Understanding climate change through data is crucial for assessing long-term trends and their interconnections. This study, created to showcase the application of data analytics in climate research, examines key environmental indicators over the period 1900–2023. By structuring and analyzing historical datasets, we applied a rigorous process covering data collection, preparation, cleaning, analysis, visualization, and reporting to provide meaningful insights into climate dynamics.

The analysis explores seven key questions: How has the global temperature anomaly evolved over time? What is the relationship between CO₂ emissions and temperature rise? How has the usage of renewable energy changed over the years? What is the trend in sea level rise? How has air pollution evolved? What is the correlation between forest area and temperature anomaly? How has the average global temperature changed? These insights help illustrate the complex environmental patterns shaping our planet.

To support climate research and policy discussions, we provide a cleaned dataset for structured analysis, an interactive Looker Studio dashboard to explore key trends, and a report summarizing the findings on global climate change.