Cynthiacyna/Data-Analysis-Dashboard

In this project, I designed and developed a complete Nigeria Library Dataset and built a fully interactive Excel Dashboard featuring KPI cards, dynamic charts, slicers. The goal was to create a real-world, portfolio-ready analytics solution that demonstrates strong data wrangling, visualization, and dashboard skills using Microsoft Excel. # Nigeria Library User Engagement Dashboard Project (Using Excel) ## Project Overview Libraries play an essential role in improving literacy, supporting research, and expanding digital access across Nigeria. To better understand library operations and usage patterns, I created a 200-record dataset covering public, private, and academic libraries across major states and cities in Nigeria. The dataset captures operational metrics, service utilization, digital resource distribution, and user engagement trends. Using this data, I developed an interactive Excel dashboard that gives stakeholders a clear, data-driven view of library performance nationwide. ## Dataset used - Dataset ## Key Performance Indicators (KPIs) At the top of the dashboard, I designed five KPI cards to highlight the most important library metrics: - Total Libraries Patrons - Average Borrow Days - Average Satisfaction Score - Total Books Borrowed - Total Fines Collected These KPI cards automatically update when filtered using slicers, making them dynamic and highly responsive. ## Interactive Charts and Visualizations To provide clearer insights, I added multiple charts powered by PivotTables: - Satisfaction Score Distribution (Doughnut Chart) Shows how library patrons’ satisfaction scores are distributed across different rating levels. - Digital Usage Trend (Bar Chart) This chart illustrates how patrons engage with the library’s digital services over time. - Event Attendance by City (Line Chart) This chart tracks how library event participation varies across different cities. - Books Borrowed by Membership Type (Pie Chart) This chart shows the proportion of books borrowed across different membership categories (e.g., Adult, Researcher, Senior, Student). Each chart is clean, color-coded, well-labeled, and scales automatically when filters are applied. ## Slicers for Interactive Filtering To make the dashboard truly dynamic, I added four slicers: - Gender - Membership Type - City With slicers, user …