Who we are, what we believe in, and the team driving Synapx forward.
The industries we serve and the outcomes we deliver across each sector.
Microsoft credentials and the partners we collaborate with to deliver outcomes.
Join a team of Microsoft specialists building the future of data and AI.
Upcoming webinars, XIAD workshops and executive briefings from our team.
Data
Pipelines one person understands, dashboards nobody quite trusts, a licensing bill that keeps climbing. We design, build and run the Microsoft data platforms that fix that: engineering, analytics and BI on Microsoft Fabric and Azure Databricks, with Synapse, Azure SQL and long-serving SQL Server estates looked after just as carefully.
Our accreditations
Engineering · Analytics · BI
Most data estates we take on look remarkably similar. A warehouse that has grown by accretion over a decade. Pipelines only one person understands. Power BI workspaces multiplying without an owner. A licensing bill nobody can fully explain. The technology is rarely the real problem; the absence of a deliberate platform decision usually is.
Synapx sits in an unusual position in the UK market. We hold all three Microsoft Fabric Featured Partner designations, something only around 30 partners worldwide can claim, and we also design and run production lakehouses on Azure Databricks. That means we have no platform to defend. When a client asks whether Fabric or Databricks should sit at the centre of their architecture, we answer from delivery experience on both.
Fabric and Databricks lead our work, but they are not the whole of it. A great deal of UK mid-market data still lives in Azure Synapse, Azure SQL and on-premises SQL Server, often with SSIS packages and SSAS cubes quietly keeping the business running. We modernise those estates at whatever pace makes commercial sense: sometimes a full lakehouse migration, sometimes tuning and governing what you already own until the case for moving is real.
Engineering is only half the job. Our analytics practice turns the platform into something people actually use: certified Power BI semantic models, governed self-service, and report estates rationalised from hundreds of orphaned workbooks down to a set the business trusts. That work shows up in hard numbers. The Fidelis Partnership saved over £60,000 a year in licensing costs after we rebuilt their reporting governance, and Mount Anvil cut report delivery times by 40% within three months of moving to a Fabric lakehouse.
The team behind this holds 150+ Microsoft certifications, including 3 Microsoft MVPs, and delivers from London with engineering hubs in India. More usefully: the consultants who scope your platform are the same people who build it, and the same people who answer the phone afterwards.
Critical information trapped in disconnected tools, spreadsheets, and databases, making it impossible to see the complete picture.
Teams spending valuable time consolidating data instead of analysing it, only to produce reports that are outdated before they're shared.
Different departments reporting different figures because they're working from different sources, undermining confidence in decision-making.
Relying on historical reports instead of real-time insights and predictive analytics, keeping you one step behind.
Manual processes and legacy tools that can't scale, creating bottlenecks that slow your entire organisation.
Platform decisions, target architecture and a roadmap the board can hold you to. We move organisations from ad-hoc data collection to a strategy with named owners, clear priorities and measurable outcomes.
When every new report means another extract and the Fabric-or-Databricks question keeps getting deferred, the estate needs a deliberate foundation. We design and build lakehouses on both platforms, and modernise Synapse and SQL Server estates at the pace that makes commercial sense.
Overnight loads that fail quietly, fixes that live in one engineer's head, numbers that shift between refreshes. We build pipelines that are tested, observable and cheap to run, so the business can trust what it reads.
Forecasts still living in spreadsheets, and ML pilots that never left the notebook. We build explainable models over governed data, wired into the workflow that uses them, and we will tell you when a good report beats a model.
A programme that needs a senior engineer for six months, a gap in the BI team, a backlog the permanent staff cannot clear. DaaS gives you named senior data people on a flexible monthly model, working to the same standards as our project delivery.
Pre-built frameworks that compress delivery from months to weeks, including our Xtract extraction accelerator and Xscale for Fabric cost optimisation.
Platform Choice
It is the question we hear most often, and it deserves better than a diplomatic "both are great". Both are lakehouse platforms, both store data in open Delta format, and both are excellent at what they were built for. Where they differ is who they were built for, and how you pay for them.
We hold Microsoft's top Fabric designations, and we still put Databricks at the heart of engineering-heavy estates when that is the right call. This is the summary we talk clients through before any platform decision.
