How the technology of Microsoft Fabric can help you maximize the value of your data

Developing your data analytics strategy via different solutions

Where traditional reactive reporting often relies on siloed data, the modern (predictive) solutions focus on an integrated approach via a unified data platform. By connecting data silos, a platform enables organizations to scale analytics efficiently and build towards true data maturity. It is a starting point of becoming data-driven, especially in finance.

We see different market solutions:

• General cloud providers: Azure (Microsoft), Google Cloud Platform and Amazon Web Services (AWS), each with their own data solutions, eg.: Fabric, Bigquery, …
• Providers with a focus on Data solutions such as Databricks (partnering with the general cloud providers for the hosting) and Snowflake.
• More niche data integration solutions such as Informatica, Qlik, and Alteryx. They offer for example easy connections to extract data from an ERP package and integrate the data into a bigger data platform.

In this article we focus on Microsoft Fabric.

A roadmap for a successful data strategy

TriFinance has extensive expertise in developing a data analytics strategy and implementing a data platform using Microsoft Fabric. Our experts assist in defining and implementing your data-driven strategy for optimal use, from best practices in data engineering to expertise in data modeling and translating reporting needs into the right solution.

Together, we create a future-proof data strategy aligning with your strategic objectives. We assess the value of data for your company, identify data & analytics topics that will create value for your business and define the to-be architecture for your data organization, processes, and systems. These elements form the basis for a roadmap for implementing this data strategy. We then conduct a business & functional analysis leading to best practice design of a new data analytics architecture, data models and dashboards.

We go beyond technological solutions. As we truly understand the business processes and reporting needs, we can provide you with the best advice for a pragmatic and unified data solution.

How Fabric, CoPilot and PowerBI strengthen each other

Fabric, CoPilot and PowerBI all belong to the Microsoft stack. The integrated environment ensures that all data and analytics tools are on a single platform, simplifying collaboration and data management. Two practical examples:

• Streamlined processes: Fabric enables data to be retrieved through Data Factory, processed in OneLake, and then visualized directly in Power BI.
• Fabric has seamlessly integrated AI capabilities, such as Copilot, that support report creation in Power BI without requiring complex DAX or SQL knowledge. Although we see many opportunities in this respect, only few companies are applying these AI capabilities for their financial reporting today.

Power BI training helps finance professionals use data strategically, not just visualize it. Discover more about our PowerBI training and learn how to use data strategically.

Key capabilities and differentiators of Microsoft Fabric

Microsoft Fabric provides a unified, AI-ready experience for data engineering, data science, analytics, and reporting, all within one environment.

Key benefits include:

• Unified compute and storage through OneLake
• Integrated governance and security with Purview
• Deep Power BI integration and Copilot capabilities
• A flexible cost model, paying only for what you use

How it works

Microsoft Fabric provides a single, cohesive environment for users across different roles to work with data. Teams can use the platform's integrated tools to prepare data, build machine learning models, and create interactive reports, all within the same unified system. The OneLake feature allows data to be stored in a single format in a single location while different workloads can still access and reuse the data without moving or copying it. This way the data and analytics are managed together.

As an end-user with the right data engineering skills you can optimally utilize the data platform’s technology. However, if you don’t have these skills, you can still get started. This evolution makes the technology accessible to a wide audience.

A key strength of the platform is that it offers various solutions based on your technical skills. This way, you have both options in one platform. More complex and computationally intensive steps can be handled efficiently by data engineers. Less technical people can also perform simpler data transformations and enable self-service, although sometimes this is less powerful. This significantly eases the learning curve and ensures that companies can also take steps independently once the foundation is solid.

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