Track real demand for modern tech skills
TechTrends analyzes live hiring data so students and developers can make clearer, evidence-based learning decisions.
Explore the DataProject mission
TechTrends started from one practical question: Which skills are genuinely gaining hiring momentum? Instead of relying on anecdotal advice, this project uses measurable trends from current job postings.
The platform collects data from Adzuna and LinkedIn, tracks 27 core skills across languages, frameworks, cloud tooling, and databases, then turns those signals into rankings, trends, and forward-looking projections.
The goal is simple: make career planning less guesswork and more data-informed for learners, early-career developers, and career switchers.
What you can explore
Each page surfaces a different angle on the same live dataset.
Dashboard
Quick KPIs, category distribution, and skill-level summaries for a fast market snapshot.
Trends
Role-level trend mapping to show which skill clusters are rising, stable, or declining.
Ranking
Compare skills by demand, salary potential, and growth to identify high-priority topics.
Forecasting
Model-based projections estimate near-term demand shifts using historical trajectories.
Filters
Narrow results by category, growth profile, salary range, and posting volume.
Insights
Narrative summaries highlight leaders, momentum changes, and salary outliers.
About Me
Justin Xie
BA Student at University of Florida
I am currently pursuing a Bachelor of Arts at the University of Florida. I built TechTrends to strengthen my data engineering and frontend development skills, from automated collection pipelines to interactive analysis interfaces.
How the data works
Live scraping + a MySQL backend keeps the numbers fresh.
Scraping
A Python scraper runs hourly via cron, hitting the Adzuna API for job counts and salaries, and scraping LinkedIn for live posting counts per skill.
Storage
Results are stored in a MySQL database with separate tables for Adzuna data, LinkedIn data, historical year-by-year snapshots, and sample job listings.
API
PHP endpoints expose the data as JSON. The frontend fetches fresh responses at runtime with a lightweight, framework-free architecture.
Visualisation
Chart.js powers the charts. Everything else — cards, tables, filters, forecasts — is rendered with plain DOM manipulation and CSS custom properties.