ETL transforms data before it’s loaded; ELT loads raw data first, then transforms it. We support both based on your tools and needs.
What we help you do
Connect Disparate Systems
Pull in data from apps, databases, APIs, flat files, and third-party services.
Build Cloud Data Warehouses
Set up secure, scalable repositories using Azure Data Lake, Synapse, or SQL.
Clean and Transform Data
Standardise messy data so it’s ready for reporting, AI, or integration.
Automate ETL/ELT Pipelines
Streamline how data flows and updates across environments.
Establish Governance and Access Rules
Ensure the right people have access — and that your data complies with policy.
Who we work with
Deliverables
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System integration map and data flow diagram
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Cloud data warehouse setup (e.g. Azure Synapse)
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ETL/ELT pipelines using Azure Data Factory or Logic Apps
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Data cleaning and transformation scripts
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Metadata dictionary and access control plan
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Integration into analytics dashboards or AI models

Our approach
Low-friction start
We build simple integrations before scaling up.
Azure-native where possible
Keep it efficient, secure, and cost-effective.
Performance-focused
Designed to meet current and future data demands.
Security-first
Your data is encrypted, monitored, and governed.
FAQs
What’s the difference between ETL and ELT?
Can we still access our existing systems during integration?
Yes — our work doesn’t disrupt your operations or live systems.
Do you support real-time or batch data integration?
Both. We’ll help you decide based on the use case and system limits.
Yes — especially when working on analytics or AI projects where visibility matters.
Let's Talk
Better data unlocks better products, decisions, and AI outcomes.
Contact us for a free consultation.