The Superstore Dashboard provides valuable insights into sales performance, profitability by product, and customer segment distribution. The analysis reveals a healthy growth in sales and profit, along with a slight improvement in return rates. By focusing on high-performing products, addressing underperforming ones, and aligning strategies with customer segment behavior, the superstore can enhance its profitability and market reach. Continuous monitoring and adapting to these insights will be key to long-term success. 

The map displays the distribution of assigned personnel and strategic partners across the area called Cross River, Nigeria. Red dots are used to represent the assigned personnel, and they appear densely concentrated around the central and lower areas of the town, showing active presence in those locations. Green dots indicate strategic partners, but only a few of them are visible on the map. These green dots are scattered and far apart from one another, suggesting that strategic partnerships in this region are limited and not evenly distributed. While the personnel coverage is strong and widespread, the lack of more green dots points to a possible gap in partnership support. The map does not show any blue dots even though the legend includes SIB, which could mean that there is either no available data for this group or they were filtered out. Overall, the map helps to understand how field teams are positioned and reveals the need for expanding strategic partner involvement in more areas.

The heatmap analysis reveals strong regional variations in sales performance. Ibadan emerges as the highest-performing region with a total annual sales volume of ₦81,063,590, significantly outperforming all other regions. Kaduna, Lagos, Abuja, and Port Harcourt also show strong performance but remain lower than Ibadan. In contrast, regions such as Jos, Enugu, and Abeokuta report extremely low sales levels, indicating possible market weakness, distribution challenges, or operational issues. Monthly patterns show that Ibadan maintains consistently high sales throughout the year, reflected in its darker intensity across multiple months, suggesting strong demand and stable market engagement. Meanwhile, some regions display fluctuating performance, pointing to seasonal or regional sales dynamics. Overall, the heatmap allows for quick identification of top-performing locations, underperforming markets, and general sales trends across the year.

This Retail Sales Analytics Dashboard provides a comprehensive view of business performance across product lines, branches, customer types, and payment modes. The analysis highlights key insights such as total revenue, monthly sales trends, top-performing products, and customer purchasing behavior. Using Power BI, I transformed raw transactional data into an interactive dashboard that helps stakeholders quickly identify revenue drivers, compare branch performance, and understand customer patterns. The dashboard showcases my ability to clean and model data, create meaningful visualizations, and communicate insights clearly. It demonstrates practical skills in:

• Data modeling & DAX calculations

• Interactive data visualization

• Trend and performance analysis

• Customer segmentation

• Business decision storytelling
  This project reflects my ability to turn data into actionable insights that support decision-making and business growth.

This project analyzes customer churn to understand why customers leave and identify patterns that can help improve retention.

The dataset contains 7,043 customers, with an overall churn rate of 26.54%, meaning 1,869 customers stopped using the service. I cleaned the data and created an interactive dashboard to explore churn across different customer segments.

Key insights from the analysis show that: Customers on month-to-month contracts have the highest churn rate compared to those on one-year or two-year contracts. Customers without partners or dependents are more likely to churn than those with family ties. Churn is higher among customers using fiber optic internet service compared to DSL or no internet service. Customers paying via electronic check show higher churn than those using automatic payment methods like bank transfer or credit card. Churn rates are relatively similar across male and female customers, indicating gender is not a strong churn driver.This dashboard helps businesses quickly identify high-risk customer groups and supports data-driven decisions to reduce churn through better contract strategies, payment options, and service improvements.

Tools used: Excel / Power BI

Skills demonstrated: Data cleaning, data analysis, data visualization, and insight storytelling.

This HR Analytics Dashboard gives an overall picture of the company’s workforce and what’s going on with employees. It shows the total number of staff, how many are still active, and how many have left, with an attrition rate of a little over sixteen percent. The average employee age is thirty-seven, and the gender distribution is fairly balanced, though there are slightly more males. When you look deeper, more employees with Bachelor’s degrees tend to leave compared to other education levels. Certain roles like Sales Executives and Laboratory Technicians experience higher turnover, and the Sales department stands out as the area with the most attrition overall. Younger employees, especially those in the early stage of their careers, leave more often, and single employees appear to exit more than married or divorced staff. The dashboard also allows filtering by different categories, making it easy to explore patterns and understand where retention efforts may be needed.