Data Engineering • Business Intelligence
Enterprise Data & BI Architecture
Pipelines, databases and dashboards that operations can trust.
Overview
This work covers the design and implementation of data pipelines, databases, dashboards and reporting ecosystems that support operational decision-making.
The Challenge
Reporting demand grows faster than the data foundation. Dashboards are requested before sources are reliable, definitions are agreed, or pipelines are owned. The result is a reporting layer that cannot be trusted under pressure.
The Approach
The architecture was treated as a sequence: sources, storage, transformation, semantic definitions, then visualisation. SQL, Azure and Microsoft Fabric were used where they fit the organisation’s existing Microsoft estate, with Power BI as the decision surface rather than the system of record.
The Solution
Data pipelines, databases and dashboards were designed as one reporting ecosystem. Operational decision-making is supported by a governed path from source data to Power BI, rather than by disconnected extracts.
Key Capabilities
- SQL
- Azure
- Microsoft Fabric
- Power BI
- Data Engineering
Technology
Architecture / workflow
Source systems
Pipelines
SQL / Fabric
Semantic model
Power BI
Dashboards consume a semantic model. They are not the data warehouse.
Screenshots
Enterprise Data & BI Architecture · desktop
Data Engineering • Business Intelligence
Enterprise Data & BI Architecture
SQL
Azure
Microsoft Fabric
Power BI
Data Engineering
Interface preview — configurable screenshot source. Not a live capture of the production application.
Enterprise Data & BI Architecture · detail
SQL
Azure
Microsoft Fabric
Power BI
Placeholder close-up. Replace with a configurable screenshot when available.
Impact / Outcomes
Operational reporting sits on a designed data path—pipelines, databases and dashboards—rather than on a growing pile of extracts.
Lessons
Business intelligence quality is determined before the first chart is drawn. If the pipeline and definitions are weak, no dashboard polish will save the decision.
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Next step
Discuss a similar problem.
If this work is close to a challenge you are facing, we can start with the process, the data and the decision—not with a tool.