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Data Architecture
Build reliable, scalable, secure and insight-driven solutions with a robust data architecture
Data Architecture
Data Architecture is the strategic design of an organisation’s data assets, policies, standards and infrastructure. It provides the blueprint for how data is collected, stored, integrated, managed and used across the enterprise.
When well implemented, it helps ensure that data remains accurate, usable and aligned with operational needs. It also supports governance, access control, regulatory compliance and the ability to work with both cloud and on-premises environments without adding unnecessary complexity.
At Claria, we help organisations design and implement practical data architectures that support growth, reduce risk and make data easier to manage across changing environments.
Our Clients
Businesses that have trusted us
The benefits of getting Data Architecture right
A well-planned data architecture serves as the foundation for how your organisation manages and uses information. It brings structure to complexity, connects systems in meaningful ways and ensures data works in support of business priorities across teams, platforms and environments.
Here’s what organisations gain when they get it right:
Enable scalability and flexibility
A well-structured data architecture supports future growth and transformation. It allows your organisation to integrate new data sources, scale workloads and evolve business capabilities without expensive rework.
Improve data quality and consistency
With standardised models, formats and data flows, you ensure consistency across systems. This reduces duplication, errors and friction between business units.
Support better decision-making
Clear data lineage, real-time access and integration across sources give stakeholders reliable, timely information to support both strategic and operational decisions.
Strengthen data governance and security
A defined architecture supports compliance with data protection laws and internal policies by embedding access controls, encryption and retention strategies from the ground up.
Reduce technical debt
Centralised design and planning reduce redundant integrations, siloed data stores and short-term fixes that accumulate over time.
How can we help you and what do we do?
At Claria, we help organisations design and implement data architectures tailored to their business, technology landscape and strategic goals.
Get in touchOur Data Architecture Services
Enterprise data architecture design
We define principles, models and blueprints that underpin your entire data estate across on-premises, cloud and hybrid environments.
Data modelling and taxonomy development
We help establish shared language and structure across systems through logical and physical data models.
Data integration and orchestration planning
We create unified architectures for APIs, ETL/ELT pipelines, messaging and event-driven data flows.
Reference architecture templates
We deliver reusable patterns and best practices for rapid scaling and standardisation.
Cloud-native and hybrid architectures
We enable platform-agnostic, flexible architectures using microservices, containers and distributed processing engines.
The technologies we use at Claria
At Claria, we work with a wide spectrum of technologies, not because we want to cover every option, but because we know that the right stack depends on context: your data landscape, your teams and your goals.
We work with the following technologies
Cloud and data platforms
Integration platforms
Data modelling and governance tools
Analytics and storage solutions
How to tackle these projects?
At Claria, we treat architecture as more than just structure. It’s about shaping how data supports your organisation every day across teams, platforms and decisions.
Here’s how we help bring order, clarity and long-term value to your data architecture initiatives:
1. Conduct a current-state architectural assessment
Evaluate the maturity of your existing data architecture, identifying technical debt, siloed data flows and missing standards. Use this to inform a roadmap for future-state design.
2. Define and embed a metamodel and taxonomy
Establish a clear metamodel that outlines how data elements relate to each other. Develop business and technical taxonomies that ensure consistent data definitions across teams and systems.
3. Classify data assets by sensitivity and use case
Incorporate data classification into your design process, enabling better security, governance and compliance alignment. This is essential for supporting GDPR, data sovereignty and lifecycle management.
4. Design a logical and physical data model
Translate business requirements into logical structures and optimise these into physical data models for implementation across your chosen platforms.
5. Establish canonical data models and integration standards
Define and document shared structures for exchanging information between systems. This promotes interoperability and reduces custom development effort.
6. Develop data flow and lineage mapping
Visualise how data moves through your systems, where it is transformed and where it is consumed. This supports data governance, impact analysis and trust in reporting.
7. Incorporate metadata management from the outset
Ensure your architecture supports the capture, use and governance of metadata. This enhances data discoverability and enables better decision-making.
8. Implement governance structures
Create roles, policies and review processes to ensure architectural standards are maintained over time.
Common mistakes made in Data Architecture initiatives
What breaks isn’t always the technology, it’s the approach behind it.
Many data architecture projects start with strong intent but fall short in practice, not because the tools are wrong, but because the foundation lacks alignment with how the organisation actually works. These are some of the issues we see most often when initiatives fail to deliver long-term value:
Focusing only on technology
Effective data architecture is about process, people and culture as much as tools. Overemphasis on tools without stakeholder buy-in leads to failed adoption.
Neglecting governance and standards
Without clear policies and ownership, data quality, security and compliance suffer, regardless of the technical design.
Underestimating integration complexity
Failing to plan for data silos, legacy systems and external sources can cause massive delays or rework.
Designing in isolation
Architecture must align with business objectives. Designing without business context risks building technically perfect, but unused, solutions.
Why choose Claria
In many organisations, data architecture lives in static diagrams and disconnected documentation. The real challenge isn’t knowing what good architecture looks like, it's making it usable, governable and aligned with how people actually work.
At Claria, we work where strategy meets implementation. We collaborate with business and IT leaders to turn abstract designs into working foundations for scale, control and clarity.
Here’s how we approach things differently:
We don’t follow templates, we build for your structure
Your organisation isn’t standard and neither is your architecture. We create designs that reflect the way your teams operate and the systems already in place.
We go beyond data flow, we build governance into the core
From ownership and classification to policies and lineage, we make sure every layer of your architecture supports responsibility and compliance.
We prioritise practical decisions over theoretical frameworks
We’ll guide you through trade-offs, edge cases and legacy constraints, not just ideal models. Because real systems aren’t perfect and neither are the timelines.
We deliver architecture that can evolve
We design with change in mind from new sources and tools to shifting priorities. You won’t need to start over every time something changes.
We keep the complexity manageable
From technology selection to integration patterns, we help you build just enough structure to stay in control without adding unnecessary overhead.
Talk to our Data Architects
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