Unlocking business value through advanced data analytics for smarter insights, informed decisions, and strategic growth.
The Challenge
A national retail chain faced challenges due to fragmented data scattered across ERP, CRM, POS, and web platforms, resulting in disconnected systems and inconsistent information flow. The organization relied heavily on manual reporting processes, which were time-consuming, error-prone, and inefficient. This lack of integration and automation hindered access to real-time insights, limiting visibility into key business metrics and slowing down decision-making across departments and store locations. coordination across departments.
Objectives
- Integrate and consolidate data from multiple platforms.
- Eliminate manual reporting and improve data accessibility.
- Provide near real-time dashboards for decision-makers.
- Enhance forecasting and operational efficiency.
- Enable self-service analytics for business users.
High-Level Architecture
- Data Sources: ERP, CRM, POS, Web/App
- Data Ingestion: Azure Data Factory
- Storage: Azure Data Lake Gen2 (Bronze/Silver/Gold Layers)
- Processing: Azure Synapse / Databricks
- Analytics: Power BI
- Governance: Azure Purview, RBAC
Data Flow Process
- Extract data using ADF pipelines.
- Store raw data in Bronze layer.
- Cleanse & transform in Silver layer.
- Aggregate & enrich in Gold layer.
- Visualize in Power BI.
Implementation
- Data Extraction -Ingest data from ERP, CRM, POS, and Web platforms using Azure Data Factory pipelines.
- Layered Storage Architecture –
- Bronze Layer: Raw ingested data.
- Silver Layer: Cleansed and standardized data.
- Gold Layer: Aggregated, business-ready data models.
- Processing & Enrichment -Use Synapse and Databricks to transform, validate and enrich data across layers.
- Visualization & Insights -Power BI dashboards deliver dynamic, self-service access to business KPIs
Power BI Dashboards
- Sales Trends & Forecasting – Analyze historical trends and future projections across stores and regions.
- Product Performance by Region -Monitor sales by category and identify top/low performers.
- Inventory Turnover Analysis – Evaluate inventory flow, reduce dead stock, and optimize reordering.
- Customer Segmentation & Loyalty – Identify behavior-based customer segments and loyalty metrics.
- 80% faster report generation
- Real-time KPI monitoring
- Enhanced data-driven culture
- Improved operational and marketing decisions