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Design and Implementation of a Decision Rule and What-If Scenario Workbench
This project designs and implements design and Implementation of a Decision Rule and What-If Scenario Workbench for strategy teams. The system was developed using Python, Django, SQLite, Bootstrap, React. It provides modules for rule networks, scenario sliders, outcome tables and documentation. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of an Entity Resolution and Deduplication Tool
This project designs and implements development of an Entity Resolution and Deduplication Tool for customer data teams. The system was developed using Node.js, Express, MongoDB, EJS, JavaScript. It provides modules for matching rules, scoring, merge decisions and audit trails. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Bootstrap and Permutation Test Console
This project designs and implements design and Implementation of a Bootstrap and Permutation Test Console for research analysts. The system was developed using Python, Django, SQLite, Chart.js, Bootstrap. It provides modules for resampling engines, test statistics, confidence intervals and reporting. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Data Lake Table Catalogue and Lineage Browser
This project designs and implements development of a Data Lake Table Catalogue and Lineage Browser for data platform teams. The system was developed using Python, Django, SQLite, Bootstrap, JavaScript. It provides modules for table metadata, lineage graphs, owners and freshness checks. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Data Quality Scorecard Builder
This project designs and implements design and Implementation of a Data Quality Scorecard Builder for quality stewards. The system was developed using Node.js, Express, MongoDB, HTML/CSS, JavaScript. It provides modules for quality dimensions, scoring rules, thresholds and remediation queues. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Hyperparameter Search and Experiment Logger
This project designs and implements development of a Hyperparameter Search and Experiment Logger for machine learning engineers. The system was developed using PHP, MySQL, HTML/CSS, JavaScript. It provides modules for search spaces, trial logs, metric comparison and best runs. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Geographic Heatmap Exploration Portal
This project designs and implements design and Implementation of a Geographic Heatmap Exploration Portal for location analytics teams. The system was developed using Python, Django, SQLite, Bootstrap, React. It provides modules for map layers, regional aggregations, time sliders and annotations. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of an Executive Narrative Generation and Commentary Tool
This project designs and implements development of an Executive Narrative Generation and Commentary Tool for reporting units. The system was developed using Node.js, Express, MongoDB, EJS, JavaScript. It provides modules for metric narratives, template libraries, commentary edits and publish. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Retention Cohort and Churn Analytics Studio
This project designs and implements design and Implementation of a Retention Cohort and Churn Analytics Studio for subscription businesses. The system was developed using Python, Django, SQLite, Chart.js, Bootstrap. It provides modules for cohort tables, retention curves, churn drivers and action lists. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Data Enrichment and Cleansing Pipeline Console
This project designs and implements development of a Data Enrichment and Cleansing Pipeline Console for data engineering teams. The system was developed using Python, Django, SQLite, Bootstrap, JavaScript. It provides modules for enrichment rules, cleansing steps, lineage traces and error logs. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Forecast Confidence and Scenario Planner
This project designs and implements design and Implementation of a Forecast Confidence and Scenario Planner for business planning units. The system was developed using Node.js, Express, MongoDB, HTML/CSS, JavaScript. It provides modules for baseline forecasts, scenario inputs, confidence bands and decision notes. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Cross-Validation and Model Comparison Toolkit
This project designs and implements development of a Cross-Validation and Model Comparison Toolkit for data science teams. The system was developed using PHP, MySQL, HTML/CSS, JavaScript. It provides modules for folds, metric tables, comparison charts and best-model selection. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Snowflake-Style Warehouse Cost Usage Dashboard
This project designs and implements design and Implementation of a Snowflake-Style Warehouse Cost Usage Dashboard for data platform teams. The system was developed using Python, Django, SQLite, Bootstrap, React. It provides modules for usage metrics, cost drivers, budget alerts and optimisation tips. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Data Sharing Agreement and Consent Register
This project designs and implements development of a Data Sharing Agreement and Consent Register for data governance offices. The system was developed using Node.js, Express, MongoDB, EJS, JavaScript. It provides modules for agreement templates, consent records, use cases and audits. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Feature Store and Model Registry Portal
This project designs and implements design and Implementation of a Feature Store and Model Registry Portal for machine learning operations teams. The system was developed using Python, Django, SQLite, Chart.js, Bootstrap. It provides modules for feature definitions, versioning, model registry and deployment metadata. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Topic Drift and Document Similarity Analyser
This project designs and implements development of a Topic Drift and Document Similarity Analyser for content analytics teams. The system was developed using Python, Django, SQLite, Bootstrap, JavaScript. It provides modules for embedding inputs, drift scores, similarity maps and review logs. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a Stream Ingestion and Alerting Console
This project designs and implements design and Implementation of a Stream Ingestion and Alerting Console for real-time operations teams. The system was developed using Node.js, Express, MongoDB, HTML/CSS, JavaScript. It provides modules for ingestion pipelines, event rules, alerting and monitoring. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Waterfall and Sankey Flow Visualization Workbench
This project designs and implements development of a Waterfall and Sankey Flow Visualization Workbench for analytics studios. The system was developed using PHP, MySQL, HTML/CSS, JavaScript. It provides modules for data import, flow mapping, visual styling and export. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Design and Implementation of a KPI Scorecard and Strategic Dashboard
This project designs and implements design and Implementation of a KPI Scorecard and Strategic Dashboard for management reporting units. The system was developed using Python, Django, SQLite, Bootstrap, React. It provides modules for metric definitions, scorecards, drill-down views and commentary. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Clickstream Session Reconstruction and Pattern Mining Platform
This project designs and implements development of a Clickstream Session Reconstruction and Pattern Mining Platform for digital marketing teams. The system was developed using Node.js, Express, MongoDB, EJS, JavaScript. It provides modules for session logs, pattern mining, behaviour segments and campaign links. Testing shows the system improves record keeping, reduces paperwork and supports timely decisions.
