ETL & Data Pipelines
Automated, observable data pipelines that connect your source systems to your analytics layer. No more manual exports. No more Monday-morning data fixes.
Discuss Your ProjectThe Problem
Your data lives in a dozen places — ERP, CRM, spreadsheets, web APIs, flat files. Getting it all to the right destination, in the right shape, at the right time, with proper error handling, is harder than it looks.
Most SMEs underestimate this. The result: manual exports, Excel-based consolidation, and fragile processes where one missed step breaks an entire month's reporting.
How We Tackle It
We design and build end-to-end data pipelines that automate the full flow from source to analytics layer:
- Source system audit — catalogue every data source, connection method, volume, and refresh frequency
- Architecture design — choose the right pattern: full load vs. incremental, push vs. pull, batch vs. near-real-time
- Pipeline development — build, test, and document each pipeline
- Monitoring setup — error alerts, data quality checks, refresh tracking
- Handover — full documentation and a training session so your team can maintain it
We build pipelines your people can understand — not black boxes that only we can support.
What You Get
- Source-to-target mapping document
- Pipeline architecture diagram
- Fully implemented and tested pipelines
- Data quality validation rules
- Error handling and alerting configuration
- Monitoring dashboard (run history, success/failure rates)
- Operational runbook and documentation
- Training session for your internal team
Tools & Technologies
- Azure Data Factory (primary orchestration)
- Power Query M (transformation, Power BI dataflows)
- Python (custom connectors, API ingestion, complex transformations)
- T-SQL (stored procedures, views)
- Azure Blob Storage / Data Lake (staging layer)
- Microsoft Fabric (modern data platform)
- REST API integration (any source with an API)
Who This Is For
- Companies still doing manual data consolidation — Excel, copy-paste, CSV exports
- Organisations integrating multiple source systems (ERP, CRM, e-commerce, and more)
- Teams that need daily (or more frequent) data refreshes without human intervention
- Projects migrating from on-premises data warehouses to Azure