BI assessment and roadmap
Stakeholder interviews, KPI review, reporting inventory, platform maturity, quick wins and a realistic delivery roadmap.
Enterprise data, BI and AI
Build BI people can question, explain and keep using.
A useful BI system does not end at a dashboard. It has to connect source systems, preserve business meaning, make ownership clear and give people a way to act when the numbers change.
Capabilities
Own the whole chain, or fix the part where trust breaks.
If integration, modelling, governance, visualization or adoption is weak, people go back to manual work. We can deliver the full system or reinforce the layer that is slowing decisions down.
Enterprise data platform
Azure architecture, SQL Server, Azure SQL, data warehouse and lakehouse design with security, cost and maintainability in mind.
Data integration
API, database, file and application integrations using reliable ETL/ELT patterns, orchestration and monitoring.
Medallion architecture
Bronze, Silver and Gold layer design for traceable ingestion, validated business entities and consumption-ready analytical models.
Semantic layer and modelling
Dimensional models, calculation standards, reusable measures, ownership rules and governed business definitions.
Power BI visualization
Executive dashboards, operational reporting, report UX, workspace governance, apps, deployment routines and adoption support.
Workflow management
Power Apps and Power Automate solutions for planning, approvals, master data maintenance and controlled write-back.
AI on trusted data
Natural language query, LLM-based analytics assistants and agentic components grounded in curated semantic context.
Operations and support
Monitoring, documentation, change handling, support routines and continuous improvement for new or inherited systems.
Delivery approach
Business leaders see the why. IT sees the how.
We combine business analysis, BI architecture, data engineering, Power BI, Power Platform and project management in one delivery rhythm. Stakeholders see what is changing and why; technical teams get assets they can maintain.
- DiscoverInterview decision owners, map pain points, clarify KPIs and identify where trust breaks.
- DesignDefine architecture, integration patterns, data model, security, governance and release plan.
- ProveBuild a thin slice on real data to validate value, data quality, UX and technical assumptions early.
- ScaleDeliver integrations, transformations, semantic models, reports and workflows in controlled increments.
- OperateTrain users, document ownership, monitor quality and improve the system after go-live.
Technology stack
Microsoft-first, not tool-first.
We work primarily with Microsoft Azure, SQL Server, Azure SQL, Power BI, Power Apps and Power Automate. Databricks and Microsoft Fabric are included when the workload, governance model and maturity make them the right choice.
AZMicrosoft Azure
Cloud infrastructure, identity, storage, data services and scalable analytics architecture.
SQLSQL Server / Azure SQL
Relational foundations for trusted reporting, business applications and governed storage.
ADFAzure Data Factory
Managed ingestion, orchestration, monitoring and repeatable data movement.
DatabricksLakehouse, advanced data engineering and analytics workloads where scale justifies it.
BIPower BI
Semantic models, dashboards, apps, reports and enterprise reporting governance.
PAPower Platform
Power Apps and Power Automate for write-back, approvals and process control.
FBMicrosoft Fabric
Fabric-native analytics scenarios where platform maturity and business fit are clear.
AILLM / NLQ / agents
AI interfaces grounded in curated data, business definitions and permission-aware context.
Selected BI references
Experience with complex organizations and demanding decision environments.
Next step
Start with a focused BI assessment.
We can review your reporting landscape, data platform maturity, semantic layer, workflow needs or AI readiness and propose a practical roadmap.