Computer · Software Development
Real-Time Data Pipeline (Kafka → Spark → Dashboard)
Intermediate 6 weeks 40-60 hours
Build end-to-end data pipeline: collect data → message broker → stream processing → visualization. Real-time analytics dashboard with multiple data sources.
Major
Computer
Focus area
Software Development
Total hours
40-60 hours
What you'll need
- Software only - Docker, Kafka, Spark (free), Grafana, Python
Steps
- Pick 2 or more public data sources, like weather or transit feeds.
- Set up Kafka in Docker and write producers that stream the data.
- Process the streams in Spark.
- Store the results and connect them to Grafana.
- Build a real-time dashboard with multiple charts.
- Document the architecture diagram and dashboard for your portfolio.
What to photograph for your portfolio
- Real-time dashboard
- data flow architecture diagram
- throughput metrics
- latency analysis
- system monitoring
Resume bullet starters
Copy one, then swap in your own numbers.
Designed and built a real-time data pipeline using Apache Kafka, Spark streaming, data engineering
Applied Docker and data visualization to implement, test, and validate the system end-to-end
Quantified performance with [insert your result, such as accuracy, error reduction, response time, or load capacity] after iterative tuning
Skills you'll show off
Apache KafkaSpark streamingdata engineeringDockerdata visualizationPython/Scala