Data Management Module (SR)

Associated Requirements:

Description:

The Data Management Module is a crucial component of the Social Registry (SR), designed to ensure data accuracy, consistency, and integrity across the system. Its primary purpose is to manage, validate, and maintain high-quality data for potential beneficiaries, supporting efficient and effective social protection program operations.

Key components include:

1. Data Matching Engine: Performs advanced data matching, validation, and deduplication.

2. Database Management System: Manages the storage, retrieval, and governance of data.

Sub-components:

• AI-Assisted Validator (SR-007, Optional): Incorporates AI capabilities for advanced data validation and anomaly detection.

• Data History Manager (SR-008, Core): Maintains a complete history of data changes, allowing reconstruction of registrant status at any point in time.

• Data Verification Module (SR-009, Core): Implements or integrates with a Data Verification Module to ensure data accuracy through automated and manual verification processes.

• Master Data Management (SR-010, Core): Implements master data management practices for core entities with processes for resolving conflicts between different data sources.

• Verification Status Tracker (SR-011, Optional): Maintains a record of the verification status for each registrant.

• Data Governance Framework (SR-018, Optional): Implements a Data Governance Framework that can interface with external compliance and audit systems to maintain the integrity and reliability of registrant data.

• Advanced Deduplication Algorithms (SR-053, Optional): Implements fuzzy matching algorithms and biometric information processing capabilities to identify and resolve potential duplicate entries.

User Journey:

1. Users: Data administrators, program managers, data quality analysts

2. Process: Data validation, deduplication, verification, and governance

3. Business Process:

   1. User logs into the SR system

   2. Navigates to the Data Management Module

   3. Selects desired data management function (e.g., validation, verification, deduplication)

   4. Sets parameters for the selected function

   5. Initiates the process and monitors progress

   6. Reviews results and takes necessary actions (e.g., resolving conflicts, updating verification status)

   7. Generates reports on data quality and integrity

   8. Uses insights to improve data management processes and overall data quality

Links to other modules:

• Provides clean, validated data to the Eligibility and Targeting Module

• Interacts with the Data Collection and Intake Module to ensure data quality at entry

• Supplies data quality metrics to the Reporting and Analytics Module

• Interfaces with the Security and Privacy Module for data protection and access control

This module plays a vital role in maintaining the overall quality and reliability of the Social Registry data. It ensures that the data used for decision-making and program operations is accurate, consistent, and up-to-date. The AI-assisted components and advanced algorithms enhance the efficiency and effectiveness of data management processes, while the governance framework ensures compliance with data protection regulations and best practices.