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Bring your data and analytics together in Microsoft Fabric

We help organisations plan and implement Microsoft Fabric across OneLake, Lakehouse, Data Factory, Data Engineering, Data Warehouse, Power BI and Real-Time Intelligence. Practical architecture for trusted analytics, reporting and AI-ready data platforms.

Microsoft Fabric works best when architecture, governance and reporting are designed together

Unified Analytics Platform

Microsoft Fabric brings together data engineering, data integration, warehousing, real-time intelligence and Power BI into a unified analytics platform. The opportunity is significant, but value depends on designing the right data architecture, security model, workspace structure and semantic layer from the start.

Synenza helps organisations adopt Microsoft Fabric in a practical way. We focus on OneLake, Lakehouse architecture, Data Factory pipelines, semantic models, Power BI reporting, governance, cost awareness and the foundations needed for analytics, AI, Copilot and business decision-making.

What we deliver

Built for the work — not for the deck.

OneLake

OneLake and Fabric architecture

Design a practical Microsoft Fabric architecture across OneLake, workspaces, lakehouses, warehouses, shortcuts, domains, security and data ownership models.

Engineering

Fabric data engineering

Build reliable data engineering patterns using Lakehouse, Delta tables, notebooks, pipelines and reusable transformation logic that supports analytics and downstream reporting.

Factory

Data Factory and pipeline design

Create ingestion and orchestration patterns using Data Factory, dataflows, pipelines and connectors to bring data from business systems into Fabric responsibly.

Warehouse

Data warehouse and lakehouse modelling

Design lakehouse and warehouse structures that support governed reporting, dimensional modelling, analytical workloads and future platform growth.

Power BI

Power BI semantic models and reporting

Create trusted semantic models, measures, dashboards and reports that provide consistent definitions and improve confidence in business intelligence.

Real-Time

Real-Time Intelligence and operational insights

Explore Real-Time Intelligence patterns for streaming data, events, operational monitoring, telemetry and time-sensitive insights where the business needs faster action.

How we work

A measured, honest path from idea to production.

01

Understand

Review your current data sources, reporting needs, analytics pain points, governance requirements, Microsoft licensing and existing platform landscape.

02

Architect

Define the right Microsoft Fabric architecture across OneLake, Lakehouse, Warehouse, Data Factory, Power BI, security, workspaces and governance.

03

Deliver

Build the data platform foundation, ingestion patterns, transformation layers, semantic models and reporting experiences using maintainable delivery practices.

04

Enable

Support adoption with documentation, governance guidance, operating practices, cost awareness and a roadmap for continuous improvement.

Use Cases

Common business scenarios.

Power BI and semantic model modernisation

Improve existing Power BI environments by creating trusted semantic models, consistent measures, governed datasets and clearer reporting structures in Microsoft Fabric.

Data platform consolidation

Bring scattered data sources into a more unified Fabric architecture using OneLake, Lakehouse, Data Factory and governed data modelling patterns.

AI-ready analytics foundation

Prepare data foundations for Microsoft Copilot, AI agents, knowledge assistants and advanced analytics by improving structure, quality, access and governance.

Outcomes you can defend

What good looks like.

  • A practical Microsoft Fabric architecture aligned to business reporting, analytics and AI goals.
  • Improved data foundations across OneLake, Lakehouse, Warehouse, Data Factory and Power BI.
  • Trusted semantic models and reporting layers that support consistent business definitions.
  • Better governance across workspaces, data ownership, access, sensitivity and platform usage.
  • A clearer pathway from raw data to analytics, dashboards, AI use cases and operational insights.
  • A roadmap for scaling Microsoft Fabric safely across teams, domains and business functions.
Frequently asked

The questions clients ask first.

What is Microsoft Fabric used for?
Microsoft Fabric is used for data integration, data engineering, data warehousing, real-time intelligence, data science and Power BI reporting in a unified analytics platform.
How does OneLake fit into Microsoft Fabric?
OneLake is the central data lake for Microsoft Fabric. It provides a single place for analytics data and supports lakehouse, warehouse, reporting and AI-ready data patterns.
Can Synenza help migrate existing Power BI solutions to Microsoft Fabric?
Yes. Synenza can review existing Power BI reports, datasets, dataflows and semantic models, then design a practical path to modernise reporting using Microsoft Fabric capabilities.
Do we need Microsoft Fabric if we already use Azure Synapse or Power BI?
It depends on your current architecture, data volumes, reporting needs, governance requirements and future roadmap. Synenza can help assess whether Microsoft Fabric is the right fit and where it adds value.
Can Microsoft Fabric support AI and Copilot use cases?
Yes. Microsoft Fabric can help prepare governed, structured and accessible data foundations for AI, Microsoft Copilot, AI agents, knowledge assistants and advanced analytics scenarios.
How do you manage governance in Microsoft Fabric?
Fabric governance should consider workspaces, domains, roles, permissions, sensitivity labels, data ownership, lifecycle management, semantic models, monitoring and cost controls.

Let's scope a first conversation.

Tell us what you're trying to do. We'll come back with a point of view, not a sales pitch.