Data cleaning is often a time-consuming and complex task that requires technical skills or expensive software, creating barriers for students, researchers, and professionals who need reliable datasets for analysis. This study developed RawtoReady, a web-based automated data cleaning system that provides one-click processing features such as handling missing values, removing duplicates, standardizing text and dates, validating emails, applying fuzzy standardization, and detecting anomalies through a guided four-step workflow of uploading data, selecting cleaning options, running the process, and downloading the cleaned output with a transparent summary. The system was evaluated using a user survey designed based on Edward de Bono’s Six Thinking Hats methodology, with responses collected from 56 participants to assess usability, effectiveness, and user satisfaction. Results showed that users found RawtoReady efficient, accessible, and easy to use, significantly reducing the time and effort required for manual data cleaning while improving confidence, organization, and control in data preparation. These findings indicate that RawtoReady is a practical and effective solution for democratizing data cleaning, supporting data-driven learning, research, and innovation in alignment with Sustainable Development Goals 4 (Quality Education) and 9 (Industry, Innovation, and Infrastructure).