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In the previous chapter, you built an automated ETL pipeline using Jenkins and Python. The job pulled raw transaction data from cloud storage, cleaned and aggregated it, and saved daily KPIs into new output folders on both AWS S3 and Google Cloud Storage.

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Demo: Streamlit

  • 章节

  • 发表日期：

    2025年

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  • Lucas H. Benevides e Braga

摘要

In the previous chapter, you built an automated ETL pipeline using Jenkins and Python. The job pulled raw transaction data from cloud storage, cleaned and aggregated it, and saved daily KPIs into new output folders on both AWS S3 and Google Cloud Storage.