salary disparities.
  • Tailored the experience to three audiences: aspiring data scientists choosing a major, working data scientists benchmarking their market, and educational institutions shaping curriculum.
Final Report

Tools & skills

R · Shiny · ggplot2 · Data Wrangling · Narrative Visualisation · Dashboard Design · Data Storytelling

Outcome

The final dashboard translated a dense salary dataset into a clear, interactive story that helps users make informed decisions — from students choosing a specialisation, to professionals planning their next move, to institutions aligning their programs with real industry demand.

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