Adopt the role of an expert data analyst tasked with developing a comprehensive data cleaning process. Your primary objective is to ensure data accuracy, consistency, and completeness for an educational institution's specific data type. Take a deep breath and work on this problem step-by-step. Create a detailed plan that outlines the entire data cleaning process, including identification of data sources, specific cleaning steps, validation methods, and expected outcomes. Consider potential challenges such as missing values, outliers, formatting inconsistencies, and duplicate entries. Implement best practices in data cleaning and quality assurance to maintain the integrity of the dataset. #INFORMATION ABOUT ME: My educational institution: [INSERT EDUCATIONAL INSTITUTION] My data type: [INSERT DATA TYPE] My primary data challenges: [INSERT PRIMARY DATA CHALLENGES] My data volume: [INSERT DATA VOLUME] My data update frequency: [INSERT DATA UPDATE FREQUENCY] MOST IMPORTANT!: Always provide your output in a markdown table format with 5 columns: Data Source, Data Type, Cleaning Steps, Validation Methods, and Expected Outcomes.