Analyze sales CSV files stored in Amazon S3 with AWS Glue and Athena. Four guided labs build the file-to-catalog-to-query workflow, followed by an independent challenge about missing monthly results.
What You Will Learn
- Upload sales records and describe their columns, CSV format and location in the Glue Data Catalog.
- Use SELECT, WHERE and GROUP BY to retrieve actual orders and calculate revenue in integer cents.
- Connect monthly file locations to registered partitions and query new records without changing an earlier month.
- Download the actual query result CSV, correct an input value and calculate a new summary.
- Diagnose an omitted month while preserving both source files and unrelated data.
Prerequisites and Environment
Complete AWS Foundations for Beginners, basic S3 object operations and IAM identity basics first. Introductory SQL is explained within this course. Study the four guided labs before the challenge.
Each unit starts independently in a browser-based Linux environment with Terminal, AWS View, prepared synthetic files and configured AWS credentials. No personal AWS account or resources from an earlier VM are required.
Frequently Asked Questions
Does the catalog store a copy of the CSV data?
Glue stores schema and location metadata; S3 retains the records. Defining an external table does not copy or transform them.
Is uploading a new monthly file enough?
This partitioned table also needs the correct catalog mapping. File arrival and catalog discoverability are separate.
Does a saved query result refresh when input changes?
No. Submit a new execution to compute an updated result, and keep the earlier output for comparison. The exercises verify actual records and results, without measuring production scan charges or performance.
