Data Analytics & Business Intelligence

Empowering Retail Leadership with Real-Time Analytics & Predictive Forecasting

Background

A growing retail chain operating across 60+ stores faced growing challenges with manual spreadsheets, inconsistent KPIs, and delayed business intelligence. Leadership lacked real-time insights into sales performance, demand trends, and inventory metrics.

Business Challenge

Reporting took 24–48 hours. Data lived across spreadsheets, POS systems, and emails. Decisions were reactive instead of proactive.

Discovery & Analysis

BrevaNext conducted a deep audit of POS systems, Excel sheets, and Google Analytics data. We identified the root cause: no centralized data model, high dependence on manual ETL, and zero predictive forecasting.

Solution Architecture


      • Power BI Executive Dashboard Suite  
      • Automated Python + SQL ETL Pipelines  
      • BigQuery Data Warehouse  
      • Predictive Models for Sales & Demand  
      • Real-time Data Refresh Architecture

Implementation Approach


      • Implemented automated ETL using Python & BigQuery  
      • Built real-time Power BI dashboards for leadership  
      • Designed SKU-level demand forecasting models  
      • Enabled unified data governance framework

Business Impact

Real-Time

Reporting Speed

92%

Forecast Accuracy

−40%

Inventory Stockouts

3× Faster

Decision-Making Speed

“BrevaNext gave us true data intelligence. Our decisions are now proactive, not reactive.”

— CFO, Retail Chain

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