Are you running a business with multiple entities, subsidiaries, or departments? Most organisations are drowning in fragmented data across different systems, and it's costing them serious money.
Here's the reality: traditional approaches to multi-entity reporting are broken. Finance teams spend weeks pulling data from different ERP systems (Sage, BC, NAV) into spreadsheets. Sales reports don't match marketing dashboards. Regional managers work from completely different versions of "the truth." Sound familiar?
Multi-entity reporting means getting one version of the truth from all your business units without the usual data nightmare. Microsoft Fabric solves this by unifying everything into OneLake - one data repository that actually works.
Microsoft Fabric is the next-generation data platform that brings together data engineering, data science, real-time analytics, and business intelligence in a single SaaS solution. It's built as a unified platform that eliminates the complexity of stitching together multiple tools.
The difference matters. Traditional data platforms force you to stitch together multiple tools, each with its own licensing, governance, and maintenance requirements. Microsoft Fabric eliminates this complexity by providing everything you need in one integrated solution.
Why Microsoft Fabric Beats Traditional Data Warehouses
Most businesses hit the same wall with traditional data warehouses: they promise unified reporting but deliver fragmented complexity. You end up with expensive systems that can't adapt to real-world business needs.
Here's what actually happens: IT builds a beautiful data warehouse. Finance loves the initial reports. Then sales wants customer segmentation. Marketing needs campaign analytics. Regional teams want local insights. Each request means custom development, lengthy approval processes, and mounting costs.
Microsoft Fabric solves the fundamental problem - it's designed for business agility, not just data storage.
Single Source of Truth: OneLake unifies data across all sources without hunting through different systems. No more Excel spreadsheets to reconcile conflicting reports or emergency meetings to figure out which numbers are actually correct.
Real-Time Integration: Deep Power BI integration updates reports directly from trusted data pipelines. When your sales team closes a deal, finance sees it immediately. When inventory levels change, procurement gets near real-time visibility.
True Scalability: Handles operational reporting to advanced AI in Microsoft Fabric workloads cost-effectively. Scale from hundreds of transactions to millions without rebuilding your entire architecture or facing exponential cost increases.
Unified Governance: Built-in security, compliance, and data lineage tracking. Know where your data comes from, who's accessed it, and how it's been transformed - essential for regulatory compliance and audit requirements.
Three Lakehouse Design Patterns for Multi-Entity Reporting
1) Centralised Lakehouse
Best when finance and IT are centralised. All companies land data in one place; we standardise it and present a single model with role-based views.
- Reporting: One set of numbers, instant consolidated KPIs with drill-downs by entity.
- Control: Consistent logic and tight governance in one hub.
- Trade-off: Fastest to value, but less flexibility for regional variations.
2) Federated Lakehouses
Best for autonomous regions/entities. Each company manages its own data and group finance reads a standardised view across them for consolidation.
- Reporting: Clean group roll-up without manual spreadsheets, local teams keep local reporting schedule
- Control: Shared data cleansing rules so numbers match across companies.
- Trade-off: Needs more coordination, best for bigger or global setups.
3) Hybrid (Most Common)
Best for balancing control and agility. Core finance sits centrally for the official numbers and local teams keep their own analytics where it adds value, based off shared models.
- Reporting: One trusted group P&L plus clear, local views
- Control: Group sets finance rules (FX, eliminations, month end close) but local teams have freedom to do operational analysis
- Trade-off: Decide up front what’s central vs local but remember simple guardrails keep it tidy.
Microsoft Fabric Data Sharing: Security That Works
Microsoft Fabric data sharing follows "governed by default, open by design" principles. Traditional perimeter security doesn't work in cloud-first environments.
Why traditional security fails: Most businesses still think in terms of network perimeters and VPNs. But when your data lives in the cloud and users work from anywhere, you need a different approach. Microsoft Fabric addresses this with identity-based security that travels with your data.
What "governed by default" means: Every piece of data has permissions attached from creation. No orphaned files. No accidental data exposure. No wondering who can see what.
