Implementing, expanding, or improving Microsoft Fabric? As a Microsoft Fabric partner, our consultants help with architecture, implementation, migration, data engineering, governance, and optimization. From a specific technical issue to setting up a complete data platform.
We always consider what best fits your needs, your existing environment, and the way your team works.
Microsoft Partner since 2015 | Certified Fabric consultants
It rarely starts with “we want Fabric,” but with a specific problem or next step. For example:
We can handle the entire process or provide targeted help with a single component, an architecture review, a second opinion, or a specific issue that requires just a few hours. Feel free to ask us a question.
A solid Fabric environment starts with the right architecture, setup, and governance. Not everything needs to move to Fabric, and not everything should be set up in the same way. That is why we look at your data sources, workloads, reports, security, deployment, management, and how your team works with the environment.
We design a Fabric architecture that fits your data sources, workloads, and existing Microsoft environment. This includes making deliberate choices about OneLake, lakehouses, warehouses, and semantic models.
We access, transform, and model data using pipelines, Dataflows Gen2, notebooks, mirroring, and Copy jobs, among other tools. This creates a data foundation that can be used for reporting, analytics, and AI.
We build new Fabric environments and migrate existing solutions from platforms such as Azure Data Factory, Synapse, Power BI, and other BI and data platforms. Rather than simply transferring them as-is, we improve them where it makes sense.
We configure Fabric for effective management, with clear choices for workspaces, security, deployment, Git/CI/CD, naming, monitoring, and ownership. This keeps the environment manageable as it continues to grow.
These elements are interconnected. Architecture, data engineering, governance, and management collectively determine whether a Fabric environment works well and remains manageable as it grows.
More and more organizations are considering Microsoft Fabric. Sometimes this is driven by a specific technical challenge, but also because Fabric is becoming increasingly prominent within the Microsoft stack.
That does not mean every organization needs Fabric. In some cases, it makes sense to bring data integration, storage, engineering, analytics, and Power BI together on a single platform. In other situations, your existing data architecture works perfectly well, or Power BI with a well-designed data foundation is sufficient.
That is why we do not start by asking how to implement Fabric, but first ask why. What do you want to solve, what challenges are you currently facing, and what needs to be possible in the coming years? Based on that, we determine which architecture and technology are the best fit.
If Fabric proves to be the right choice, we help with setup and implementation. If not, we provide further advice based on Power BI or your existing data architecture.
A Fabric implementation often does not start with an empty environment. There is usually already a data warehouse, Power BI landscape, Azure Data Factory, Synapse, or another BI or data platform in place.
That is why we first assess what is already in place and determine what should be migrated, what would be better redesigned, and what can simply remain as it is. To us, migration is not a like-for-like transfer, but a deliberate choice about what to retain and what to improve.
We help with areas including:
Where necessary, we begin with an assessment or architecture review. This allows us to map the current situation, dependencies, risks, and logical migration sequence before we start building.
We do not set up Fabric as a loose collection of workspaces, pipelines, and models. Instead, we use consistent principles for architecture, naming conventions, security, deployment, documentation, and management.
A key component is a metadata-driven foundation for loading and maintaining historical data. Wherever possible, you add new sources through configuration rather than building new pipelines for every table or source.
We also use clearly defined layers and separate development, testing, and production. Runs are traceable, customizations remain separate from the generic foundation, and we document key architectural decisions.
This keeps the environment understandable, scalable, and easy to hand over to your own team.
We use the Blueprint as a starting point, not a rigid framework. If a component does not fit your situation, we adapt it.
With Copilot, Fabric IQ, and data agents, Microsoft Fabric is increasingly becoming a platform where both users and AI applications work directly with business data.
This makes the quality of your data foundation even more important. Semantic models, definitions, metadata, relationships, and security must be sound before AI can provide reliable answers.
That is why we help organizations not only with the technical setup of Fabric, but also with determining which data and models are suitable for AI applications and how to make them available in a controlled manner.
Microsoft Fabric runs on capacity. This makes cost and performance integral to your architecture.
Among other things, we help select and size an appropriate Fabric capacity, analyze usage and peak loads, and distribute workloads. We also assess the impact of Power BI, data engineering, and other Fabric workloads on the same capacity.
