Twelve systems. Zero shared truth.
CRM, ERP, marketing automation, finance, HR, ops, each with its own data model. Cross-system reporting is a six-week project. Every time.
CRM, ERP, marketing automation, finance, HR: twelve systems, zero shared truth. Cross-domain reports take six weeks. Fix it with a Microsoft Fabric OneLake backbone + unified semantic model. End-to-end customer view in ten weeks.
If half of these sound familiar, this is your fight.
No formal assessment needed, just an honest look at the daily friction.
Cross-domain reports require a manual Excel join every month.
Customer data lives in five systems with five different keys.
Marketing and sales argue about lead attribution because nobody owns the funnel data.
Each business unit has its own BI tool. Three of them are licensed and barely used.
New initiatives die in week one because data integration takes longer than the project itself.
You've never seen a single end-to-end customer view.
Why it happens
Acquisition or org growth
Mergers, decentralised IT or fast hiring left behind a portfolio of overlapping systems.
No central platform
Without a Fabric or OneLake backbone, every integration is point-to-point, and every change ripples.
No shared semantics
No agreed definitions of customer, product, transaction, so cross-domain reporting starts with arguing.
What it costs you
Slow strategic moves
Pricing experiments, market entries, M&A diligence: all stall on data plumbing instead of strategy.
Duplicate spend
Five BI tools, three ETL platforms, two MDM tools: paid for, half-used, none aligned.
AI dead-ends
You can't train a model that needs cross-domain features when those features live in five systems with no joins.
The shortest path from problem to results.
Microsoft-first stack. Belgian and Estonian engineering. Senior team kickoff through delivery to support.
Microsoft Fabric backbone
OneLake as the single source for governed data, with shortcuts to legacy systems instead of full migration day one.
See solutionMaster data strategy
Where master data belongs in your architecture: one canonical record per business entity, with stewards, change workflow and survivorship rules.
See solutionUnified semantic model
A Power BI model with certified definitions across domains, so cross-system questions take minutes, not weeks.
See solutionWhen 11 source systems became one Fabric backbone.
OneLake medallion · 11 sources, one truth
A Walloon manufacturer with 11 source systems and no shared customer view. We built a Microsoft Fabric medallion on OneLake using shortcuts to keep operations running, then migrated incrementally. End-to-end customer view live in week ten. Cross-domain reports now self-service.
Fragmented data is fixable. Let's draw your map.
Free 60-minute architecture call: we'll sketch the shortest path to OneLake.
Common questions, direct answers.
Do we need to migrate all systems to Fabric?
No. OneLake shortcuts let you reference data in Synapse, Snowflake, S3, ADLS, even SQL Server, without copying. You consolidate the SEMANTIC layer first, migration follows when it earns its keep.
What's the difference between Fabric and a traditional warehouse?
Fabric is SaaS lakehouse with separated storage and compute, plus integrated Power BI + AI workloads. Traditional warehouses scale storage AND compute together, which means you over-provision one to satisfy the other.
How long until cross-domain queries become "self-service"?
Ten weeks for first end-to-end view (e.g., customer 360). Twenty weeks for full self-service across three domains. The semantic model and certifications are what enable self-service, not the platform.
What about real-time data?
Microsoft Fabric Real-Time Intelligence (Eventstreams + KQL) handles sub-minute freshness. Most cases don't need it. Daily batch is fine. Reserve real-time for genuine sub-minute SLAs.
How do we avoid creating a new silo (the lakehouse)?
The lakehouse is the integration layer, not a new silo. As long as everything has a Purview classification and lineage, and certified semantic model on top, it's the opposite of a silo.