Data Architecture & Foundations (Microsoft Fabric)
Designing data platforms that are understandable, governed, and durable.
Data architecture defines how data is created, moved, stored, governed, and consumed across an organization.
At Core Data Fuse, we treat data architecture as a foundational enterprise capability, not a tooling exercise. We design and deliver Microsoft Fabric based data platforms that organizations can operate, govern, and evolve with confidence.
Our work supports analytics, reporting, and AI initiatives while remaining secure, resilient, and aligned with how the business actually functions. We engage across both new data platform initiatives and existing enterprise data environments.
- Data platforms have grown without clear architectural direction
- Analytics and reporting lack consistency or trust
- New use cases are constrained by legacy data architectures
- Governance and security expectations are increasing
- Senior architectural ownership is needed without adding permanent headcount
In these situations, data architecture functions as a stabilizing foundation that enables progress without increasing long term risk.
Many organizations already operate data platforms with defined tooling, standards, and delivery partners.
In these environments, we commonly engage to:
- Complement internal data teams or existing vendors
- Act as an alternative delivery partner for new data initiatives
- Provide architectural clarity where platforms have grown organically
We are comfortable working within existing data models, governance frameworks, and operating constraints, and do not require organizations to re platform to engage with us. This allows teams to introduce us on new use cases or domains with minimal disruption.
We have deep experience designing and delivering data architectures using modern, enterprise grade platforms, with a primary focus on Microsoft Fabric.
Microsoft Fabric provides a unified environment for data ingestion, lakehouse based storage and processing, analytics, reporting, and governance. We design Fabric architectures that are intentional, structured, and aligned with enterprise operating models rather than loosely assembled collections of workloads.
Platform usage is driven by organizational context, maturity, and long-term sustainability rather than feature adoption.
Domain Oriented and Purpose Driven Design
We design data architectures that establish:
- Clear data ownership and accountability
- Logical separation of domains and responsibilities
- Alignment between operational systems and analytical consumption
This reduces ambiguity, improves data trust, and enables teams to evolve data products independently.
Lakehouse Based Foundations
Where appropriate, we design lakehouse architectures using Microsoft Fabric that balance:
- Flexibility of raw and curated data storage
- Performance and scalability for analytical workloads
- Clear separation between ingestion, transformation, and consumption
The objective is to support both current reporting needs and future analytical or AI driven use cases.
Analytical and Semantic Layer Design
Reliable analytics require more than raw data.
- Curated data models aligned to business concepts
- Semantic layer design for consistent reporting and self-service analytics
- Clear lineage from source systems to analytical outputs
This improves consistency across dashboards, reports, and downstream consumers.
Data platform delivery is treated as software and platform engineering, not ad hoc development.
Our delivery practices include:
- Source control for data pipelines, models, and configurations
- Environment separation and controlled promotion
- CI CD practices aligned to platform capabilities
- Reproducible deployment and configuration management
These practices reduce operational risk and support predictable evolution of the data platform.
Data platforms introduce significant governance and security considerations.
Our approach includes:
- Clear access controls and role based permissions
- Alignment with enterprise identity and security models
- Data classification and sensitivity awareness
- Support for auditability, lineage, and traceability
- Integration with broader security and risk frameworks
Security and governance are embedded into platform design rather than layered on after implementation.
In addition to project-based delivery, we offer managed service packages for organizations operating Microsoft Fabric based data platforms.
These services are designed to complement existing data operations, not replace internal ownership.
Managed services may include:
- Platform health monitoring and operational support
- Incremental enhancements and data model evolution
- Pipeline reliability and performance tuning
- Platform upgrades and feature enablement
- Architecture and standards enforcement
- Documentation and knowledge continuity
This provides stability and architectural consistency as data platforms mature.
Depending on scope and engagement model, our data architecture services may include:
- Data platform architecture and target state design
- Domain and data model definition
- Ingestion and transformation design
- Lakehouse and analytical architecture
- Semantic and reporting layer design
- Platform enablement and delivery support
- Hands on implementation and technical leadership
- Ongoing managed support and enhancement
We design data foundations that teams can operate, trust, and extend over time.
Project Based Delivery
New data platform or domain initiatives, incremental expansion of existing Fabric environments, and modernization of legacy data architectures.
Architecture and Advisory
Data strategy and roadmap definition, architecture reviews, design validation, and governance and operating model definition.
Managed Services
Ongoing support and enhancement of Microsoft Fabric environments with operational stability and architectural oversight.
Engagements are scoped based on platform maturity, complexity, and organizational needs.
Build data foundations that scale with you
If you are planning a Microsoft Fabric initiative, evolving an existing data platform, or addressing data architecture challenges, we are happy to have a focused technical discussion.
Book a Discovery CallNo sales pitch. Just a practical data architecture conversation.