Case study
Python Data Preparation Toolkit
A learning-forward data engineering project for cleaning, validating, and preparing tabular data for analytics workflows.
Challenge
Raw files often need consistent structure, validation, and repeatable transformations before they can be used in reports.
Solution
Built reusable Python and Pandas patterns for loading files, checking quality, standardizing fields, and preparing reporting-ready outputs.
Impact
Creates a practical bridge from current analytics work toward stronger data engineering workflows with Python, SQL, and PySpark.