Building a PySpark and AWS Glue ETL Pipeline for Search Keyword Revenue Analysis

Naveen Ayalla Posted on May 31 Building a PySpark and AWS Glue ETL Pipeline for Search Keyword Revenue Analysis # aws # dataengineering # showdev # terraform I published a public data engineering project that demonstrates a cloud-based ETL pipeline for analyzing web analytics search keyword revenue. The project uses PySpark, AWS Glue, Amazon S3, and Terraform to process hit-level web analytics data, extract external search engine domains and keywords, parse revenue, and generate a sorted reporting output. Key concepts covered: Batch ETL pipeline design PySpark transformations AWS Glue job configuration S3 input and output workflow Revenue aggregation logic Terraform infrastructure examples This is a generic open-source portfolio project and does not include proprietary or company-provided data. GitHub: https://github.com/naveenayalla1-CS50/search-keyword-performance-revenue Feedback from data engineers and cloud data practitioners is welcome. Top comments (0) Subscribe Personal Trusted User Create template Templates let you quickly answer FAQs or store snippets for re-use. Submit Preview Dismiss Code of Conduct • Report abuse Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink . Hide child comments as well Confirm For further actions, you may consider blocking this person and/or reporting abuse