Cover image for E-commerce Sales Analytics Dashboard -

E-commerce Sales Analytics Dashboard - Power BI | ₹3.27M Revenue Tracking Client Problem: 2K customers, 8K orders in Excel. Owner had no idea which products actually make profit, which category drives customers. Dashboard Solution - 6 KPIs + 6 Visuals: Top 3 Sales: Tablet ₹0.53M | Laptop ₹0.48M | Monitor ₹0.47M Bottom 3 Sales: Phone, Chair, Printer - Clear underperformers to discount Sales by Category: Office Supplies ₹1.19M leads Furniture & Electronics Customer Mix: Electronics 34%, Office 33%, Furniture 33% - Balanced Cost Price by Category - 39% Office Supplies cost Review Rating by Payment: Credit Card 29% top, Debit 22% - Improve COD experience KPIs at Bottom: Total Sales ₹3.27M | Customers 2K | Margin 30% | Qty 8K | Profit 980K | AOV 1.81K | Rating 3.0 Impact: Client stopped pushing low-margin Phone/Chair, focused on Tablet/Office Supplies. Increased profit from 30% to 38% in 45 days Tools: Power BI, DAX, Sales Analytics For: E-commerce, Retail Stores, D2C Brands.

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Cover image for Supply Chain & Inventory Control

Supply Chain & Inventory Control Dashboard - Power BI | 126K Units | 500 SKUs Client Problem: E-commerce brand with 500 products across 6 warehouses. No visibility on what to reorder, stockout risk, or how much capital needed. What I Built - 8-Panel Command Center: Reorder Value by Product - Tablet $55K highest risk Stock Value by Warehouse - WH2 holds $1.38M (overstocked) Quantity by Warehouse - WH4 11.8K units Value by Product & Supplier - Full matrix to negotiate better rates Stock Status: 81% In Stock, 13% Low Stock, 6% Reorder Now Lead Time vs Stock - Visual alert for delayed suppliers KPIs: Total SKUs 500 | To Reorder 67 | Stockout Risk 13.40% | Capital Needed $281.63K Business Impact: Client prevented $281K in lost sales. Reduced stockout from 13.4% to 3% in 30 days. Clear reorder list daily - no manual Excel counting. Stack: Power BI, DAX, Supply Chain Analytics, Excel Timeline: 3 Days | Best for: E-commerce, Retail, Warehouse Ops

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Cover image for Insurance Portfolio Dashboard - Power

Insurance Portfolio Dashboard - Power BI | $5M Premium Tracking Client Problem: Insurance agency tracking 10K policies in Excel - no clarity on which age group claims more, which policy type is profitable. Dashboard I Built: Premium vs Claim Analysis by Age Group (Junior 6K vs Senior 4K) Claim Status Breakdown: 44% Settled, 34% Pending, 22% Rejected Claim Ratio % by Gender Customers by Policy Type: Travel 41%, Auto 20%, Home 16%, Health 12%, Life 11% KPIs: Total Customers 10K | Senior 4K | Junior 6K | Premium 5M Business Impact: Client found Senior Citizens claim 2x more vs Junior, and Travel policy is top seller. Helped them re-price premiums and save $50K in risk. Tools: Power BI, DAX, Data Modelling, Excel Timeline: 2 Days | For: Insurance Brokers / Agencies.

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Cover image for Jewellery E-commerce Sales Dashboard -

Jewellery E-commerce Sales Dashboard - Power BI | 36.64M Revenue The Problem: Client had sales data scattered across Excel - couldn't see which product, city, or payment mode drives revenue. What I Built: Single CEO dashboard with: • Top 5 Products & Cities by Revenue • Sales by Category (Diamond, Gold, Silver) • Payment Analysis (Credit, EMI, UPI, Cash) • Customer Type - Returning vs New • KPIs: 1K orders | 622 customers | 36.64M revenue The Result: Owner now sees best-selling Diamond Pendant & Chennai as top city in 5 seconds. No more manual Excel. Stack: Power BI, DAX, Power Query, Excel Timeline: 2 days

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KALYANA SREENIVASAN

Power BI Expert | Excel Chaos to CEO Dashboards