Development of a Customized Analytics Powered Cloud based Operations Management Application for Post Secondary Educational Institutions

This collaborative research initiative between Academy of Learning (AOL)—a prominent Canadian Private Career College offering diploma and certificate programs in healthcare, business, and technology—and WIMTACH-CEDA aims to address AOL’s operational inefficiencies related to data management and decision-making. Currently, AOL’s reliance on disconnected third-party systems for critical functions like student registration, admissions, financial reporting, and compliance tracking results in fragmented data, inefficient workflows, and delays in critical decision-making processes. These limitations restrict AOL’s ability to maintain seamless operations and rapidly respond to administrative demands.
To overcome these challenges, AOL proposes the development of a customized, data-driven Operations Management System in collaboration with WIMTACH-CEDA. This innovative platform will centralize and automate key administrative processes, which are mentioned above. This integrated system will enable seamless connectivity with AOL’s various third-party tools, transforming previously isolated functions into a cohesive, unified framework.
Designed with a focus on scalable cloud architecture, the platform is expected to significantly enhance data accuracy, streamline workflow automation, and support real-time reporting capabilities across AOL’s departments. Through an intuitive, user-friendly interface, the system will empower AOL staff to access reliable, up-to-date data, and improve both internal and external reporting accuracy. This centralization will directly address the inefficiencies currently caused by fragmented systems, allowing AOL to operate more effectively and make data-informed decisions with greater agility.
Focusing on operational efficiency and advanced data integration, this project will support AOL’s mission of delivering high-quality educational services by improving administrative accuracy, timeliness, and responsiveness. With this solution, AOL will be able to manage critical functions more effectively, and respond promptly to institutional needs, setting a new standard in data-driven educational operations. This research project is anticipated to contribute valuable insights to the field of educational technology and offer a replicable model for improving operational efficiency and integration across private career-focused institutions.

Faculty Supervisor:

Tenzin Jinpa;Sreekumar Radhakrishna Pillai

Student:

Partner:

Academy of Learning Career College

Discipline:

Computer science

Sector:

Education

University:

Centennial College of Applied Arts and Technology

Program: