This project used Tableau to analyse regional economic shifts in the United Kingdom. The data set is named UK Industrial Employment Trends (EMSI) and was provided by JustIT.
Economic fluctuations between 2011 and 2014 significantly impacted UK regions, requiring a clear way to distinguish between broad economic trends and specific industrial shifts.
Create a comprehensive visualisation suite in Tableau that allows stakeholders to navigate between high-level regional overviews and granular sector-specific analysis.
Data Architecture: I utilised a dual-layer dataset structure consisting of 1-digit (Broad Industries) and 2-digit (Detailed Sub-industries) sheets to allow for hierarchical exploration.
Visual Strategy: I developed two distinct dashboards using geographic maps for spatial distribution (highlighting the cities were changes were sharper), bar charts for ranking, and heat maps to visualise the intensity of sector shifts per specific cities.
Analytical Validation: I performed a cross-sheet validation using Swansea as a control. By tracing a +42.7% growth in the broad Arts & Entertainment sector down to specific sub-sectors, I ensured the accuracy of my calculated fields and data joins across the entire workbook.
The final product is a multi-dashboard setup that identifies a "two-speed" economy across the UK:
Regional Growth Divergence: The analysis highlighted significant localized booms, such as Aberdeen’s Administrative and Support sector, which grew by +32.2% (adding over 7,200 jobs).
Granular Insights: The "drill-down" functionality revealed that growth in one area often masked declines in others. For instance, in Swansea, the high growth in leisure was contrasted by a sharp -21.9% decline in Professional and Scientific services.
Public Sector Contraction: Traditional sectors faced widespread challenges, notably in Birmingham, where Public Administration and Defence saw a -5.3% decrease, representing a loss of 2,680 jobs.
Please click here to see the dashboards live: dashboard 1 dashboard 2 or find them embedded further below. The Tableau Workbook file is available in my GitHub repository here
To understand the UK economy, we often look at the "average" trend, but the data suggests that the most extreme data points—the outliers—provide the most critical lessons. In this project, I treated outliers as essential signals rather than anomalies.
1. Outliers as "Success Blueprints"
Outliers highlight regions that have unlocked unique growth engines. For example, while professional services grew moderately in most UK hubs, Nottingham-Derby saw a massive +47.9% surge in Professional, Scientific and Technical Activities. By studying the driving forces behind this specific success, other cities can learn how to replicate that momentum.
2. Outliers as "Early Warning Signs"
Sharp declines serve as localised shocks that warrant investigation. My analysis revealed:
Cardiff-Newport experienced a significant -27.0% drop in Professional, Scientific and Technical Activities.
Newcastle-Sunderland saw a -26.7% decline in Other Service Activities. Understanding the forces behind these specific extremes, such as regional budget shifts or industrial relocations, crucial for organisations looking to prevent these trends from spreading.
3. Distinguishing Speed vs. Magnitude
A key finding from the dashboard is that a high percentage change does not always equal a high volume of jobs.
Swansea’s Real Estate sector showed steady growth of +11.5%, which represents a gain of 277 jobs.
In contrast, London’s growth in the Professional sector (at a lower percentage) added over 100,000 jobs, demonstrating the massive scale of the capital.
The most extreme growth in the dataset was found in Newcastle-Sunderland, where Electricity, Gas, and Steam grew by +53.2%.
4. The Swansea Validation
Through my validation process, I confirmed that Swansea's Public Administration, showed indeed a stable growth of +0.9%. However, the city's real story was in Arts, Entertainment, and Recreation, which saw a boom of +42.7%, signaling a shift toward a leisure-driven regional economy.
And finally, the data suggests that during this period, jobs were not necessarily "lost" to the economy, they were redistributed. While Public Administration (-49,500 jobs) and Manufacturing (-28,000 jobs) faced contraction nationwide, these losses were more than offset by massive surges in Professional Services (+134,600 jobs) and Administrative Support (+120,000 jobs).
The analysis proves that the UK economy is "tilting" rather than shrinking. By identifying these extremes, we can better understand where the economy is moving and prepare for a future where traditional sectors are being replaced by high-growth service and technical industries.
Dashboards
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Data visualisation is more than just a collection of charts; it is a universal language that translates raw complexity into immediate insight. In an era of information overload, the ability to convey intricate stories about people, trends, and systems in a matter of seconds is a superpower. By leveraging pre-attentive attributes—like color, size, and orientation—we can bypass the heavy lifting of manual analysis. This allows stakeholders to grasp the "what" and the "why" of a dataset through intuition rather than labor-intensive reading, turning cold numbers into a compelling narrative that drives action. It saves them a lot of time too.
However, the bridge between data and understanding is built on intentional design. A truly effective visualisation is inclusive; it must be intuitive enough for a layperson to navigate while remaining robust enough for an expert to find deep value. My approach prioritizes clarity and cognitive ease, ensuring that every design choice—from white space to tooltips—serves to reduce "noise." When we design with the end-user in mind, we ensure that critical insights are accessible to everyone, regardless of their technical background.