If your analytics plan has been sitting in draft for the past 18 months, you’re not alone. Most organisations start with good intentions, but the reality is that data transformation is difficult. With legacy systems, competing business priorities, and the complexity of connecting multiple data sources, progress often grinds to a halt before it even gets underway.
The truth is simple: you can’t fix what you can’t see.
When customers first approach Data#3 to discuss Microsoft Fabric, they often don’t know how, or where to start. Some attempt to develop analytics strategies on their own, while others are still navigating issues of ownership and funding. Many have invested in tools like Power BI but haven’t transformed them into a unified, scalable data platform. It’s not that these organisations lack intention, it’s more that the path ahead feels unclear and daunting.
In our experience, organisations tend to get stuck at the starting gate or planning stage due to uncertainty, not inaction. They are often paralysed by a few recurring challenges:
As a result, they often look at the size of the task and decide it’s too difficult, too large or too premature to tackle. They may have the ambition but lack the capacity to gain traction, resulting in repeated delays or abandoned plans.
Microsoft Fabric is a unified, cloud-based analytics platform that covers the entire data lifecycle from ingestion through preparation, storage, analysis, and visualisation.
At the heart of Fabric is OneLake, a single data lake structure that all workloads share. It removes the need for multiple copies of data and supporting governance, discovery, and reuse across the organisation. For organisations frustrated by fragmented analytics setups, this means fewer silos, fewer “point” tools, and a clearer path to insights.
When you dig deeper, it’s not a lack of tools that causes customers’ analytics projects to stall or fail; it’s a lack of clarity. Therefore, the initial step isn’t buying technology but having a structured discussion about what success entails, identifying key opportunities, and understanding existing capabilities. We describe this as “level-setting”, helping customers align on what Microsoft Fabric offers, how it connects to their business priorities, and where to start. Often, that involves dispelling the idea that analytics transformation needs a full rebuild of systems. Instead, it focuses on finding a practical starting point, confirming an early win, and expanding from there.
This is where Data#3’s Analytics Assessment proves invaluable. It gives customers the “picture on the box” for their data transformation puzzle, showing what’s connected, what’s missing and where the next best step is. It provides a high-level design for customers ready to plan, presenting a holistic view of data maturity and alignment with Microsoft Fabric’s modern architecture, highlighting where you are and where you need to go.
For eligible qualifying customers, Data#3 may be able to secure funding support through Microsoft, reducing the initial costs. The outcome is a clear, actionable roadmap that highlights priorities such as what to address first, what to develop next, and what to postpone for later stages.
Analytics transformation doesn’t have to be daunting. You don’t need the entire plan laid out before you begin, you just need to identify where you are and take the right first step.
Data#3 supports organisations in navigating this uncertainty, simplifying complex challenges, and transforming analytics goals into real results. With our straightforward approach and extensive Microsoft Fabric knowledge, we eliminate guesswork so you can begin realising value faster.
While it shouldn’t be daunting, this stuff is still tough, and that’s exactly why you need us.
This blog is the first instalment of our three-part series on building a high-performing analytics foundation. In blog two, we break down what it takes to convert early wins into a scalable, organisation-wide platform. If you’d like to explore the full journey, you can also jump ahead to blog three, where we unpack what happens after go-live.
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