DigiVal Integration Framework

Education Software
November 18, 2025

Ahmed Kabeer

This document outlines the DigiVal Integration Framework, a comprehensive solution designed to seamlessly connect diverse institutional systems with the DigiVal Cloud Core. The framework facilitates data flow through a multi-modal integration layer, ensuring data governance, security, and efficient processing for enhanced learning analytics, personalized experiences, and improved institutional outcomes.

Institution Systems

The framework begins by acknowledging the diverse landscape of institutional systems that need to be integrated. These typically include:

LMS (Learning Management System): The central platform for course delivery, content management, and student interaction.
SAS/SIS (Student Administration System/Student Information System): Manages
student records, enrollment, grades, and other administrative data.
Legacy ERP (Enterprise Resource Planning): Handles financial, human resources, and other operational aspects of the institution.
Campus Databases: Various databases storing specific institutional data, such as
library resources, research data, and facilities information.

Integration Layer (3 Modes)

The integration layer acts as the bridge between these disparate systems and the DigiVal Cloud Core. It offers three distinct modes to accommodate different data types, integration requirements, and system capabilities:

1. Real-Time Event Integration

Mechanism: Employs event bus technology, webhooks, or Kafka for real-time data
Directionality: Supports bi-directional data flow, enabling both ingestion and
Data Scope: Handles events related to enrollment, course activities, calendar updates, and assessment submissions.
Use Case: Ideal for scenarios requiring immediate data synchronization, such as real-time notifications or dynamic updates to learning dashboards.

2. API-Based Integration

Mechanism: Leverages REST or GraphQL APIs to access and exchange
Scheduling: Supports scheduled synchronization at hourly, nightly, or custom
Data Scope: Focuses on core academic data, including courses, programs, and academic calendars.
Use Case: Suitable for systems with well-defined APIs and data that can be synchronized periodically.

3.Database Connector Integration

Mechanism: Utilizes a thin connector layer to directly access
Access Type: Provides read-only access to prevent unintended data
Extraction Methods: Supports Change Data Capture (CDC), incremental extraction, and batch extraction to optimize data
Use Case: Best suited for legacy systems or databases without readily available APIs, allowing for efficient data extraction without impacting system performance

Governance & Security

Data governance and security are paramount throughout the integration process. The framework incorporates the following measures:

Joint Governance Workshops: Collaborative sessions with stakeholders to define data ownership, access policies, and integration
Data Access Boundaries: Clearly defined roles and permissions to restrict data access based on user roles and responsibilities.

Environment Rules (DEV/QA/UAT/PROD): Segregated environments for development, testing, user acceptance testing, and production to ensure data integrity and prevent disruptions.
Audit Logs & Compliance: Comprehensive audit logs to track data access, modifications, and integration activities, ensuring compliance with relevant regulations.

Iterative Data Sync Policy: A well-defined policy for data synchronization, including frequency, conflict resolution, and error.

Data Processing Layer

The data processing layer transforms raw data from various sources into a consistent and usable format for the DigiVal Cloud Core. Key processes include:

Data Normalization: Standardizing data formats, units, and representations to ensure consistency across different
Transformation to DigiVal Schema: Mapping data elements from source systems to the DigiVal Cloud Core’s unified data schema.

Validation & Cleansing: Identifying and correcting data errors, inconsistencies, and missing values to improve data
Streaming & Pipeline Orchestration: Managing the flow of data through the processing pipeline, ensuring efficient and reliable data delivery.

DigiVal Cloud Core

The DigiVal Cloud Core serves as the central repository and processing engine for all integrated data. It provides the following functionalities:

Unified Data Store: A centralized repository for storing normalized and transformed data from various institutional systems.

Learning Analytics Engine: A powerful engine for analyzing student learning data, identifying trends, and providing insights into student
Engagement Tracking: Monitoring student engagement with learning resources and activities to identify at-risk students and personalize interventions.

Program & Curriculum Mapping: Mapping courses and learning outcomes to programs and curricula to ensure alignment and identify
AI/ML Personalization Models: Utilizing artificial intelligence and machine learning to personalize learning experiences, recommend relevant resources, and provide targeted support.

Institutional Consumption

The integrated data and insights generated by the DigiVal Cloud Core are consumed by various stakeholders through the following channels:

Dashboards: Interactive dashboards providing real-time insights into key performance indicators (KPIs) related to student success, program effectiveness, and institutional
Reports: Customizable reports providing detailed analysis of student data, learning outcomes, and institutional trends.

Student Success Analytics: Tools for identifying at-risk students, predicting student performance, and recommending
Faculty Tools: Resources for faculty to track student engagement, assess learning outcomes, and personalize instruction.

Admin Controls: Administrative tools for managing data access, configuring integration settings, and monitoring system.

The DigiVal Integration Framework provides a robust and scalable solution for connecting diverse institutional systems, enabling data-driven decision-making, personalized learning experiences, and improved institutional outcomes.