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data-engineering-project

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Leveraging AWS Cloud Services, an ETL pipeline transforms YouTube video statistics data. Data is downloaded from Kaggle, uploaded to an S3 bucket, and cataloged using AWS Glue for querying with Athena. AWS Lambda and Glue converts to Parquet format and stores it in a cleansed S3 bucket. AWS QuickSight then visualizes the materialised data.

  • Updated May 30, 2024
  • Python

Build a data pipeline on Google Cloud using an event-driven architecture, leveraging GCS, Cloud Run functions, and BigQuery. Explore both VM and Composer options for Airflow management, and utilize Logging & Monitoring for pipeline health. Discover how SQL-based BigQuery ML can be used for initial ML implementation in specific scenarios.

  • Updated Aug 25, 2024
  • Python

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