For existing environments, we investigate where capacity is being consumed, which workloads cause peaks, and where optimization is possible. This prevents performance issues or unexpected costs from becoming apparent only once the environment is already in full use.
Our consultants hold Microsoft certifications in both analytics and data engineering within Fabric. This gives us knowledge across the platform, from semantic models and Power BI to data ingestion, transformation, and engineering. Bitmetric has been a Microsoft Partner since 2015.
DP-600: Fabric Analytics Engineer Associate
DP-700: Fabric Data Engineer Associate
Whether you want to set up a complete Fabric environment, improve an existing one, or need help with one specific component, we would be happy to discuss the most practical approach.
Fabric rarely operates in isolation. It often also involves Power BI, data modeling, governance, and your broader data architecture.
Still exploring Microsoft Fabric?Learn more about the platform on our Microsoft Fabric page.
Do you mainly work with Power BI?Fabric and Power BI are closely connected. On our Power BI consulting page, you can learn how we help with reporting, data models, DAX, and governance.
Looking for broader Data & Analytics consulting?Fabric is one of the platforms we work with. On our Data & Analytics consulting page, you can learn how we also approach strategy, architecture, implementation, and management.
Do you need support or management?Is your environment already up and running, but do you need help with incidents, improvements, or periodic maintenance? Visit our support and management page.
A Microsoft Fabric consultant helps you make decisions about the architecture, setup, implementation, and management of Microsoft Fabric. This may involve a complete data platform or a specific issue related to data engineering, pipelines, lakehouses, warehouses, semantic models, Power BI, governance, or performance.
Not necessarily. Fabric can make sense if you want to organize data integration, storage, engineering, analytics, and Power BI within a single platform. In other situations, your existing data architecture may be perfectly adequate, or Power BI with a well-designed data foundation may be sufficient. That is why we look at the challenge first and the technology second.
That depends on what you want to do with it and the capacity required. Fabric does not have to be rolled out across the entire organization right away. We assess workloads, usage, growth, and costs to determine whether Fabric is a good fit and which setup makes sense. Sometimes, a smaller or existing solution is the better choice.
No. A Fabric implementation does not have to mean completely replacing your current environment. We assess what works well and can remain in place, what can logically be moved to Fabric, and which components would be better redesigned. A hybrid architecture can be a deliberate and perfectly valid choice.
Yes. We can handle the entire process, from architecture and setup to data engineering, modeling, deployment, governance, and handover. We can also join a project that is already underway or take responsibility for a specific component only.
Yes. We help with migrations from Azure Data Factory, Synapse, existing Power BI environments, Qlik, and other BI and data platforms. We do not automatically migrate everything on a one-to-one basis. We first determine what you want to retain, what would be better redesigned, and what does not need to be migrated at all.
Yes. You do not have to start a complete Fabric project right away. We can begin with an architecture review, an assessment, a proof of concept, a single workload, or a specific technical issue that takes a few hours to address. You can then scale up based on what you learn.
Yes. Not every Fabric challenge needs to lead to an implementation project. We can assess an architecture, advise on a proposed decision, review an existing environment, or provide a second opinion on a design created by your own team or another vendor.
Yes. We often work with internal BI and data teams and design the environment so that your own people can continue working with it. We use established standards, document important architectural decisions, and ensure knowledge transfer. You therefore do not need to outsource further development or management to Bitmetric.
Yes. Our consultants hold Microsoft certifications including DP-600 (Fabric Analytics Engineer Associate) and DP-700 (Fabric Data Engineer Associate). Bitmetric has also been a Microsoft Partner since 2015.
Yes. We look not only at the AI functionality itself, but especially at the underlying data foundation. Semantic models, definitions, metadata, relationships, security, and governance must be properly configured before AI can work reliably with your business data.
Would you like to set up a new Fabric environment, improve an existing one, or discuss a specific challenge? Barry and Eric would be happy to help you determine what makes sense for your situation. Send us your question, call us, or schedule a call right away.
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Available on weekdays between 8:00 AM and 6:00 PM (Amsterdam time)
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