Data Engineering

Build the trusted data foundation for reporting, analytics and AI

AI, automation and reporting only work when data is trusted, connected and governed. We help organisations unify fragmented data sources, modernise reporting, build Microsoft Fabric or Databricks foundations, and create reusable data products that support better decisions and future AI use cases.

Microsoft Solutions Partner Data & AI Microsoft Solutions Partner Digital & App Innovation
Common outcomes

Replace fragmented reporting with governed data products

Replace manual reporting, disconnected data sources and inconsistent definitions with governed data products your teams can use for reporting, analytics, automation and AI.

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Common outcomes

Data foundations your teams can actually use

Trusted reporting layer

Reliable data for leadership and operational teams.

Less manual preparation

Automated ingestion, validation, transformation and reporting flows.

Better ownership

Clearer data quality, governance, definitions and accountability.

AI-ready foundations

Microsoft Fabric or Databricks platforms that support analytics and future AI use cases.

Proof from similar work

Trusted data platforms built for reporting, analytics and AI

Selected examples of how we have modernised reporting, connected fragmented financial data and delivered reliable data processing at enterprise scale.

Charity and nonprofit operations

Financial reporting modernised with Microsoft Fabric

Situation
An organisation wanted to evaluate Microsoft Fabric as its future data and analytics platform while preserving existing reporting operations and creating a route to broader multi-source integration.

Solution
We delivered a Fabric proof of value with automated ingestion, Bronze-Silver-Gold lakehouse layers, a Fabric Data Warehouse, Power BI reporting, development-to-production environments and deployment pipelines.

Benefits

  • Validated Fabric as a future-state analytics platform.
  • Delivered trusted financial reporting from a unified data foundation.
  • Created a practical roadmap for additional systems and wider adoption.
Read the case study

Real estate investment

Financial data integration across portfolio companies

Situation
A European real estate investment organisation needed to integrate financial data from portfolio companies and service providers. Files arrived in different formats, data quality checks were manual, and reporting depended on disconnected systems.

Solution
We built secure ingestion, validation, transformation and integration workflows on Azure and Databricks, supported by a business-facing portal for controlled file submission, review and exception handling.

Benefits

  • Reduced manual file handling and repeated data mapping.
  • Improved data quality before information reached accounting and reporting systems.
  • Created a reusable integration foundation for new portfolio companies and service providers.

UK energy market

Data platform processing more than one billion events daily

Situation
A business-critical electricity settlement platform needed to process and reconcile more than one billion events each day while meeting strict requirements for accuracy, timeliness and continuous operation.

Solution
We delivered a cloud-native Azure platform using scalable data pipelines, event-driven integration and microservices to ingest, transform and aggregate market data at national scale.

Benefits

  • Processes more than one billion events daily with capacity to grow.
  • Supports continuous, resilient operation for critical settlement workflows.
  • Established a foundation for predictive analytics and machine-learning use cases.
Read the case study