Services → Data Architecture & Strategy
Data Architecture & Strategy

The foundation every data initiative is built on

A modern data architecture is not just a technical upgrade — it is the backbone for every analytics, BI, and AI initiative in your organisation. We design architectures that are scalable, trustworthy, and built to last.

Cloud Architecture Data Strategy Governance Lakehouse Design Migration Planning
Modern Data Architecture — Click a layer to explore
Consumption Layer
Power BI · Tableau · Looker · REST APIs · ML Models · Data Products
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Semantic Layer
dbt Semantic Layer · Cube · AtScale · Metrics Store
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Transformation Layer
dbt · Apache Spark · Apache Flink · AWS Glue · Apache Beam
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Orchestration Layer
Apache Airflow · Prefect · Dagster
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Storage Layer
Snowflake · BigQuery · Redshift · Azure Synapse · Delta Lake · Apache Iceberg
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Data Quality & Observability
Great Expectations · Soda · dbt Tests · OpenLineage · Prometheus · Grafana · Datadog
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Governance & Security
Apache Atlas · AWS Lake Formation · Azure Purview · RBAC · Data Masking
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Ingestion Layer
Kafka · Airbyte · Fivetran · Debezium · AWS Kinesis · APIs
Is This You?

Signs your data architecture needs attention

These are the most common symptoms we see in organisations before they invest in a proper data architecture. If more than two of these sound familiar, it is time to act.

Data scattered across systems
Your data lives in spreadsheets, SaaS tools, legacy databases, and cloud platforms with no single source of truth and no clear way to connect them.
Slow, manual reporting pipelines
Reports take days to produce, require manual intervention, and are often out of date before they reach the person who needs them.
Nobody trusts the dashboards
Teams run their own spreadsheets because they have stopped trusting the BI tools. Decisions are made on gut feel because the data feels unreliable.
No governance or data lineage
Nobody knows where the data came from, who changed it, or whether it is compliant with internal policies or regulatory requirements.
AI initiatives stuck in experiments
Your team wants to build ML models and AI systems but the data foundation is not ready — leading to failed pilots and frustrated data scientists.
Infrastructure costs spiralling
Cloud bills are growing faster than your data usage. Poorly designed pipelines and unoptimised storage are costing more than they should.
The Difference We Make

Before Cybryne vs After Cybryne

A well-designed data architecture changes how your entire organisation operates — not just the data team.

Without a proper architecture
✗Data engineers spend 80% of their time fixing broken pipelines
✗Reports take 3 to 5 days to produce and are often wrong
✗No visibility into data lineage or transformation history
✗Every new data source requires weeks of custom engineering
✗Compliance and audit requests are painful and manual
✗Cloud costs grow with no clear explanation or control
With Cybryne's architecture
✓Pipelines are monitored and self-healing with minimal manual intervention
✓Dashboards refresh automatically with trusted, validated data
✓Full data lineage, ownership, and audit trail built in from day one
✓New data sources onboarded in hours using standardised patterns
✓Compliance reports generated automatically on demand
✓Infrastructure costs optimised with FinOps best practices built in
Our Approach

Strategy led. Engineering backed.

Every architecture engagement follows the same four-step process — designed to de-risk delivery and ensure the outcome matches the business objective.

01
Discover & Assess
We assess your existing data sources, transformation processes, cloud infrastructure, governance maturity, and business goals — identifying gaps and opportunities before writing a single line of code.
02
Architect & Plan
We design your target state architecture including storage layers, governance frameworks, and cloud platform choices — with a roadmap that prioritises high-value, low-risk milestones.
03
Validate & Build
Before full rollout we run a proof of value to validate alignment with your operational, compliance, and performance requirements. Then we build and scale.
04
Optimise & Evolve
Your architecture is not static. We continuously refine performance, query execution, infrastructure costs, lineage, and governance so the platform evolves as you grow.
What We Deliver

Exactly what you get from this engagement

We do not deliver vague recommendations. Every architecture engagement produces specific, documented, production-ready outputs.

Strategy & Design
Cloud data architecture design for AWS, Azure, and GCP including hybrid and multi-cloud
Data warehouse, data lake, and lakehouse architecture blueprints
Dimensional modelling, Data Vault modelling, and semantic layer design
Data platform strategy document and migration planning roadmap
Governance framework covering policies, lineage, metadata, and RBAC
Engineering & Integration
Modern ETL and ELT pipelines using Airflow, dbt, and native cloud tools
Batch and streaming data pipeline implementation
API integrations, partner system ingestion, and event-based architectures
MLOps foundation setup, feature store design, and deployment orchestration
Infrastructure as code for all provisioned resources
Governance & Optimisation
Data governance and compliance models aligned to your regulatory requirements
Data quality frameworks with automated validations and alerting
Performance optimisation, FinOps recommendations, and storage tiering
Monitoring, observability dashboards, alerts, and incident workflows
Full documentation and knowledge transfer to your internal team
Related Services

Architecture is just the beginning

02
Data Engineering & Infrastructure
Once the architecture is designed, we build and maintain the pipelines and data systems that power it.
Explore Data Engineering →
03
Analytics & Business Intelligence
With a trusted architecture in place, we build the analytics and BI layer that turns your data into decisions.
Explore Analytics & BI →
04
Applied AI & Machine Learning
A solid data architecture is the prerequisite for production-ready AI. We build the foundation and the models on top of it.
Explore Applied AI →
Get Started

Ready to build a data architecture
your business can rely on?

Tell us about your current data environment and we will give you an honest assessment of what needs to change and how we would approach it.

Schedule Free Consultation →
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