Skip to main content

Scalable, Cloud-Native Architecture

Modern Data Platforms

Fabric or Databricks is the question stalling half the data programmes we meet. We design, build and run production estates on both, so the platform decision gets made on your workloads and your budget, not a vendor's roadmap.

Our Core Data Platform Technologies

Data programmes stall on the platform question more than any other: Fabric or Databricks, and who in the room can answer it without a vendor incentive. This page exists to settle it properly. The right choice depends on your workloads, your existing Microsoft investment and your long-term architecture goals, and we help you make that call on evidence rather than instinct, because we design, build and run production estates on both platforms every week.

As a Fabric Featured Partner, Fabric Databases Featured Partner and Real-Time Intelligence Featured Partner, one of approximately 30 partners globally holding all three designations, Synapx brings unusual depth on the Fabric platform. Our Databricks practice covers lakehouse architecture, Unity Catalog governance and ML workload optimisation.

Two platforms does not mean two silos. OneLake mirroring lets Fabric serve Power BI analytics directly from the Delta tables a Databricks estate maintains, so plenty of our clients run both without copying data twice. And where your current answer is Azure Synapse, Azure SQL or an on-premises SQL Server warehouse, we will keep it healthy and governed until a migration genuinely earns its business case. Platform loyalty is for vendors; our loyalty is to the workload.

Every platform build lands with the same non-negotiables: infrastructure as code, CI/CD from the first commit, Purview governance, cost management designed in (our Xscale accelerator cut Mount Anvil's Fabric costs by 80%), and documentation your team can actually run the platform from.

The platform is also the foundation everything else in your Microsoft estate stands on. Copilot answers are only as good as the governed data beneath them, AI agents need curated domains to ground on, and Power BI is only trusted when the numbers reconcile. Build the platform properly once, and every later initiative starts faster and argues less.

Platforms we design, deploy and run

Microsoft Fabric Featured Partner
Microsoft Fabric Featured Partner
Fabric Databases Featured Partner
Fabric Databases Featured Partner
Data & AI on Azure
Data & AI on Azure
Real-Time Intelligence Featured Partner
Real-Time Intelligence Featured Partner
Infrastructure (Azure)
Infrastructure (Azure)
What We Deliver

Key capabilities

Microsoft Fabric & Azure Data Factory Implementation

We implement and optimise Microsoft Fabric and Azure Data Factory to unify your data engineering, warehousing, real-time analytics, and Power BI in one integrated SaaS experience.

  • Lakehouse, Warehouse, Real-Time Intelligence and Fabric Databases
  • Direct Lake semantic models for near-instant Power BI
  • Capacity sizing and Xscale cost optimisation
  • Purview governance configured from day one

Databricks & Lakehouse Solutions

We deploy Databricks and Lakehouse architectures for data engineering and ML workloads, enabling advanced analytics, machine learning, and unified governance at enterprise scale.

  • Delta Lake medallion architecture with data contracts
  • Unity Catalog for permissions, lineage and audit
  • MLflow for model lifecycle management
  • OneLake mirroring so Fabric serves BI from the same tables

Data Warehousing & Data Lakes

We design and build data warehousing, data lake, and multicloud data architectures that consolidate your data assets and provide a single source of truth for analytics and reporting.

Real-Time Streaming & Analytics

We implement real-time streaming, transaction processing, and customer insights analytics that enable your organisation to act on data as it arrives, not hours or days later.

  • Fabric Real-Time Intelligence: Event Streams, KQL, Data Activator
  • Spark Structured Streaming on Databricks for high-volume feeds
  • Honest sizing: real-time engineering only where the need is real
  • Real-Time Intelligence Featured Partner credentials behind the work

Compliance & Regulatory Reporting

We build fraud prevention, AML compliance, risk calculation, and regulatory reporting solutions that ensure your data platform meets the most stringent industry requirements.

  • Immutable history and full lineage back to source systems
  • Row-level security and least-privilege access models
  • Audit-ready documentation for FCA and PRA contexts
  • Proven in financial services and insurance estates
8 wks

To a governed, production-ready data platform

80%

Fabric cost reduction at Mount Anvil through Xscale

1

Single source of truth across business units

100%

Aligned to Microsoft reference architecture

Common Use Cases

Where Modern Data Platforms earns its keep

Migrating off legacy warehouses

Retire on-prem SQL, Teradata, Netezza or Oracle estates in favour of a cloud lakehouse that scales with demand and usage.

