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Data Science — 2025, Undergraduate
This study developed a data warehousing and OLAP reporting dashboard that consolidates multi-source data into dimensional models and supports slice, dice, and drill-down analysis. Users build reports from cubes and export summaries. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Django, Pandas, and PostgreSQL. The findings showed that the dashboard reduced report turnaround and improved analytical flexibility, while achieving a high System Usability Scale score. The study recommends adoption by institutional planning units.
For reference and learning only. Do not submit this work as your own.

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