Microsoft Fabric

Microsoft Fabric is used by organisations to bring their data together, improve reporting, and build a more scalable and reliable analytics environment. 

In practice, most organisations don’t adopt Fabric just for a single use case. They typically use it to address a combination of challenges across reporting and analytics. 

Common uses of Microsoft Fabric include: 

Improving reporting and reducing manual processes 

Many organisations use Fabric to replace time-consuming, error-prone reporting processes that often rely on spreadsheets or multiple disconnected tools. 

By centralising data and using Fabric and Power BI, teams can create consistent reports and dashboards, making it easier to access insights to make decisions. 

Creating a single, trusted view of data 

A common issue in many organisations is having multiple versions of the same data across different systems and teams. 

Fabric brings data together into a central location (OneLake), helping ensure everyone works from a consistent, trusted source of information and improving confidence in reporting. 

Enabling self-service analytics 

In many businesses, reporting requests sit in IT backlogs, slowing down decision-making. 

Fabric empowers business users to access and explore data more easily, while still maintaining governance. This reduces reliance on IT for every report change and allows teams to answer their own questions faster. 

Improving data governance and security

When data is shared via spreadsheets, emails, or multiple reporting tools, it can introduce security and compliance risks.

Fabric provides a more controlled environment for managing and sharing data, helping organisations improve governance while still making data accessible to the right users.

Building a modern, scalable data platform

Fabric is also used to replace and modernise legacy data environments.

Organisations use it to replace fragmented tools or older data warehouse solutions with a single, cloud-based platform that can scale as data volumes and business needs grow.

Supporting advanced use cases and real-time analytics

Fabric also enables use cases beyond traditional reporting, such as:

• Analysing real-time data (e.g. operational or event-driven data).
• Supporting data science and machine learning use cases.
• Enabling more advanced use cases such as predictive analytics.

Improving efficiency for data and BI teams

From a technical perspective, Fabric simplifies the development and management of data pipelines and analytics workflows.

By bringing multiple capabilities into one platform, teams spend less time integrating tools and more time delivering value from data.

Do you have a specific use case that you would like to discuss? Talk to a Fabric specialist today.

OneLake is the data foundation of Microsoft Fabric. It is a single, unified data hub to manage, access, and reuse your data, without the overhead of constantly moving or duplicating it. OneLake is like OneDrive, but for your organisation’s data instead of files. The benefits of OneLake include: 

• Single source of data
• Less duplication, less complexity
• Works across other cloud systems
• Organised and easy to navigate
• Built for reuse: Data is stored in open formats
• Access control and centralised data governance. 

For business users, OneLake isn’t about how data is stored; it’s about how easily you can access, trust, and use that data in your day-to-day work.

With OneLake, business users do not need to wait for data to be prepared; you can access what you need in one place, reducing reliance on IT. Business users work from a common view of the data, enabling more consistent reporting and better cross-team collaboration.

For data engineers, OneLake changes how you manage, organise, and serve data across the business. Data can be ingested once and reused across Fabric workloads, reducing pipeline duplication. Shortcuts minimise data movement by allowing access to data where it resides, reducing engineering effort and simplifying the architecture. Overall, OneLake reduces the heavy lifting so teams can focus on building and delivering reliable data solutions.

Microsoft Fabric is licensed using a capacity-based (SaaS) model, meaning you pay for a pool of computing resources across Fabric workloads. Instead of purchasing separate tools or licences for each feature, you pay for a shared pool of cloud computing resources that can be shared across Fabric workloads.

Costs are based on two main components:

• The amount of compute capacity you provision.
• The amount of data you store.

Capacities are available in different sizes, known as SKUs (e.g., F2, F4, F8). Higher SKUs provide greater performance and scale.

One of the key advantages of this model is simplified billing. Rather than managing multiple tools and vendors, compute capacity and storage are consolidated within the Fabric platform.

Storage in Fabric is provided through OneLake, Microsoft’s unified data lake, and is billed based on data stored and usage.

Power BI licensing still plays a role. Report creators require Power BI Pro (or Premium Per User). If your organisation is using a Fabric F64 or above capacity, users can view reports without needing individual Pro licenses. Where a Fabric capacity is lower than F64, viewers will also require Power BI Pro or Premium Per User licenses.

You can access the latest Fabric pricing and a price calculator on the Microsoft website here:
Microsoft Fabric pricing

Microsoft Fabric includes Power BI as one of its core workloads. When you purchase Fabric capacity, you gain access to Power BI, along with other data and analytics capabilities such as data engineering, data warehousing, and data integration.

When we say "Fabric includes Power BI”, we are referring to the platform itself.

However, this does not remove the need for user licences. Power BI licences (such as Pro or Premium Per User) are still used to control who can create, share, and in some cases, access reports.

Refer to FAQ: Do I need to purchase a Power BI license if I purchase a Fabric license?