OneLake Security Model
Workspace Permissions:
- Admin: Full control including member management
- Member: Can manage items and write data
- Contributor: Write access without role management
- Viewer: Read-only unless explicitly granted more access
Advanced Control: SQL Analytics Endpoint offers User Identity mode (OneLake roles) or Delegated Identity mode (SQL-level permissions with Row-Level Security).
Row-Level Security in practice: Your sales director sees all regions. Regional managers see only their territory. Individual reps see only their accounts. Same report, different data based on who's looking.
Compliance Built-In
Microsoft Purview integration provides end-to-end data lineage, sensitivity labels, governance recommendations, and legal hold capabilities. Microsoft Fabric licensing includes Purview governance at no additional cost.
Data lineage tracking: See exactly where every piece of data came from and how it's been transformed. Essential when auditors ask questions or when data quality issues emerge. No more detective work to trace problems back to their source.
Automated compliance: Sensitivity labels automatically classify data based on content. Personal information gets flagged. Financial data gets extra protection. Regulatory requirements get built into the workflow, not bolted on afterwards.
Implementation Timeline
Month 1: Data discovery, architecture planning, and initial lakehouse setup
Month 2-3: Build reports, test security, and configure governance
Month 4-6: Full rollout with user training and adoption
Cost reality: Microsoft Fabric licensing varies based on capacity and features required. Budget 6-12 months for full deployment plus implementation and training costs.
What usually goes wrong: Most businesses underestimate data quality issues in their existing systems. Plan extra time for data cleansing. User training takes longer than expected - people resist change even when the new system is better.
Success factors: Get executive buy-in early. Identify data champions in each business unit. Start with a pilot group before rolling out company-wide. Have realistic expectations about timelines and invest properly in change management.
When to Choose Microsoft Fabric
Use Microsoft Fabric for:
- Multiple entities with complex reporting requirements
- Existing Microsoft 365 and Power BI environments
- AI in Microsoft Fabric capabilities without complex integration
Look elsewhere for:
- Simple reporting needs or small data volumes – a standalone Power BI may be sufficient; we can help you decide.
- Your existing data platform is heavily invested in non-Microsoft technology – Do you need to reinvent the wheel? Perhaps you do we can help review your existing data platform.
Common Implementation Pitfalls
Over-engineering from day one: Don't try to solve every possible future requirement in your initial design. Start with core reporting needs and expand incrementally.
Ignoring data quality: Your new lakehouse won't fix bad data - it'll just make bad data more visible. Address data quality issues before migration, not after.
Underestimating training needs: Users need more than a quick demo. Plan comprehensive training programmes and ongoing support for adoption success.
Skipping governance: Set up security, access controls, and data policies before loading data. It's much harder to retrofit governance after go-live.
Ready to Transform Your Multi-Entity Reporting?
Don't let fragmented data hold your business back. Microsoft Fabric can unify your entities and deliver the insights you need - but only with proper implementation.
Get it right from the start. Our team has deployed dozens of Microsoft Fabric implementations and knows exactly what works (and what doesn't). We'll design the right lakehouse pattern for your business and ensure your data governance is bulletproof from day one.
Book a consultation to discuss your multi-entity reporting challenges. We'll show you exactly how Microsoft Fabric can solve your data problems - no corporate fluff, just practical solutions.
Contact TSG today to start your Microsoft Fabric journey.
Frequently Asked Questions
What is Microsoft Fabric? Fabric's data platform is unified, combining data engineering, data science, real-time analytics, and business intelligence in one SaaS solution.
What is Microsoft Fabric lakehouse? It combines data lakes and warehouses without the usual headaches. Everything goes into OneLake - no more hunting through different systems or wasting time moving data between fragmented tools.
Is Microsoft Fabric replacing Power BI? No. Power BI is integrated within Microsoft Fabric as the analytics layer. Think of Fabric as the engine, Power BI as the dashboard.
