Data Engineering & Analytics
Build Trusted Data Foundations for Better Decisions.
We help organisations consolidate, govern and activate their data so that leaders, analysts and AI systems can rely on it.
Challenges
Business challenges we address
- Data siloed across systems and spreadsheets
- Inconsistent reporting and conflicting numbers
- Slow, manual data preparation
- Data not ready for AI initiatives
Deliverables
Typical engagement deliverables
- Reference data architecture
- Automated, monitored pipelines
- Governed semantic models and dashboards
- Data quality and lineage controls
Capabilities
What we deliver
- Data platform strategy
- Data architecture
- Data ingestion and ETL/ELT
- Data pipeline development
- Data warehouses and lakehouses
- Microsoft Fabric implementation
- Analytics and Power BI
- Data quality and governance
- Data migrations
- Real-time analytics
- Operational analytics
Reference architecture
From raw data to intelligence
Data Sources
Ingestion
Transformation
Storage
Governance
Analytics & AI
Technologies
Applicable technologies
Microsoft FabricAzure Data FactoryAzure DatabricksApache SparkSQLPower BI
Use cases
Industry use cases
- Attendance and learner performance analytics
- Health data consolidation and reporting
- Financial market data platforms
Our engagement process
- 1
Discover
Understand business goals, challenges and requirements.
- 2
Assess
Evaluate systems, data, readiness and risks.
- 3
Design
Define architecture, delivery roadmap and success measures.
- 4
Build
Engineer, integrate and validate the solution.
- 5
Deploy
Operationalise securely and prepare teams for adoption.
- 6
Optimise
Monitor outcomes, improve performance and scale.
Have a Technology Challenge Worth Solving?
Let's explore how software engineering, data and AI can help your organisation innovate, operate more efficiently and create lasting value.