Business analytics · Django · Data workflows
DataSense
An Arabic-first analytics platform that takes e-commerce data from validation through sales analysis, inventory, forecasting, pricing, and basket insights.
PROJECT OVERVIEW
DataSense was developed as an end-to-end analytical workflow for small and medium-sized e-commerce businesses. Instead of treating dashboards as isolated charts, it connects data ingestion, business rules, analytics, forecasting, inventory operations, and decision-support features in one system.
PROBLEM
Context and problem
E-commerce businesses often have enough raw data to produce charts, but not enough structure to trust the decisions that follow. Order states, inventory changes, pricing history, forecasting, and repeatable reporting all require consistent definitions and validation.
APPROACH
Engineering approach
DataSense validates imported records, applies explicit business and analytical rules, and presents the results through connected workflows rather than disconnected reports. The public environment uses generated data and disables sensitive write operations server-side.
SYSTEM STRUCTURE
How the main parts of the system connect.
A simplified view of the project architecture, showing the main stages and the boundaries between them.
KEY CAPABILITIES