Fernanda Pauli developed and ingested two new environmental time-series datasets for the data-hydenv/data repository, focusing on enabling analytics and machine learning workflows. She engineered CSV files at both 10-minute and hourly intervals, incorporating fields such as ID, timestamp, temperature, lux, and an explicit origin indicator to ensure data provenance. Using her skills in data collection and data engineering, Fernanda structured the datasets to support historical analysis and immediate model development, reducing data preparation time. Her work emphasized reproducibility and auditability, establishing disciplined repository practices and laying the groundwork for scalable, well-governed time-series data assets within the organization.