2025 — Undergraduate
Development of a Customer Churn Prediction and Retention Analytics Platform
This study developed a customer churn prediction and retention analytics platform that scores subscribers by churn risk, explains contributing factors, and tracks retention campaigns. The platform presents segment-level risk dashboards. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the platform improved proactive retention and reduced avoidable churn, while achieving a high System Usability Scale score. The study recommends deployment in subscription-based businesses.
2025 — Undergraduate
Development of an Online Model Evaluation and Comparison Platform
This study developed an online model evaluation and comparison platform that runs cross-validation, computes confusion matrices, and compares candidate models side by side. The platform recommends models by metric and stores experiments. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the platform standardised evaluation and reduced comparison effort, while achieving a high System Usability Scale score. The study recommends use in model selection workflows.
2025 — Undergraduate
Development of a Web-Based Topic Modelling and Document Summarisation Platform
This study developed a web-based topic modelling and document summarisation platform that groups documents into themes and produces extractive summaries with key terms. Users upload corpora and review cluster labels and summaries. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Django, and Scikit-learn. The findings showed that the platform reduced review time for large document sets, while achieving a high System Usability Scale score. The study recommends use in research and knowledge-management units.
2025 — Undergraduate
Development of a Sentiment Analysis and Text Mining System
This study developed a sentiment analysis and text mining system that classifies customer reviews and extracts frequent terms, entities, and theme scores. Users upload text or connect to review exports and inspect visual summaries. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and NLTK. The findings showed that the system provided fast and consistent opinion insights, while achieving a high System Usability Scale score. The study recommends use in customer feedback and brand monitoring units.
2025 — Undergraduate
Development of a Sales and Demand Forecasting Analytics System
This study developed a sales and demand forecasting analytics system that profiles historical demand, applies trend and seasonal models, and generates forecasts with accuracy bands. The system compares forecasts against actuals and alerts planners to outliers. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, FastAPI, Statsmodels, and PostgreSQL. The findings showed that the system improved planning accuracy and reduced forecast effort, while achieving a high System Usability Scale score. The study recommends adoption by retail and distribution firms.
2025 — Undergraduate
Development of a Web-Based Privacy and Consent Management Platform
This study developed a web-based privacy and consent management platform that records data-subject consents, manages revocations, and tracks processing purposes in line with fair-use principles. The platform logs consent versions and generates compliance summaries. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the platform improved consent transparency and reduced compliance risk, while achieving a high System Usability Scale score. The study recommends integration with organisational data systems.
2025 — Undergraduate
Development of a Web-Based Data Lake Management and Cataloguing System
This study developed a web-based data lake management and cataloguing system that registers datasets, stores metadata and lineage, and provides searchable access for analysts. The system tracks resource lifecycle and ownership. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the system improved dataset discovery and governance, while achieving a high System Usability Scale score. The study recommends adoption in growing data estates.
2025 — Undergraduate
Development of a Cloud Data Pipeline Orchestration Portal
This study developed a cloud data pipeline orchestration portal that schedules, monitors, and retries data jobs across storage and processing stages. The portal visualises job graphs and tracks runtime and failures. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and SQLite. The findings showed that the portal improved pipeline reliability and observability, while achieving a high System Usability Scale score. The study recommends deployment for cloud-based data teams.
2025 — Undergraduate
Development of a Data Governance and Quality Management System
This study developed a data governance and quality management system that registers data assets, assigns stewards, and tracks quality checks against defined business rules. The system produces quality scorecards and issue queues. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Django, and SQLite. The findings showed that the system improved accountability and data quality visibility, while achieving a high System Usability Scale score. The study recommends deployment in organisations with dispersed data.