Consolidating fragmented data

Replace department-by-department reporting silos with a governed platform where finance, operations and commercial share one semantic layer.

Enabling real-time analytics

Add event streams, KQL databases and Data Activator so the business reacts to what is happening right now, not last month.

Preparing for enterprise AI

Build the clean, governed foundation Copilot, agents and bespoke models need to generate trustworthy answers.

Multi-cloud and hybrid estates

Design a lakehouse that spans Azure, Fabric and Databricks, and integrates cleanly with AWS or GCP sources where needed.

Regulated reporting platforms

Engineer fraud, AML, Solvency II and risk reporting on a platform with immutable history, lineage and role-based access.

How We Work

A proven delivery approach

  1. 01 Step

    Assess

    Review current data estate, workloads, licensing and skills against a Microsoft-aligned target state.

  2. 02 Step

    Architect

    Design a reference architecture, governance model and migration approach with clear cost and risk trade-offs.

  3. 03 Step

    Build

    Deploy the platform using infrastructure-as-code, wire up governance, and migrate the first priority workloads.

  4. 04 Step

    Scale

    Onboard additional domains, optimise capacity and cost, and embed DataOps so the platform keeps improving.

Client Voices

From our platform clients

"Not an external supplier, an extension of our team."

"Working with Synapx has been transformative for Mount Anvil. They didn't feel like an external supplier; they became an extension of our team. Their technical expertise in implementing Microsoft Fabric solved our immediate challenges and positioned us for future growth, including AI and machine learning. What truly set Synapx apart was their transparency, commitment, and cost-optimisation through Xscale, making Fabric financially sustainable."

Mount Anvil

Head of Technology Applications, Mount Anvil

"Our go-to data partner. We recommend them to every one of our clients."

"We work with Synapx as our go-to and trusted partner for anything Power BI, or data in general, so much so we recommend them to all our clients! The team at Synapx work with us in a way that makes it feel like they are part of our business, our 'data team'; projects and on-going support are executed easily and effortlessly."

Lanware

Chief Technology Officer, Lanware

FAQ

Frequently asked questions

Do we have to choose between Fabric and Databricks?

No. We regularly design hybrid estates where Databricks handles heavy engineering and ML, and Fabric surfaces curated data to Power BI, Copilot and business users. The right split depends on workloads, team skills and commercial model.

How long does a platform build take?

A governed foundation – networking, identity, OneLake / catalogue, CI/CD and a first domain – typically takes 8–12 weeks. Full migration off a legacy warehouse usually runs 6–12 months depending on complexity and change appetite.

Can the platform support real-time use cases?

Yes. We implement Fabric Real-Time Intelligence, Event Streams, KQL databases, or Databricks structured streaming – choosing the pattern that best fits latency, volume and downstream consumption.

How do you keep cloud data costs under control?

We baseline capacity, tag every resource, monitor Fabric capacity units and Databricks DBUs, and tune workloads continuously. Clients on Synapx-as-a-Service typically see 20–40% cost reduction in the first six months.

Is this suitable for regulated industries?

Yes. We run data platform programmes for financial services, healthcare and public sector clients with private networking, customer-managed keys, Purview classification, audit logging and evidence trails for regulators.

Can you operate the platform after go-live?

Yes. Synapx-as-a-Service provides 24/7 platform operations, enhancement and cost optimisation by the same UK-based team that built it, so knowledge is retained and improvements continue.

Our Clients

Trusted by

Glassmoon
Lanware
Micheldever Tyre Services
Midwich
Mount Anvil
Nuevo Partners
Pro Global
Seras Energy
Skanska
Ocean Conservation Trust
WA Comms
Glassmoon
Lanware
Micheldever Tyre Services
Midwich
Mount Anvil
Nuevo Partners
Pro Global
Seras Energy
Skanska
Ocean Conservation Trust
WA Comms

Book a Platform Selection Workshop

Half a day with your architects and your real workloads. You leave with a written recommendation: Fabric, Databricks, both, or the estate you already own, with costs and a migration sequence attached.

Book a Selection Workshop