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07 · Data engineeringPipeline and Power BI

Why the plane was late.

A data pipeline and Power BI dashboard that model US flight delays as connected flights and airports, the way Palantir Foundry teams structure data.

  • Python
  • PySpark
  • Power BI
“Why did Chicago run later than Atlanta?”Press play · 6 scenes · scroll to watch it unfold ↓
63KFlights analysed

01

Atlanta or O'Hare?

63,029 flights in June 2018. Which airport makes you late?

02

Flights as objects, not rows.

Each flight links to its airport. Every question becomes a filter.

03

O'Hare: 21.1 minutes late.

Atlanta: 13.6. Average arrival delay.

04

Almost one in three.

32% of O'Hare flights were delayed, 24% at Atlanta.

05

Worst at 11 pm.

Late evening departures had the biggest delays.

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