Degree

Bachelor of Science (Computer Science)

Department

Department of Computer Science

School

School of Mathematics and Computer Science (SMCS)

Advisor

Ms. Maria Rahim, Lecturer, Computer Science -SMCS

Co-Advisor

Muhammad Ahsan Siddiq, Senior Software Engineer I, Astera

Keywords

Data Repository, Web Application, Data Quality Rules, Data Profiling, Role Based Access Control

Abstract

In today’s data-driven world, ensuring data quality, discoverability, and access control has become essential for organizations that rely on accurate analytics, AI model training, and informed decision-making. However, existing data governance solutions either lack the flexibility to define complex quality rules or fall short in facilitating secure, collaborative data sharing. Our solution, DataVeritas, addresses these challenges by offering an end-to-end system where users can upload CSV/TXT datasets, perform data profiling, and run nested custom quality rules using a powerful rule parser and execution engine. Users can measure the conformity of their dataset against these rules. The platform incorporates robust role-based access control, enabling dataset owners to grant, revoke, or limit access with granular privileges. Additionally, tagging and search functionality enhance dataset discoverability, while ensuring responsiveness and scalability for large datasets.

Tools and Technologies Used

ASP.NET, NEXT.JS, Microsoft SQL Server

Methodology

We began the project with a comprehensive market review of existing data governance and data quality platforms. This initial analysis revealed that most current solutions were either limited in functionality, overly complex and difficult to use, or designed as heavy enterprise systems with high implementation and licensing costs. Common shortcomings included a lack of support for complex custom rule creation, inadequate dataset sharing controls, and insufficient user-centric features such as intuitive search and flexible tagging mechanisms. Our development approach followed the Agile methodology, emphasizing iterative progress, continuous feedback from our advisors, and team collaboration. We divided the project into sprints, each focusing on implementing key features such as file upload, profiling, rule validation, access control, and search functionality. The system architecture was designed using a modular, layered structure with clear separation of concerns between the frontend (Next.js), backend (ASP.NET Core), and database (Microsoft SQL Server).

Document Type

Restricted Access

Submission Type

BSCS Final Year Project

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