Microsoft Fabric
Microsoft Fabric is a unified, cloud-based data platform that brings together data analytics, governance, and AI into a single, seamless solution. It unifies a wide range of data applications and sources across clouds and data formats into a single foundation that enables real-time insights, seamless collaboration, and continuous innovation.
Microsoft Fabric is particularly suitable for organizations that want to unify their data platforms, reduce silos, and extend their Power BI environment toward advanced analytics and AI within the Microsoft ecosystem. It provides a clear and well-governed way to build a scalable data platform that serves business users, analysts, and data engineering teams alike.
Why choose Microsoft Fabric?
What does Microsoft Fabric offer?
1. Unified data platform
A single unified analytics platform eliminates data silos, accelerates decision-making, and reduces the need for complex integrations. In Microsoft Fabric, data, analytics tools, and governance are centralized within the same environment, where different analytics components work seamlessly together without separate systems.
The single-platform model simplifies data utilization across the entire organization. A centralized data catalog improves data discoverability and enables different teams and use cases to leverage data without separate transfers or manual coordination.
2. OneLake – unified data lake for all platforms
Data availability improves, duplicate storage is reduced, and collaboration becomes more efficient when all organizational data resides in one place. OneLake acts as the centralized data store for Microsoft Fabric, bringing data together into a single environment regardless of file formats or source systems, while supporting solutions based on open standards.
OneLake supports data virtualization using a shortcut mechanism, allowing external data sources to be used without physical copying. This enables efficient data sharing and reuse while simplifying data integration.
3. End-to-end data engineering with Spark
Scalable and efficient data processing is achieved without complex architectures or multiple separate tools. Microsoft Fabric offers a unified data engineering solution where data import, processing, and further utilization take place within the same platform, which simplifies the whole process.
A lot of data processing is based on Apache Spark, enabling distributed and scalable processing of large amounts of data. The computing model adapts to the growth of data volumes and supports both traditional ETL processes and more advanced analytics use cases.
4. Native Power BI integration
Reporting is faster and a consistent business view is maintained when data processing and visualization occur within the same environment. Microsoft Fabric and Power BI form a solution where data flows from analytics to reporting without additional integration layers.
Data processed in Fabric is directly available in Power BI through semantic models. This improves data consistency and supports self-service analytics for business users as well.
5. Advanced analytics: AI, ML, and real-time data
Real-time visibility and AI-driven insights can be achieved directly within the organization’s own data platform. Microsoft Fabric supports streaming data processing, enabling real-time analytics and rapid responses to business events.
AI and machine learning capabilities are integrated directly into Fabric, allowing organizations to leverage their own data for analytics and automation solutions without separate integrations.
6. Enterprise governance on Microsoft Azure
Reliable data governance and precisely defined access controls reduce risk and support compliance requirements. In Microsoft Fabric, data governance, security, and access management are built-in components of the analytics platform, and access rights can be precisely defined at the data level, such as in files or tables.
The solution leverages Microsoft Entra for identity and access management and Microsoft Purview for data classification and visibility, supporting the controlled use of sensitive data within the Microsoft Azure environment.
Microsoft Fabric of Azure Databricks?
Both are excellent tools for building data platforms, with their strengths in slightly different areas. Microsoft Fabric is a comprehensive offering for building a centralized, very Microsoft-native approach to data platforms. Databricks, on the other hand, is a more mature product especially in complex analytical applications. While Fabric is quickly catching up on many feature gaps, it is still the simpler product, in both good and bad.
Choosing between the platforms, or a hybrid solution, is often also based on available skillset and expected usage. Databricks is the heavy hammer that can be used to solve the hardest problems, but Fabric often provides the lowest-friction option at least for organizations just getting started with data platforms. We will support you with the choice if necessary. And rest assured, whichever way you go, we are certain neither product will disappoint you.
Frequently asked questions about Fabric
How quickly can Microsoft Fabric be implemented?
Typically, implementation takes 3–6 months. It can also be implemented very quickly. As a fully managed SaaS platform, there is no infrastructure to provision. Power BI developers can start working with familiar tools almost immediately, often delivering value in days rather than months. Designing robust data governance, data layers, and operational processes may require additional time and expertise.
Who is Microsoft Fabric designed for?
Microsoft Fabric is designed for a broad audience, including Power BI developers, data engineers, data analysts, and data scientists.
It's especially well suited for organizations where Power BI is already widely used, and teams want to expand into data engineering and advanced analytics without a steep learning curve.
Can existing Azure analytics solutions be migrated to Microsoft Fabric?
Yes. Fabric works well alongside existing Azure solutions. Data and solutions from different platforms can be brought together under a single umbrella, whether they run in Azure or elsewhere. The idea is that Fabric enables this consolidation without requiring everything to be rebuilt from scratch.
How is Microsoft Fabric licensed?
Microsoft Fabric is licensed using a capacity-based model where you purchase Fabric capacities measured in Capacity Units (CUs) that power all workloads across the platform. A single capacity can be shared across Power BI, data engineering, analytics, and other Fabric workloads, simplifying licensing and making costs more predictable.
For Apache Spark workloads, you can optionally enable Autoscale Billing for Spark, which runs Spark jobs using dedicated serverless resources billed separately on a pay-as-you-go basis. This lets you pay only for the Spark compute you use without consuming the shared Fabric capacity.
Data in OneLake storage is billed separately at a pay-as-you-go rate per gigabyte of storage consumed. OneLake storage costs are typically much lower than capacity costs, making centralized data storage cost-effective.
Some of our clients
Adopting Fabric is a snap
Implementing Fabric typically takes 3–6 months. Costs depend significantly on the maturity of your data culture and cloud architecture. We'd be happy to give you an estimate once we know your needs.
Get in touch, and we’ll assess your needs together and provide you with an estimate of costs and schedule.
