Durban University of Technology / Jan – May 2024

From questions
to systems.

A research chapter in data, requirements and technical leadership.

Research Assistant / Software Developer (Jan–Mar) → Technical Lead (Mar–May)

Node.jsExpress.jsReactPower BIAWS research
Conceptual reconstruction / architecture study
Research questions01Requirements & model02DMS / data exploration03Departmental insights04MODEL / DUT / NO PRODUCTION DATA

Reconstructed to explain the work. Not an original system screenshot.

Interactive concept / invented demo records

Research & document workspace

Inspect how document status and ownership could help structure an academic review workflow.

CONCEPT INTERFACE
NO PRODUCTION DATA
3 demo records
Conceptual reconstruction with invented sample data; not an original employer interface.
Demo documentOwnerVersionState
Research proposalStudent Av1Review
Literature outlineStudent Bv2Approved
Methodology notesStudent Cv1Review

A conceptual metadata view. Real access control, storage and authorisation belong in the application and database layers, not in a front-end status selector.

CASE STUDY / 01

Document Management System

Led an eight-member team developing a DMS for postgraduate students using Node.js and Express.js.

My contribution

Designed database architecture and coordinated development tasks using Agile methods, supporting document handling and accessibility.

Methods & tools

Technical leadership • Node.js • Express.js

CASE STUDY / 02

Hospitality CRM requirements

Researched CRM systems and developed a Functional Requirements Specification for the Hospitality Department.

My contribution

Gathered requirements, collaborated with stakeholders and explored implementation strategies appropriate to the academic environment.

Methods & tools

Stakeholder research • Functional specifications

CASE STUDY / 03

Data-lake research & visualisation

Researched AWS services and potential data-lake architectures for MICT SETA; developed Power BI dashboards during the research assistant role.

My contribution

Explored data lakes and warehouses, identified useful data points and provided architecture recommendations and departmental advice.

Methods & tools

AWS research • Power BI • Data modelling

Lead the delivery

An eight-person development team and an academic context.

Ask before building

Requirements and research informed implementation choices.

Separate research from deployment

AWS exploration is presented as research, not a live infrastructure claim.

Employment history and contributions verified against the supplied CV. System models are illustrative reconstructions, not original proprietary screenshots. DUT’s official brand guidelines were consulted. No official logo or campus imagery is reproduced. Each page is an independent portfolio interpretation; its palette is not presented as an official employer colour specification.