"We have reports, but people still ask for the Excel behind them."
The issue is rarely the visual. It is usually trust, definitions, refresh logic or missing ownership.
Microsoft BI, data platforms and AI
Make business numbers hold up under pressure.
When a report is challenged in a meeting, the answer should not be another spreadsheet export. We help leadership, finance and operations teams turn scattered data into Power BI, planning workflows and AI-ready models they can explain.
Working since
2020
Delivery style
Owner-led
Core stack
Microsoft
Why clients call us
We are not trying to be the largest BI consultancy in the room.
We are built for the projects where attention matters. The kind where the CFO wants one margin number, operations needs daily visibility, IT needs something maintainable, and nobody has time for a six-month discovery theatre.
Our edge is senior attention, direct communication and practical engineering. Small enough to care about every project, experienced enough to work with enterprise complexity.
Common starting points
The work usually starts with a sentence like this.
These are the situations where a BI project becomes business-critical. They are also the moments where a clean dashboard alone is not enough.
"Month-end takes too long, and nobody sees the problem early enough."
We make finance, sales and operational signals visible before the post-mortem starts.
"Planning lives in files, approvals live in emails."
Power Apps and Power Automate can turn planning and write-back into a controlled business workflow.
"We want AI, but our data definitions are not ready."
Good NLQ and agents need a semantic layer, permissions and data quality before the chatbot gets clever.
What changes after the work
Fewer arguments about data. Faster answers. Better follow-through.
We work across the full BI chain, but the outcome should be simple: people know where numbers come from, what they mean and what to do next.
Leadership can defend the number
Power BI reports, KPI logic and semantic models that survive follow-up questions instead of creating new ones.
IT can operate the platform
Azure and SQL-based foundations, integrations and data layers that are documented, monitored and built for change.
Business can act inside the system
Write-back, approvals, planning and master-data workflows that move work out of attachments and private files.
AI has something reliable to stand on
Natural language query and agent ideas connected to curated definitions instead of raw tables nobody fully trusts.
Delivery method
Enough structure to stay calm. Enough pace to keep momentum.
We do not start by drawing the perfect architecture in isolation. We start with the decisions people are trying to make, then work backwards into data, definitions, platform and workflow.
The first useful release should prove the direction with real users. After that, we scale deliberately.
- ListenStakeholder interviews, pain-point map, current reports, KPI disagreements and priority decisions.
- ShapeArchitecture, data model, security, governance and release plan, written in language business and IT can both follow.
- ProveA focused release with real data and real users, so value and risk become visible early.
- ScaleIntegrations, transformations, semantic models, Power BI reports and workflow surfaces in controlled increments.
- StayTraining, documentation, support routines and improvement after go-live, because BI never really ends.
Technology stack
Microsoft where it is strong. Databricks and Fabric where they earn their place.
We do not sell a tool religion. We choose the stack based on data volume, team maturity, governance, cost and how the system will be operated after launch.
AZMicrosoft Azure
Infrastructure, identity, storage, integration and scalable analytics services.
SQLSQL Server / Azure SQL
Reliable relational foundations for enterprise reporting and business applications.
BIPower BI
Governed semantic models, reports, apps, dashboards and executive analytics.
PAPower Platform
Power Apps and Power Automate workflows for write-back and process control.
ADFAzure Data Factory
Managed ingestion, orchestration, scheduling, monitoring and integration flows.
DatabricksLakehouse, data engineering and advanced analytics when scale or workload complexity requires it.
FBMicrosoft Fabric
Used carefully for Fabric-native scenarios where the maturity and fit are clear.
AILLM / NLQ / agents
AI interfaces connected to curated business definitions and governed data context.
Selected references
Enterprise BI work, practical finance workflows and business applications.
We keep public reference visibility conservative. The point is not logo volume, but the mix: demanding data work, real business users and systems that have to keep working.
Chill Out Home
Start the conversation
Bring us the messy version first.
You do not need a perfect brief. Tell us what feels slow, fragile or hard to trust in reporting, planning, workflows or AI readiness. We will help turn that into a sensible next step.
Company details
rockaBI Kft.
H-2053 Herceghalom, Kiserdő út 10. 1. em. 8.
reg: 13-09-209770
tax/vat: 28981105-2-13 / HU28981105
Contact
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