Microsoft Fabric & Power BI
The infrastructure investment has been made. The licences are paid. The data is somewhere in the Azure environment. The dashboard the business actually needs still doesn't exist. That's where we come in.
What we hear from operators
The problems we solve
The data platform exists. The insights don't.
After an Azure migration or a cloud data warehouse implementation, most organisations have infrastructure — blob storage, Azure SQL, maybe a Synapse workspace that nobody uses. The data is in the cloud. But nobody built the semantic layer, the transformation logic, or the dashboards on top of it. The IT team got the infrastructure running and handed it over. The business is still waiting for something useful.
Power BI reports are slow and nobody trusts the numbers
Import mode Power BI reports refresh overnight. Users arrive in the morning and the numbers are already 8 hours old. Direct Query is too slow on large tables. The semantic model has measures defined inconsistently across different reports — the same KPI returns different numbers depending on which report you open. Trust collapses fast when that happens, and it's hard to rebuild.
SAP and ERP data isn't connected to the analytics layer
The ERP is the system of record. The analytics platform is where decisions happen. In most Microsoft environments we walk into, these two things are connected by a nightly export to a shared drive, or by an Azure Data Factory pipeline that breaks whenever SAP is patched. The integration is fragile, undocumented, and owned by nobody.
By market
Microsoft Fabric — market-specific pages
Each page below covers what microsoft fabric & power bi looks like specifically in that market — the local ERP landscape, compliance context, and the operational patterns we actually see there.
Singapore & Malaysia
United Kingdom
North America
By industry
Microsoft Fabric — industry-specific pages
How microsoft fabric & power bi applies to the specific systems, metrics, and operational challenges of each vertical.
Manufacturing
Most manufacturing plants we walk into have four or five systems that don't talk to each other: SAP or Oracle for production orders, a separate MES for floor execution, a quality system that's often standalone, and spreadsheets filling every gap in between.
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FMCG & Retail
FMCG and retail data problems concentrate at two points: the demand signal and the shelf.
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Packaging
Packaging plants sit at the intersection of manufacturing analytics complexity and FMCG demand volatility.
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Logistics & Supply Chain
Logistics operations in the GCC, India, and Southeast Asia share a common data challenge: high transactional volume, multi-party execution (3PL, 4PL, last-mile carriers), and a fragmented visibility picture.
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EPC (Engineering, Procurement & Construction)
EPC data environments are uniquely complex: long project timelines, multi-currency and multi-jurisdiction reporting, complex contractual structures (lump sum, reimbursable, target cost), and a fundamental tension between the project management system (Primavera, MS Project) and the cost management system (Oracle, SAP PS).
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Technology stack
Related services
Start with a conversation, not a proposal
First call is 45 minutes. No deck. We ask about your systems, your team, and your most pressing operational problem. You get a clear view of where the gap is and what closing it looks like.