Digital Transformation

Data Architecture and Platform Unification Roadmap

We provide end-to-end solutions for designing, building, and managing reliable infrastructure and technologies that enable efficient data collection, storage, and processing, transforming raw data into structured streams ready for analysis and confident strategic decision-making. We deliver end-to-end solutions for designing, building, and managing reliable infrastructure and technologies that enable efficient data collection, storage, and processing, transforming raw data into structured streams ready for analysis and confident strategic decision-making. We also develop phased strategies and implementation plans to integrate disparate systems and technology platforms across the organization, creating a unified and interconnected environment that enhances operational efficiency and provides comprehensive insights to support fast and accurate management decisions.

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Data Architecture and Platform Unification Roadmap

Service Overview

Data Architecture and Platform Unification Roadmap

When platforms evolve independently within the same sector, recurring challenges arise, such as data duplication, inconsistent definitions across entities, fragmented reporting, and high integration costs. These issues slow down decision-making, increase operational risks, and hinder the delivery of a unified digital experience for users across the organization.

Our service provides a practical, actionable roadmap for platform unification and the creation of a single data foundation, enabling teams to integrate quickly, produce consistent reports, and scale within clear governance. We deliver end-to-end data engineering solutions to build digital “pipelines” that form the backbone of any analytics or AI system. In the context of Saudi Arabia’s digital transformation, this service is critical for leveraging data as a strategic asset. We also help organizations develop a strategic roadmap to unify and integrate their diverse, disparate technology platforms and systems.

Our services include:

- Designing and building robust systems for processing and managing big data and integrating multiple data sources.

- Establishing an optimal data infrastructure to collect and store data in warehouses and data lakes, process it through advanced ETL/ELT workflows, and transfer it efficiently and securely.

- Ensuring clean, reliable, and timely data for all stakeholders, enabling actionable insights and supporting AI models.

The service begins with a comprehensive assessment of the current state, understanding business objectives, and mapping complex data flows and workflows across systems. We then design a phased transformation plan that prioritizes integrations, sequences optimal connectivity, and selects the right technologies and frameworks, such as APIs, microservices, or enterprise service buses, to seamlessly link platforms.

Through this service, we eliminate isolated “information islands,” streamline processes, and enable smooth data flow across the organization, creating a unified view, enhancing the end-user experience, and reducing long-term operational costs associated with maintaining multiple disconnected systems.

Required Documents

List of entities/platforms in scope and their business goals
Current system inventory (applications, databases, integrations, reporting tools)
Existing architecture documentation (if available) and integration diagrams
Data domain definitions and key business metrics currently used
Current governance practices (ownership, access controls, retention, audit requirements)
Known pain points (duplication, mismatches, manual workarounds, reporting gaps)
Stakeholder list for workshops and sign-off process

What's Included

Current-State Assessment

Conduct discovery workshops, inventory existing systems (applications, databases, integrations, reporting tools), and review available architecture documentation and integration diagrams.

Target-State Data Architecture Design

Define a unified future-state architecture, including data domains and standardized key business metrics across entities.

Migration Approach Options

Determine migration strategies (phased, parallel, or pilot-first) and risk mitigation plans during transition.

Integration Patterns and Simplification

Establish standardized integration patterns to reduce duplication and complexity across platforms.

Governance Foundations

Implement ownership models, access controls, retention policies, and audit requirements to ensure accountability and data quality.

Phased Execution Roadmap

Deliver a practical roadmap with prioritized tasks and measurable milestones for incremental delivery.

Service Execution Steps

1
Definition & Preparation

- Identify entities/platforms in scope and their business objectives.
- Inventory current systems and integrations.
- Collect architecture documentation and pain points (duplication, mismatched definitions, reporting gaps).
- Review current governance practices (ownership, access, retention, audit).

2
Current-State Assessment

- Analyze data flows, domain definitions, and key metrics.
- Identify duplication, inconsistencies, and integration sprawl.
- Assess operational risks and impact on reporting and decision-making.

3
Target-State Design

- Define unified data architecture (data warehouse/data lake, domain models, integration layers).
- Standardize data definitions and KPIs across entities.
- Develop integration patterns (APIs, ETL/ELT, event-driven).

4
Migration Strategy

- Select migration approach: pilot-first, phased by domain, or platform-based.
- Prioritize migration based on value, risk, and dependencies.
- Define risk mitigation measures (parallel runs, quality checks, rollback plans).

5
Governance Enablement

- Establish ownership and accountability model.
- Implement access controls, retention policies, and audit requirements.
- Set up data quality monitoring and reconciliation mechanisms.

6
Roadmap Development

- Break down implementation into waves with measurable deliverables.
- Define resources, timelines, and KPIs (reduced duplication, improved reporting consistency).
- Create monitoring and adjustment mechanisms for roadmap execution.

7
Testing & Launch

- Conduct functional and technical testing of integrations and unified data models.
- Validate performance, scalability, and data quality.
- Execute phased rollout with change management and user training.

8
Operations and Continuous Improvement

- Perform regular reviews of architecture performance and data quality.
- Apply iterative enhancements to integration patterns and governance policies.
- Maintain updated documentation and audit readiness.

Service Benefits

A clear target-state architecture aligned with business priorities and constraints
Standardized data definitions to reduce reporting conflicts across entities
A phased roadmap that reduces risk and supports incremental delivery
Governance foundations that improve accountability, quality, and audit readiness
Reduced long-term integration cost by simplifying and standardizing patterns