25/10/2024
Progress Report: My Beginner Journey in Data Science at NCAIRNigeria🎓💻
This week brought another milestone in my Data Science journey at NITDA/NCAIR Nigeria! I’m thrilled to showcase my recent project focused on User Behavior Class (Mobile Phone), which dives into mobile usage patterns and demographics across various user groups. Data for this project was sourced from Kaggle, and I used Power BI to make sense of the data with engaging, insightful visuals.
📊 Key Highlights of My Project:
User Behavior Classification & Demographic Analysis:
User Segmentation: I classified user behavior into Low, Medium, and Extreme usage categories. I also categorized age groups into GenZ, GenX, Millennials, and Elders, providing a clear breakdown of mobile behavior by age.
Gender Breakdown: Calculated and visualized the percentage distribution for male and female users across behavior classes.
Mobile User Types: Analyzed the data for five distinct types of mobile users identified in the research.
Interactive Power BI Dashboard:
Created dynamic dashboards in Power BI that provide quick insights into key usage metrics:
User Screen On Time (hours/day)
Battery Drain (mAh/day)
Number of Apps Installed
Data Usage (MB/day)
The visuals not only highlighted differences in data usage and battery drain among user types but also allowed for quick gender and age-based comparisons.
Comparative Analysis:
Conducted comparative analyses to explore how metrics like screen time and data usage vary across Low, Medium, and Extreme users. Extreme users, for example, were shown to have the highest data usage and battery drain, which provided valuable insights into mobile behavior trends.
This project significantly sharpened my skills in data analysis and visualization, offering a deeper understanding of user behavior patterns. Looking forward to sharing more insights and taking on new challenges as I progress on this data science journey!