Placeholder case study — [REPLACE WITH REAL CASE STUDY] before launch.

← Back to Portfolio

Retail Analytics Dashboard

• React
• GraphQL
• Python
• GCP

The challenge

[REPLACE WITH REAL CASE STUDY] A multi-channel retailer had sales data scattered across POS, e-commerce, and warehouse systems.

Our solution

[REPLACE WITH REAL CASE STUDY] We built a unified data pipeline and a live dashboard with drill-downs by store, SKU, and channel.

Results

• ▸Single source of truth across 3 sales channels (placeholder metric)
• ▸Inventory decisions made in hours, not weeks (placeholder metric)
• ▸15% reduction in stock-outs (placeholder metric)