Ricardo Urdaneta

Data analysis project covering everything from the automated extraction of historical meteorological records via API for Chile's 16 regional capitals to the development of an interactive dashboard. The objective is to monitor the evolution of temperatures and rainfall over the last decade, identifying climate patterns and regional anomalies through the integration of Python for data processing and dynamic visualization.

Business intelligence project focused on analyzing Adidas' commercial performance in the US (2020-2021), evaluating the relationship between revenue growth, operating margin, and profitability leaks. Through an interactive dashboard developed with Google BigQuery and Looker Studio, key commercial drivers, regions, and customer segments explaining the margin gap are identified, translating findings into actionable insights for strategic decision-making.

Geospatial analysis project focused on the visualization of pollutant emissions from diffuse sources (agricultural burning and residential wood combustion) across Chile. It utilizes Python-based data processing and interactive cartography to map emission density at the communal level, enabling the identification of environmental hotspots and supporting air quality monitoring between 2019 and 2023.

Data analysis project covering everything from data cleaning and modeling of over 22,000 records using Power Query to the creation of a Power BI dashboard. The objective is to identify critical workplace burnout and mental fatigue factors, validating hypotheses on the impact of overtime and work-life balance to propose data-driven talent retention strategies.

Data analysis project covering the cleaning of 1.8M records from ODEPA, memory optimization with PARQUET, to interactive app deployment. The goal is to visualize the evolution and regional gaps in food prices in Chile (2020-2025).