Challenge 28: Can You Trust Your Office Equipment Data?
Level: Hard
Description: Your company is planning to upgrade its office setup with new chairs, desks, monitors, and other essentials. To help with the decision, someone scraped product details and reviews, but before trusting this data you have been asked to assess its quality. Your task is to evaluate two datasets (product details and product reviews) and create a data quality profile for each, focusing on three key factors: completeness, uniqueness, and conformity. Identify missing, duplicate, or inconsistent information to determine how reliable the data truly is. You can optionally explore further insights, but the main goal is to uncover whether this scraped data is good enough to guide the company’s purchasing decisions. Hint: Need help with data quality assessment? Check out Lesson 3 of our free self-paced [L4-DA] Data Analytics and Visualization: Specialization for guidance on measuring and visualizing data quality.
Beginner-friendly objective(s): 1. Load and preprocess the product data from Excel files. 2. Perform basic data exploration to understand the structure and key attributes of the dataset.
Intermediate-friendly objective(s): 1. Calculate key metrics like completeness, uniqueness, and conformity to assess data quality.
Advanced objective(s): 1. Create a comprehensive quality profile for the datasets.
Author: Armin Ghassemi Rudd
Dataset: Office product data on KNIME Community Hub
Remember to upload your solution with tag JKISeason4-28 to your public space on KNIME Community Hub. To increase the visibility of your solution, also post it to this challenge thread on KNIME Forum.