ُEmails Traffic Analysis

Objective: To turn ambiguous and inconsistent email traffic data into useful insights that can inform business decisions.

Background: The raw data used for this project consisted of email traffic records with various discrepancies and inconsistencies. The subject lines of the emails were not standardized, and there were multiple duplicates and missing values.

Methodology: The first step was to clean and preprocess the data by removing duplicates, filling in missing values, and standardizing the subject lines. Then, exploratory data analysis was performed using visualization techniques to gain insights into the email traffic patterns.

Results: The analysis revealed several interesting findings, including the busiest times of day and days of the week for email traffic, the most common subjects of emails, and the departments and individuals with the highest volume of emails sent and received. The insights provided valuable information for optimizing email communication strategies and improving overall efficiency.

Conclusion: Despite the initial challenges posed by the ambiguous and inconsistent raw data, the project was successful in turning it into meaningful insights that can inform business decisions. The visualization techniques used were effective in uncovering patterns and trends that would have been difficult to discern from the raw data alone.