2025 — Undergraduate
Development of an Interactive Data Storytelling Platform
This study developed an interactive data storytelling platform that lets users assemble datasets, visualisations, and narrative text into guided presentations. The platform supports annotations and shareable story links. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using JavaScript, D3.js, Node.js, and MongoDB. The findings showed that the platform improved communication of data insights to non-technical audiences, while achieving a high System Usability Scale score. The study recommends use in reporting and academic presentations.
2025 — Undergraduate
Development of a Web-Based Regression and Classification Learning Tool
This study developed a web-based regression and classification learning tool that guides users through fitting, selecting, and interpreting models while checking assumptions. The tool exposes metrics and residuals and warns when models misbehave. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, FastAPI, Scikit-learn, and PostgreSQL. The findings showed that the tool deepened learning and reduced analytical errors, while achieving a high System Usability Scale score. The study recommends adoption in statistical learning courses.
2025 — Undergraduate
Design of a BI Analytics Dashboard for Small and Medium Enterprises
This study designed a business intelligence analytics dashboard tailored for small and medium enterprises, presenting sales, inventory, cash-flow, and customer metrics on a single view. The dashboard supports simple goal comparisons and exports. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the dashboard improved owner understanding of business performance, while achieving a high System Usability Scale score. The study recommends affordable rollout for SME associations.
2025 — Undergraduate
Development of a Web-Based Geospatial Data Visualization System
This study developed a web-based geospatial data visualization system that maps point data onto interactive maps with choropleth overlays and pop-up summaries. Users upload coordinates and metadata and filter by attributes. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and Leaflet. The findings showed that the system made geospatial insights accessible without specialised GIS software, while achieving a high System Usability Scale score. The study recommends deployment for community and environmental monitoring.
2025 — Undergraduate
Design and Implementation of a Data Mining Pattern Discovery System
This study designed and implemented a data mining pattern discovery system that runs association, clustering, and outlier analyses on uploaded datasets and explains discovered patterns. Users select algorithms and inspect frequent itemsets and cluster profiles. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and Scikit-learn. The findings showed that the system made pattern discovery accessible to students and analysts, while achieving a high System Usability Scale score. The study recommends use in academic and market-analysis settings.
2025 — Undergraduate
Development of a Business Intelligence Reporting System
This study developed a business intelligence reporting system that connects to operational data, builds KPI dashboards, and schedules executive reports. Users drill into trends and share dashboards. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Django, Pandas, and MySQL. The findings showed that the system improved data-driven reviews and reporting consistency, while achieving a high System Usability Scale score. The study recommends deployment in organisational management units.
2025 — Undergraduate
Development of a Data Warehousing and OLAP Reporting Dashboard
This study developed a data warehousing and OLAP reporting dashboard that consolidates multi-source data into dimensional models and supports slice, dice, and drill-down analysis. Users build reports from cubes and export summaries. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Django, Pandas, and PostgreSQL. The findings showed that the dashboard reduced report turnaround and improved analytical flexibility, while achieving a high System Usability Scale score. The study recommends adoption by institutional planning units.
2025 — Undergraduate
Development of a Customer Segmentation Machine Learning System
This study developed a customer segmentation machine learning system that groups customers using clustering algorithms and profiles each segment with visual summaries. The system scores new customers into segments automatically. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, FastAPI, and Scikit-learn. The findings showed that the system improved marketing targeting and reduced manual segmentation effort, while achieving a high System Usability Scale score. The study recommends adoption by SMEs and marketing teams.
2025 — Undergraduate
Development of a Predictive Model Deployment and API Platform
This study developed a predictive model deployment and API platform that lets data scientists register trained models, supply test inputs, and serve predictions over a REST API with usage logging. The platform compares model versions. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Flask, and SQLite. The findings showed that the platform simplified model serving and accelerated integration, while achieving a high System Usability Scale score. The study recommends use in data science teams.
2025 — Undergraduate
Development of a Big Data Processing and Analytics Pipeline
This study developed a big data processing and analytics pipeline that ingests large files, splits workloads, and produces summary analytics with progress tracking. The pipeline validates schemas and schedules batch runs. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Python, Django, and PostgreSQL. The findings showed that the pipeline handled large datasets more efficiently than manual methods, while achieving a high System Usability Scale score. The study recommends deployment in data-intensive research units.
2025 — Undergraduate
Development of a Real-Time Streaming Data Analytics Platform
This study developed a real-time streaming data analytics platform that ingests continuous data feeds, computes sliding-window aggregates, and updates live dashboards. Users monitor KPIs and set threshold alerts. Adopting a client-server architecture and a survey-based usability evaluation, the system was built using Node.js, Express, and MongoDB. The findings showed that the platform supported timely decision-making with live metrics, while achieving a high System Usability Scale score. The study recommends adoption for IoT and transaction monitoring use cases.
2025 — Undergraduate