Automatización del procesamiento de aprendices y visualización analítica en Looker Studio

Abstract

The Campus Virtual’s academic data management suffered delays and errors due to manual consolidation and the lack of an integrated analytics panel. Objective: optimize data processing to provide timely, reliable information for academic management. Content: two complementary applications were developed: (1) the “Procesador de Aprendices” web app (HTML5/JavaScript with SheetJS and FileSaver.js), which compares “before” and “now” report snapshots, normalizes columns, and generates a single-source Master Workbook; and (2) an Analytics Dashboard in Looker Studio, powered by Google Sheets and Google Analytics 4 (GA4), offering dynamic visualizations of enrollment, retention, and platform engagement across undergraduate, graduate, and continuing education. Methodology: in-browser ETL (extract–transform–load), validation rules with unique keys, Google Workspace integration, and pilot/operational testing across multiple cohorts and schools. Results: consolidation time decreased from ~3 hours to ~15 minutes per cohort; duplicate records and transcription errors were eliminated; early alerts on data inconsistencies (e.g., no enrollment or no payment) improved traceability. Discussion: a client-side architecture combined with cloud analytics provides scalability, security, and low cost, but requires periodic remapping when Moodle’s HTML or user permissions change, as well as ongoing user training. Conclusions: the solution enhances data quality, timeliness, and governance, enables evidence-based decision-making, and lays the groundwork for next steps such as automated ingestion, more resilient templates, and a strengthened metric catalog.