01 Data.zip -

Mention if you used techniques like Random Forest estimation or simple linear regression. 4. Key Findings & Visualizations

Handling missing values, duplicates, or formatting issues. Tools Used: (e.g., Python/Pandas, Excel, SQL, or MATLAB).

Where did the data come from? (e.g., European Central Bank , internal company database, or academic repository). 01 Data.zip

Include charts (Bar, Line, or Heatmaps) to support these points. 5. Conclusions & Recommendations Summarize what the data tells you.

Suggest the next steps (e.g., "Increase inventory for Q3" or "Investigate the dip in user engagement observed in file 01 Data.csv "). Mention if you used techniques like Random Forest

The timeframe and population covered (e.g., "Daily exchange rates from 1999 to 2026"). 3. Methodology Describe how you processed the data:

List the files found inside the zip (e.g., data.csv , metadata.txt ). Tools Used: (e

Describe a major pattern (e.g., "Sales peaked in Q3"). Trend 2: Note any significant correlations or anomalies.