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App Review Analysis, Rating Prediction System, & Big Data Business Use Cases

Welcome to the documentation and development portal for the Review Analysis & Rating Prediction project.

In the modern mobile ecosystem, user feedback is a high-volume, high-velocity stream of unstructured data. While our company receives thousands of reviews weekly, the ability to transform that text into actionable insights—starting with accurate rating prediction—is critical for both developers and store curators.

🎯 Project Mission

We have inherited a prototype system that, while functional, lacks the robustness, transparency, and architectural integrity required for production. Our objective is to transition this “weak and biased” model into a mature Data Science Software Product through a full engineering lifecycle.

This site serves as a live record of our transition from a loosely documented prototype to a rigorous, scalable, and well-documented system.


🏗️ Core Pillars of Our Approach

We aren’t just building a better model; we are building a better system. Our work is organized around four key engineering domains:

📋 Requirements & Stakeholders Defining exactly what the system needs to do and for whom, ensuring we address the biases of the previous iteration.

🏗️ System Architecture Designing a transparent, modular pipeline that separates data ingestion, processing, and inference.

🚀 ML Lifecycle (MLOps) Evolving the model from a prototype to a refined pipeline with clear evaluation metrics and reproducible results.

🤝 Team Management Practicing agile coordination and reflective engineering to ensure our process is as high-quality as our code.


🗺️ Project Roadmap

PhaseDescriptionStatus
DiscoveryRe-evaluating the prototype and stakeholder needs✅ Complete
DesignArchitecting the baseline pipeline and data flow🚧 In Progress
DevelopmentModel evolution and system implementation⏳ Planned
EvaluationTesting against requirements and bias metrics⏳ Planned

👥 Meet the Team

We are a part of the Applied Data Science engineering team.