Ungoverned workspaces
Fabric workspaces are created without naming, access or lifecycle standards.
Microsoft data platform
One data platform instead of five tools duct-taped together.
Fabric brings data engineering, warehousing, real-time analytics and Power BI into a single governed platform on OneLake. We implement it so your data lives in one place with consistent governance, rather than copied across a dozen systems that never quite agree. Especially compelling if you're already invested in Microsoft.
Discuss Microsoft Fabric
Architecture
flowchart LR
SRC[Source Systems] --> INGD[Ingestion]
INGD --> LAKE[OneLake / Lakehouse]
LAKE --> TRANS[Transform and Model]
TRANS --> WH[Warehouse]
WH --> BI[Power BI]
WH --> AIRAG[RAG / AI]
GOV[Governance and Access] -. controls .-> LAKE
- Customer SSN: 512-88-xxxx
- Card ending 4471
- Home address on file
- Health record ID: HR-2291
Business challenges
Microsoft Fabric challenges we solve.
Every recommendation starts with business pressure, technical risk and the operating model required after launch.
Disconnected pipelines
Data movement between OneLake, Power BI and source systems is not consistently designed.
Unclear analytics ownership
Reports and datasets are created without a clear owner or refresh strategy.
Solution overview
Microsoft Fabric designed for production readiness.
We implement it so your data lives in one place with consistent governance, rather than copied across a dozen systems that never quite agree. Especially compelling if you're already invested in Microsoft.
Fabric architecture
Data engineering, warehousing and analytics unified on OneLake instead of copied across systems.
Workspace governance
Consistent governance applied across every Fabric workspace.
Data pipelines
Pipelines that keep data in one place with a single source of truth.
Analytics enablement
Power BI and real-time analytics built on the same governed foundation.
Architecture model
A practical delivery architecture before implementation begins.
We define the target operating model, controls, integration points and ownership path before building, so the solution can be supported after launch.
CloudevTech
Enterprise delivery model
01
Discover
02
Architect
03
Implement
04
Validate
05
Operate
Our approach
Structured delivery from discovery to operational handover.
Every engagement is shaped around the service goal, current constraints and the operating model your team needs after launch.
Assess current analytics setup
Review existing reporting and data movement.
Design workspace governance
Define naming, access and lifecycle standards for Fabric workspaces.
Build pipelines
Implement OneLake and Data Factory pipelines.
Enable analytics
Connect Power BI and support adoption across teams.
Business benefits
Outcomes designed for decision makers and delivery teams.
Benefits are framed around measurable improvement, operating confidence and reduced delivery risk.
Governed workspace structure
Workspace standards keep Fabric organized as usage grows.
Designed data pipelines
OneLake and Data Factory pipelines follow a consistent, documented pattern.
Analytics enablement
Reports and datasets have clear ownership and a defined refresh strategy.
Technology stack
Implemented with proven platforms and tools.
Technology choices are confirmed during discovery, with a preference for reliable, maintainable platforms your team can support.
Microsoft Fabric
OneLake
Power BI
Data Factory
Lakehouse
FAQ
Common questions before engagement.
Short answers to common planning questions for Microsoft Fabric.
Is Fabric right if we're not a Microsoft shop?
It's strongest in a Microsoft ecosystem. Elsewhere we'll weigh it against alternatives honestly.
Can it replace our current stack?
Often it consolidates several tools — we assess what's worth migrating and what isn't.
Enterprise consultation
Book a consultation