In most cases, yes. Power BI licences are still required, depending on how users interact with content.

• Report creators need a Power BI Pro or Premium Per User (PPU) licence
• Viewers:
  • With a Fabric F64 or above capacity, users can view reports without a Pro license.
  • With a smaller Fabric capacity (ie F2 to F32), users will require a Power BI Pro or Premium Per User (PPU) licence.

In summary, Fabric provides the platform. Power BI licences control access.

No, you do not need Microsoft Fabric to use Power BI.

Power BI remains a standalone service that organisations can use independently for reporting and dashboards.

Microsoft Fabric builds on Power BI by adding broader data capabilities, such as data engineering, data warehousing, and real-time intelligence, all within a single platform.

Organisations typically consider Fabric when Power BI alone is no longer enough to manage growing data complexity — such as combining multiple data sources, handling larger data volumes, or supporting more frequent and reliable data refreshes.

Every Fabric implementation at Professional Advantage starts with an Analysis and Design phase. Through workshops, we work with your team to understand your current data environment, what you're trying to achieve, and what success looks like for your organisation. This phase results in a formal proposal outlining the scope and effort involved, giving you a clear picture of what's ahead before any build work begins. 

If you choose to proceed, the project moves into build, deployment, and depending on your needs, ongoing maintenance and expansion. 

How long does a Microsoft Fabric implementation take? 

It depends on the scope and approach that's right for your business. Here are some typical examples: 

• Pilot or Proof of Concept (2–4 weeks): Ideal for organisations that want to explore Fabric before committing to a full rollout. We architect your Fabric environment and deliver one or two integrations, giving you a working foundation and a clear picture of what's possible. 

• Focused Implementation (4–8 weeks): Suited to teams with a defined use case — such as consolidating a small number of data sources into a unified analytics layer. You get a production-ready solution without the overhead of a large programme. 

• Enterprise Implementation (3–6 months): For complex, multi-source environments where data needs to be pulled from several platforms, transformed, and modelled for reporting and analytics at scale. This typically includes governance, security configuration, and onboarding your wider team. 

Most clients don't stop there. Microsoft Fabric is a platform built for growth, and the majority of our engagements evolve into ongoing partnerships — whether that's adding new data sources, building out additional reports and models, automating more of the data pipeline, or expanding access across the business. Phase 2 often looks very different from Phase 1, and that's the point: as your confidence in the platform grows, so does what you can do with it. 

Every engagement starts with a scoping conversation, so you'll always know what to expect before work begins. 

That's largely up to your organisation. Some clients want a fully delivered solution: a clean, governed data layer, dashboards, documentation, training, and a structured handover. Others have internal capability and prefer to take ownership of certain parts of the build, such as report development, while PA handles the architecture and data engineering. We work flexibly around your internal skills and resources, so you're not paying for work your team can already do.

Depending on the size and complexity of the engagement, your project team may include a data engineer, Power BI developers, a project manager, and an account manager. Smaller engagements can be delivered by a single consultant; larger ones by a small, dedicated team.

The honest answer is that it depends. The cost of a Fabric implementation is driven by a number of factors: how many data sources need to be integrated, the complexity of the architecture required, the level of transformation and cleansing your data needs, and how much of the delivery your internal team can absorb versus what PA needs to provide. 

That's why we start every engagement with a paid Analysis and Design phase. Through a series of structured workshops, we map your current data environment, define what you want to achieve, and scope the work involved. At the end of that process, you receive a formal proposal outlining the scope and investment required, so there are no surprises once the build begins. 

It's also worth considering the cost of your current situation. Fragmented data environments are rarely cheap to run, with duplicate licensing across multiple tools, the time your team spends reconciling data from different systems, and the risk of decisions made on incomplete information, and risk of ungoverned data. The status quo carries a cost, too. A well-implemented Fabric environment typically consolidates that spend, and reduces risk significantly. 

If you'd like a conversation about what a Fabric engagement might look like for your organisation, our data specialists are happy to talk it through before you commit to anything. 

Talk to a data specialist: https://www.pa.com.au/contact/ 

Your project will be staffed by a team of Microsoft-certified data consultants with hands-on experience delivering Fabric and Power BI implementations across a range of industries and organisational sizes. 

Our consultants hold the following Microsoft certifications: 

• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) 

• Microsoft Certified: Fabric Data Engineer Associate (DP-700) 

• Microsoft Certified: Power BI Data Analyst Associate (PL-300) 

Professional Advantage is also an accredited Microsoft Fabric Analyst in a Day and Dashboard in a Day delivery partner. 

What sets our team apart is the breadth of experience they bring beyond the platform itself. Many of our consultants have backgrounds implementing ERP, budgeting, and financial planning systems. Some hold CPA qualifications; others hold postgraduate degrees in analytics. That means they understand your data in a business context — not just how to move it from one system to another, but what it means and why it matters to your organisation.