| Criteria | Microsoft Fabric | Azure Databricks |
|---|---|---|
| Built for | Organisations that live in Microsoft 365 and Power BI and want one governed SaaS platform for BI, engineering and real-time analytics | Engineering-led teams running large-scale Spark, streaming and machine learning who want fine-grained control of everything |
| Team skills | Friendly to analysts and BI developers, with low-code options at every layer | Assumes engineers who are at home in notebooks, Python and Git |
| Cost model | Capacity-based: one pooled compute SKU covers every workload, so spend is predictable | Consumption-based: pay per second of compute, efficient under load but needs active FinOps |
| Power BI & Microsoft 365 | Native. Direct Lake, OneLake shortcuts and semantic models in the same tenant | Strong connectors and mirroring into OneLake, but BI sits one integration away |
| Engineering & ML depth | Improving fast and already strong for most workloads | The deepest on the market: MLflow, Unity Catalog and years of Spark maturity |
| Governance | Purview integration and workspace governance largely out of the box | Unity Catalog is excellent, but expect more assembly work |
| We reach for it when | BI-centric estates, mixed skill levels, and budgets that need to be predictable | Heavy engineering, serious data science, and very large or multi-cloud data |
In practice the answer is frequently both: Databricks doing the heavy engineering while Fabric serves analytics from the same Delta tables through OneLake mirroring, so nothing is copied twice. And when the honest answer is that your Synapse or SQL Server estate has years of useful life left in it, we will say that instead. Read our full Fabric vs Databricks comparison, or ask us to run the decision against your actual workloads.
Accurate. Accessible. Aligned.
We evaluate your current data infrastructure, quality, and governance capabilities to identify gaps and opportunities.
Through conversations with key stakeholders, we uncover data sources, usage patterns, and pain points across your organisation.
We bring leadership together to define data strategy, prioritise initiatives, and align on high-impact use cases.
Our team performs a detailed analysis of data quality, architecture, and pipelines to uncover insights and improvement areas.
We design and deploy data solutions, pipelines, and integrations that streamline processes and enhance accessibility.
We create a comprehensive roadmap, governance framework, and key performance metrics to guide your data-driven initiatives.
We establish a governance council to oversee data initiatives, drive accountability, and ensure strategic alignment.
We equip your teams with the skills, training, and best practices needed to maximise the value of your data.
Synapx is proud to host Microsoft Fabric Analyst in a Day workshops on behalf of Microsoft, helping organisations accelerate their analytics and Data & AI capabilities using the Microsoft Fabric platform.
Recent data platform and analytics engagements, with the numbers that mattered to the client.
A modern Microsoft Fabric data platform with master data management, daily snapshotting and Activator alerting, built as a foundation for AI at Mount Anvil.
A Power BI reporting suite connected to Jira Service Management, providing real-time visibility into ticket volumes, SLA compliance, and team performance.
A Power BI revenue reporting solution replacing manual Excel reports, delivering automated daily insights into revenue performance, technician productivity, and service trends.
"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."
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."
Chief Technology Officer, Lanware
Common questions about how Synapx delivers data platforms, Microsoft Fabric, Databricks and analytics.
It genuinely depends on your workloads, your team and how you prefer to pay for compute. Fabric usually wins for BI-centric estates that live in Microsoft 365; Databricks usually wins for engineering-heavy and data science workloads. Plenty of our clients run both, mirrored through OneLake so nothing is stored twice. We run a short platform decision workshop that settles the question against your actual data rather than a slide deck.
Yes. We run dedicated migration engagements from SQL Server, Teradata, Snowflake, Redshift and on-premises warehouses into Fabric or Databricks. We assess readiness, map workloads, re-platform the ETL and cut over with minimal disruption to business reporting.
Governance is designed in, not bolted on. We implement Microsoft Purview for cataloguing, lineage and access policy, build automated data quality testing into pipelines, and set up ownership models so every dataset has a named steward. For Power BI we certify semantic models, so the business knows exactly which numbers to trust.
AI Strategy, AI Readiness Assessments, Agentic solutions with Microsoft Copilot Studio, MLOps, AI Governance, Azure AI Foundry implementation, and delivery accelerators. We cover generative AI, traditional ML, computer vision, and NLP.
We deliver the full Microsoft data stack: Microsoft Fabric (Lakehouse, Warehouse, Real-Time Intelligence, Data Activator, Fabric Databases), Azure Databricks, Azure Synapse, Azure SQL, Power BI, and Purview for governance. We also modernise existing estates on SQL Server, SSIS, and SSAS.
Our accelerators deliver a working Fabric or Databricks foundation in 4–8 weeks. Full enterprise data platforms (multi-source, governed, with Power BI and AI layered on) typically run 3–6 months using our agile pod model.
Yes. Our Synapx-as-a-Service model provides ongoing platform engineering, performance tuning, cost optimisation, and roadmap development for Fabric, Databricks, and Azure data estates.
Fully Featured Fabric Partner
One of just 30 partners worldwide, out of 400,000+ Microsoft Partners, holding all 3 Fabric designations
Microsoft MVPs
Recognised by Microsoft
Microsoft Certifications
Across Azure, Fabric & Power Platform
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Tell us what your estate looks like today: the platforms, the pain points and the licensing bill. We will come back with an honest view of where Fabric, Databricks or the SQL estate you already own fits, and what to fix first.
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