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Tableau_Dashboard (1)

Overview

In this project, I explored commuting behaviour and transport usage patterns across Australia, focusing on how far people travel to work, how public transport usage has changed over time, and how transport demand differs between capital cities and regional areas.

I combined national and state-level datasets to produce clear, comparable insights for urban planners, policymakers, and the general public. To improve analytical clarity, I intentionally avoided map-based visualisations and instead focused on trend- and comparison-driven charts that highlight patterns without geographic distortion.

Visualisation link: Australian Commute Patterns

Approach

I began by defining the key questions around commuting distance, transport usage trends, and regional demand. I sourced and combined multiple datasets from the Australian Bureau of Statistics (ABS) and Data Victoria, ensuring alignment across regions and time periods to support meaningful comparison.

Data Preparation

The datasets were cleaned and prepared prior to visualisation by filtering unnecessary fields, standardising categories, and selecting metrics that best represent typical behaviour. Median commuting distance was used instead of mean to reduce the influence of extreme outliers and improve interpretability.

Visual Design

Each visualisation was designed to prioritise trend detection, comparability, and accessibility. I selected chart types that clearly communicate changes over time and differences between regions. Consistent colour palettes, layouts, and scales were applied to reduce cognitive load and improve readability.

Visualisations Included

  • Median commuting distance by Greater Capital City Statistical Area
    Highlights longer commute distances in regions such as the ACT, Greater Melbourne, and Greater Brisbane.

  • Yearly public transport usage by mode (2011–2021)
    Compares changes across train, bus, tram, taxi, and ferry usage.

  • Monthly public transport usage by mode
    Reveals seasonal demand patterns across metropolitan and regional services.

  • Total annual road traffic usage in Victoria
    Shows the concentration of traffic volume in metropolitan regions compared to other areas.

Dashboard Development

All visualisations were combined into a single interactive Tableau dashboard. The layout was designed to guide users logically through the analysis, with interactive filters allowing exploration by year, region, and transport mode.

Key Insights

  • Capital city residents generally experience longer median commute distances than those in regional areas
  • Rail-based public transport modes, particularly trains and trams, show strong long-term growth
  • Transport demand exhibits clear seasonal patterns across most public transport modes
  • Road traffic usage in Victoria is heavily concentrated in metropolitan regions, indicating ongoing infrastructure pressure

Limitations & Future Work

This analysis is limited by the use of aggregated data, which does not capture full commute distributions, travel time, or route-level detail. Road traffic analysis is restricted to Victoria, and post-pandemic changes such as remote and hybrid work are not reflected.

Future improvements could include:

  • Incorporating travel time and congestion metrics
  • Analysing post-2021 transport trends
  • Adding sustainability and emissions indicators
  • Integrating real-time or sensor-based transport data

Tools & Technologies

  • Tableau for interactive dashboard development
  • Public datasets from the Australian Bureau of Statistics and Data Victoria
  • Data cleaning and preprocessing performed prior to visualisation

Intended Audience

  • Government and transport policymakers
  • Urban and infrastructure planners
  • Data analytics and visualisation professionals
  • Members of the public interested in Australian transport trends

Author

James Huynh
Dashboard created: 01/09/2024

About

exploring commute patterns across Australia using Tableau, providing insights into travel behavior, transport usage, and peak trends. Helps inform planning and operational decisions.

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