Service area
Data Transformation
Clean, consistent and connected data at scale.
Clean, consistent and connected data at scale
How we turn messy sources into reliable, reusable data assets.
We turn fragmented formatted, siloed and messy datasets into trusted information. We specialise in data transformation pipelines that keep quality, lineage and reuse patterns front and centre so every downstream consumer can rely on the data they receive.
What we offer
The transformation tooling, automation, and governance we implement.
- ETL and ELT delivery using open-source and Microsoft tooling
- Databricks engineering across Delta Live Tables and data lineage workflows so your pipelines coexist with existing platform investments
- Real-time streaming, micro-batch and batch processing patterns
- Data validation, lineage toolsets and auditability of data transformation rules
- Legacy migration, hybrid toolset integration and interoperability across multi-cloud data environments
- Performance tuning and optimisation across compute and storage resources
Technologies & accelerators
Tools we use to accelerate delivery
- Azure Data Factory, Synapse Pipelines and Fabric Dataflows templates for orchestrating ingestion scenarios
- Databricks Delta Live Tables, Unity Catalog and Workflows starter kits that accelerate governed lakehouse delivery
- dbt project scaffolding, modular notebooks and integration with legacy SQL server connectors for consistent transformation logic
- Great Expectations, DBT and Azure Monitor process workflows that embed automated testing, alerting and lineage capture
- Azure DevOps, Data Factory and GitHub Actions CI/CD blueprints that keep deployments auditable across environments
Problems we solve
Bottlenecks and quality issues we remove to keep data flowing.
Manual reconciliation, difficult to explain transformation logic and slow refresh cycles erode confidence in data quality. We streamline pipelines, introduce automated quality gates and embed data lineage tooling to shorten latency and improve trust so analysts and applications receive reliable data when they need it.
How we engage
Our delivery cadence from discovery through optimisation.
- Discover dependencies — Map source systems, integration constraints and data consumers against stakeholder requirements.
- Engineer the flow — Build modular transformations, orchestrate workloads across Databricks Workflows and your existing schedulers and implement observability and data quality checks.
- Optimise & transition — Tune performance, document lineage and empower your team to operate the pipelines.
Why organisations trust us
Evidence of the outcomes we deliver for complex organisational environments.
We have worked to modernise data transformation stacks for healthcare, multi disciplined SMEs and public sector clients, leveraging reusable ingestion blueprints, our favourite technical accelerators and cost management models to deliver predictable, trusted data transformation outcomes.
Need pipelines that just flow?
Work with our engineers to orchestrate cleaner, faster data delivery.
Let’s orchestrate cleaner, faster data delivery—talk with the team about what’s next.Our approach
How we partner
Step 1 Discover context
Clarify goals, understand your current landscape and stakeholders to make sure we are solving the right problem from day one.
Step 2 Design the path
Co-create the architecture, delivery plan and success measures that will deliver durable data capability.
Step 3 Deliver & evolve
Ship value iteratively, embed change and transfer knowledge so your team can sustain momentum.