PostgreSQL & Tableau Project
UK Job Market Analysis
Analysed UK data and analytics job postings using PostgreSQL and Tableau to identify the most in-demand skills, hiring locations and job titles.
Why I Built This
While applying for data analyst roles, I wanted to understand what UK employers were seeking. I used a LinkedIn jobs dataset to analyse the market for skills, locations and job titles that appeared most often.
This analysis has helped me prioritise which skills to develop and which locations to target when applying for data analyst roles.
Dataset
The original dataset contained over 1.3 million LinkedIn job postings. I filtered this down to UK data and analytics roles using SQL views in PostgreSQL.
The original dataset was sourced from Kaggle, containing over 1.3 million LinkedIn job postings with extracted skills.
SQL Workflow
Import CSV Files
I imported the 3 CSV files into PostgreSQL, examined the headings and structure of the data.
Create Relational Database
Structured the dataset using job links as primary keys and foreign keys across related tables.
Create SQL Views
Created SQLviews to narrow down the data first to UK jobs and then subsequently to data roles.
Analyse Skills, Locations & Titles
Used joins, string splitting, grouping and percentages to answer a few of my research questions.
Import into Tableau
Exported final SQL outputs into Tableau Public to build a focused dashboard.
Tableau Dashboard
View on TableauThe dashboard highlights the most requested skills, top hiring locations and most common job titles across the analysed UK data roles.
Dashboard built from PostgreSQL outputs. Click the image to explore the interactive version on Tableau Public.
Key Insights
Most In-Demand Skill
SQL was the most requested skill, appearing in 344 UK job postings.
Top Hiring Location
London had the highest demand for data and analytics roles.
Popular BI Tool
Power BI appeared more frequently than Tableau across the analysed jobs.
What I Learned
This project improved my understanding of PostgreSQL, SQL views, joins and data validation.
The project highlighted issues commonly found in real-world datasets. Inconsistent job titles, recruitment agencies and incomplete salary data made it more difficult to draw meaningful conclusions.
Future Improvements
To build on this project, I would standardise similar job titles and merge duplicate skill names to improve the accuracy of the analysis. I would also include salary, remote and hybrid working trends using a richer dataset.
Future versions of this project could compare trends across different countries and over time, providing a broader view of the data and analytics job market.
Overall, this project provided valuable insights into the UK job market and helped validate that I'm learning the right skills to get hired for data analyst jobs.