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System Design Question

Design a Predictive Analytics System

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  1. Functional Requirements:

    • Data Ingestion: Ability to collect and process data from multiple sources in real-time or batch mode.
    • Data Preprocessing: Clean, transform, and normalize data to ensure quality and consistency.
    • Model Training: Develop and train machine learning models using historical data.
    • Prediction Generation: Generate predictions based on new input data using trained models.
    • Result Visualization: Provide visual representation of predictions and insights for end-users.
    • User Interface: Develop a user-friendly interface for interacting with the system.
    • Feedback Loop: Implement a mechanism for users to provide feedback on predictions to improve model accuracy.
    • Alert System: Notify users of significant predictions or anomalies.
  2. Non-Functional Requirements:

    • Scalability: System should handle increasing amounts of data and users without performance degradation.
    • Performance: Ensure low latency in data processing and prediction generation.
    • Reliability: System should be highly available with minimal downtime.
    • Security: Protect data integrity and ensure secure access to the system.
    • Compliance: Adhere to relevant data protection regulations and standards.
    • Maintainability: Codebase should be easy to update and maintain.
    • Interoperability: Ability to integrate with existing systems and third-party services.
    • Usability: Ensure the system is intuitive and easy to use for non-technical users.
  3. Constraints:

    • Budget: Limited financial resources for development and maintenance.
    • Time: Project must be completed within a specified timeframe.
    • Data Availability: Dependence on the availability and quality of external data sources.
    • Resource Limitations: Limited computational resources for model training and deployment.
    • Regulatory Constraints: Compliance with industry-specific regulations and standards.

System Design Diagrams

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