Operations management · Django · Workflow automation
DataQ Operations
A private operations platform built for DataQ to manage recurring client work across services, months, tasks, attention events, hidden work-time intelligence, and management reporting.
PROJECT OVERVIEW
DataQ Operations was built to replace the operational parts of a general-purpose work-management tool with a system shaped around DataQ's actual process. The product models recurring work explicitly, keeps employee workflows focused, and gives management controlled visibility into progress, blockers, workload, time contribution, assessment, and reporting.
PROBLEM
Context and problem
DataQ needed to manage recurring operational work for multiple clients and services without carrying the complexity of a generic project-management suite. The workflow also required rules that ordinary task boards do not encode well: independent client/service engagements, month lifecycles, exact access boundaries, blocker-aware work timing, management-only assessments, and auditable reporting.
APPROACH
Engineering approach
I designed a modular Django/PostgreSQL monolith around those rules. Employees work inside the months they can access and can only modify assigned work, while management receives custom operational views, attention workflows, analytics, assessments, reports, reminders, and lifecycle controls. Time contribution is calculated server-side against Riyadh business hours and remains hidden from employees. The validated v1.7 release was promoted to main after browser UAT, a 591/591 regression suite, and CI checks.
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