Sales Performance Dashboard | Power BI

Designed and developed an interactive sales analytics dashboard to help stakeholders monitor revenue, customer growth, product performance, and regional sales trends in one centralized view.

Tools Used: - Power BI -Power Query - DAX - PowerPoint (wireframing and dashboard planning)

My Contributions: - Imported and transformed raw sales data using Power Query. - Built a star schema data model by creating relationships between fact and dimension tables.

Developed DAX measures for: - Total Sales ($105M) - Total Quantity Sold (6M units) - Total Customers (9,191) - Average Unit Price ($17.6) - Created Previous Year (PY) metrics and Year-over-Year growth calculations for sales, quantity, and customers. - Implemented conditional formatting with dynamic color indicators to highlight performance changes.

Dashboard Features: - Geographic sales analysis using Shape Maps. - Monthly trends for sales, quantity, pricing, and customer acquisition. - Customer segment analysis using donut charts. - Product and country performance rankings using stacked bar charts. - Interactive filtering for business units and service plans.

Business Impact: The dashboard provides decision-makers with a single source of truth for tracking sales performance, customer behavior, and regional trends, enabling faster and more informed business decisions.

Sales Performance Analysis using Excel Pivot Tables

Analyzed sales performance data using Excel Pivot Tables to identify revenue contribution across sales representatives and product categories. Built interactive summaries to compare individual sales performance, product demand, and overall business revenue.

Tools Used: - Microsoft Excel - Pivot Tables - Pivot Charts - Data Aggregation - Business Reporting

My Contributions: - Structured raw sales data for analysis. - Built Pivot Tables to summarize sales by: - Sales Representatives - Product Categories - Revenue Contribution - Created dynamic reports to compare performance across products and team members. - Used Excel aggregation functions to generate business insights from transactional data.

Key Insights: Identified top-performing sales representatives. Determined highest revenue-generating product categories. Highlighted sales concentration across products and personnel.

Business Value: The analysis provided management with a quick overview of sales performance and product contribution, enabling data-driven decisions around sales strategy and resource allocation.