📊 Power BI Dashboard – Revenue & Retention Analysis

An interactive Power BI dashboard designed to analyze revenue performance, sales channels, product categories, and customer retention.
This project demonstrates my skills in data modeling, DAX, and interactive dashboard design using Power BI.

• Provide a clear executive view of revenue, orders, and key KPIs.
• Enable users to explore channel performance, top-selling products, and category contributions.
• Track customer retention using cohort analysis to monitor engagement over time.

KPIs: Total Revenue, Total Orders, Distinct Customers, and Average Ticket.
Visuals: Yearly Revenue (Column Chart), Revenue by Channel (Bar Chart).
Filters: Date, Acquisition Channel, and State (UF).
Goal: Provide decision-makers with a high-level snapshot of business performance.

Visuals: Revenue by Channel (Bar Chart), Revenue by Channel over Time (Stacked Column Chart).
Table: Channel share, total orders, and % of contribution.
Goal: Quickly compare performance of marketing channels (Ads, Organic, Social, Partners).

Visuals: Top Products by Revenue (Column Chart), Revenue by Category (Treemap).
Table: Revenue and total orders per product and category.
Goal: Identify best-selling products and categories, driving the highest revenue share.

Visuals: Cohort Heatmap showing monthly revenue contribution by cohorts.
Goal: Track customer engagement and measure retention across time since acquisition.

• Star schema with: orders, order_items, customers, channels, and products tables.
• Relationships established by primary/foreign keys (customer_id, order_id).

• Total Revenue = SUM(order_items[price])
• Average Ticket = DIVIDE([Total Revenue], [Total Orders])

• KPI Cards, Clustered Column Charts, Treemaps, and Bar Charts.
• Slicers for date, channel, state (UF), and category.

• Executive_PowerBI_Dashboard_Business_Insights.pbix
• Project Documentation (PDF)

1. Download the .pbix file and open it in Power BI Desktop.
2. Explore the dashboard using slicers for date, channel, and product category.
3. Review the PDF for context on the business problem, solution design, and technical approach.

• Microsoft Power BI Development
• Data Visualization & Storytelling
• DAX & Data Modeling
• Business Intelligence & Analytics
• KPI Tracking & Cohort Analysis