This project was completed as part of my Data Analyst Associate Certification practical exam with DataCamp, where I was required to demonstrate entry-level competency in data management, exploratory analysis, statistical thinking, and communication. The certification process included rigorous timed and adaptive assessments, followed by a practical business case in which I cleaned and validated raw data, calculated key metrics, and generated insights to support real-world decision-making.
FoodYum, a US-based grocery store chain, wanted to ensure product pricing across categories remains competitive and accessible to a broad customer base amid rising food costs.
The objective of this project was to clean product data and analyze pricing distribution across product categories to support stocking and pricing decisions.
The analysis was conducted on the products table containing 1,700 product records from the latest full year of the loyalty program.
The dataset includes:
1. Data Quality Check