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Data EngineeringCase Study·88% Match

NYC Taxi Data Engineering & Power BI Visualization

Serverless AWS data engineering pipeline for NYC taxi analytics. AWS Lambda processes raw trip data; EventBridge triggers scheduled runs; AWS Glue Studio performs ETL with a visual data catalog; Athena queries the S3 data lake. Power BI and AWS QuickSight deliver stakeholder dashboards. Topics: python, aws-lambda, powerbi, aws-athena, aws-glue, event-bridge.

AWS GlueAWS EventBridgeAWS S3AWS AthenaAWS QuickSightPower BI
ProductionServerlessAWS LambdaEventBridgeSchedulerGlue + AthenaETL + QueryPower BIDashboards
Serverless
AWS Lambda
EventBridge
Scheduler
Glue + Athena
ETL + Query
Power BI
Dashboards
🔴 The Problem
▸

NYC Taxi data arrived as raw CSV dumps — no scalable ETL or ad-hoc query layer

▸

Dashboard refreshes required manual data exports

✅ The Solution
▸

AWS Lambda + EventBridge trigger serverless ETL on schedule; Glue Studio catalogs and transforms; Athena queries the S3 data lake directly

▸

Power BI and QuickSight consume Athena results for stakeholder dashboards

📈 Impact & Results
▸

Zero-server ETL: Lambda + Glue handle millions of trip records per run

▸

Athena queries run in seconds against Parquet-partitioned S3

▸

Power BI dashboard refresh automated via scheduled Glue crawlers

Full Tech Stack
AWS GlueAWS EventBridgeAWS S3AWS AthenaAWS QuickSightPower BI

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