Rajrang: E-Commerce Analytics with Power BI Dashboards
Business Overview
Rajrang, an India-based home furnishing & accessories manufacturing company, offers a diverse product portfolio including Home Décor & Furnishing, Kitchenware, Tableware, Dining Linen, Bags, Yoga mats, and Ethnic clothing. Selling across multiple e-commerce channels, Rajrang partnered with Logesys to modernize its fragmented reporting using SQL Database and Power BI Dashboards for unified revenue and expense visibility.
Current Scenario
Rajrang's e-commerce data was scattered across multiple portals with varying granularities, requiring heavy manual intervention for data pulls, collation, cleansing, and SQL database loading. Management lacked a single view of revenue, expenses, product performance, and profitability across channels. Manual batch processes were error-prone and time-consuming, preventing real-time business insights.
Recognizing the need for automated, unified e-commerce analytics, Rajrang engaged Logesys to build a scalable reporting platform.
Recognizing the need for automated, unified e-commerce analytics, Rajrang engaged Logesys to build a scalable reporting platform.
Project Objective
- Consolidate multi-channel data into a normalized SQL reporting layer
- Standardize varying data granularities for consistent analysis
- Enable real-time Power BI dashboards across orders, fulfillment, products, and expenses
- Provide product-level profitability and P&L visibility
- Automate data ingestion to eliminate manual reporting processes
Scope of Work
- Extract raw data from multiple e-commerce portals into SQL Database
- Normalize varying data granularities (order-item-SKU level) with automated transformations
- Develop comprehensive Power BI dashboards covering Order Management, Fulfillment, Product Performance, Expenses, and P&L
- Enable drill-down analytics from channel/geography to individual SKU level
- Implement automated data pipelines replacing manual batch processes
Data Flow Design & Technical Solution
| Component | Purpose |
|---|---|
| SQL Database | Centralized data warehouse for e-commerce data normalization and reporting |
| Automated ETL | Data extraction, cleansing, and standardization from multiple portals |
| Power BI Dashboards | Interactive analytics covering orders, products, expenses, and profitability |
| Drill-Down Analytics | Channel → Geography → Product Hierarchy → SKU level insights |
Architecture Flow:
Raw Data Layer: Multi-portal e-commerce data (orders, shipments, expenses)
ETL Normalization: Standardized granularity in SQL Database
Unified Reporting Layer: Normalized data for Power BI consumption
Interactive Dashboards: Real-time insights across all business functions
Raw Data Layer: Multi-portal e-commerce data (orders, shipments, expenses)
ETL Normalization: Standardized granularity in SQL Database
Unified Reporting Layer: Normalized data for Power BI consumption
Interactive Dashboards: Real-time insights across all business functions
Solution Design
Data Extraction
Tool: Automated ETL to SQL Database
Description: Replaced manual data pulls from e-commerce portals with scheduled automated ingestion and cleansing
Data Normalization
Tool: SQL Database
Description: Standardized varying granularities (order → item → SKU) for consistent cross-channel analysis
Data Warehousing
Tool: SQL Database
Description: Single source of truth enabling unified revenue, expense, and profitability reporting
Reporting & Visualization
Tool: Power BI Dashboards
Description: Five comprehensive dashboards with full drill-down from channel/geography to SKU profitability
Is your e-commerce data holding you back?
Stop wasting hours on manual data pulls and fragmented spreadsheets. Let Logesys build your single source of truth.
Request a Demo of Our E-Commerce Framework
Stop wasting hours on manual data pulls and fragmented spreadsheets. Let Logesys build your single source of truth.
Request a Demo of Our E-Commerce Framework
Challenges & Solutions
| Challenge | Solution |
|---|---|
| Fragmented multi-portal data | Automated ETL consolidated all sources into normalized SQL layer |
| Varying data granularities | SQL transformations standardized data at order-item-SKU level |
| No unified revenue view | Power BI provided single view across all channels and geographies |
| Manual data processes | Automated pipelines eliminated manual batch runs and cleansing |
| No product profitability | Detailed P&L dashboards with Amazon expense impact analysis |
Business Impact
- 75% reduction in manual reporting time through automation
- Complete SKU-level profitability visibility across all channels
- 30% improved inventory turnover via rate-of-sale and stock cover analytics
- 25% expense optimization through Amazon fee and ad spend analysis
- Real-time order fulfillment monitoring with TAT and return insights
- Actionable P&L insights driving channel and geography optimization
Key Dashboard Capabilities
- Order Booking: Drill-down to order-item level, shipping charges, cancellation reasons
- Fulfillment: FC efficiency TAT, return analysis, reimbursement tracking
- Product Performance: Sales/returns by hierarchy, ROS, inventory turns, reorder levels
- Expenses: Amazon fees, shipping, ad spend efficiency, keyword performance
- P&L: Detailed statements with geography/channel breakdowns
Conclusion
Rajrang now operates on a unified e-commerce analytics platform powered by SQL Database and Power BI dashboards. Business leaders access real-time insights into multi-channel performance, product profitability, and expense optimization, enabling data-driven inventory, pricing, and marketing decisions. Logesys delivered this transformation, establishing a scalable foundation for Rajrang's continued e-commerce growth across India and beyond.
Take control of your profitability today.
Join the ranks of data-driven brands like Rajrang. Contact Logesys to modernize your reporting layer.
Contact Our Expert Team
Join the ranks of data-driven brands like Rajrang. Contact Logesys to modernize your reporting layer.
Contact Our Expert Team
