Meet Microsoft Fabric 

microsoft fabrics new

Microsoft Fabric – the new powerful data tool

What is Microsoft Fabric? Picture it as the Swiss Army knife for your data – blending data engineering, warehousing, real-time analytics, business intelligence, data science, and governance into a smart, scalable platform. By bringing together the best of Microsoft Azure and other services, Fabric creates a streamlined user experience designed for intuitive data management. The Microsoft’s AI-powered data platform unifies all workloads in one data lake called OneLake, making it easier for businesses to make decisions based on their data.

What makes Microsoft Fabric a game changer? 

Tailored workloads

Choose the solution with all necessary tools customized for your role.

OneLake integration

Dive into the unified data lake for simplified data management.

Copilot power

Boost your productivity with the Microsoft AI-driven helping hand.

Azure AI Foundry

Take advantage of advanced AI and machine learning capabilities and build AI models seamlessly.

See examples of ready-made Power BI Packs developed by the Isystems team for Sales, Purchases, Warehouse, Receivables, Payables

Empowering every data role 

Microsoft Fabric is purpose-built to support every data professional across your organization: 

Maximize the value of your enterprise data 

  • Make smarter decisions
  • Unify your workflows
  • Collaborate cross-organizational
  • Simplify your data operations
  • Scale and be flexible
Make smarter decisions

Fabric automates tasks and reveals the latest insights for faster and better decisions thanks to built-in AI-powered analytics and machine learning algorithms. 

Unify your workflows

With Azure, Power BI, Microsoft 365, and other Microsoft services all at one place you can enjoy a great user experience while processing your data.  

Collaborate cross-organizational

Fabric gives you the ability to access, manage and analyze the same data as your coworker across your organizations. Thus, collaboration and sharing knowledge become easier and more effective. 

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Simplify your data operations

Microsoft’s data platform streamlines every stage of the data lifecycle within one secure, SaaS-based platform. With integrated security, governance, and compliance, it brings data together from various sources, then prepares, stores, and analyzes it. 

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Scale and be flexible

Organization of all sizes can utilize Fabric’s capabilities thanks to its cloud-native architecture that can withstand data evaluation while keeping its high performance and security standards. 

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FAQ
  • Why is Microsoft Fabric more advanced than Power BI?
  • Is Microsoft Fabric free to use?
  • How does Microsoft Fabric differ from other platforms?
Why is Microsoft Fabric more advanced than Power BI?

Microsoft Fabric covers the complete data cycle in a single platform. Power BI is focused only on data visualization and reporting.   

Is Microsoft Fabric free to use?

A free trial is available, providing access to core workloads and essential resources. 

How does Microsoft Fabric differ from other platforms?

Fabric enables complete data workflows, covering ingestion, transformation, storage, and visualization, while supporting seamless collaboration, open data standards, and scalable, domain-oriented architectures such as data mesh.

  • Is Microsoft Fabric suitable only for large enterprises?
  • Does Microsoft Fabric require servers?
  • What is the difference between Data Factory and Data Engineering in Fabric?
Is Microsoft Fabric suitable only for large enterprises?

Not at all. Fabric is designed for organizations of all sizes, offering flexible scalability and powerful features. 

Does Microsoft Fabric require servers?

No, Fabric is fully cloud-based, eliminating the need for server management. 

What is the difference between Data Factory and Data Engineering in Fabric?

Data Factory is designed for orchestrating data flows and ETL pipelines, ensuring smooth transfer and transformation between systems, while Data Engineering emphasizes constructing lakehouses and applying Spark for high-volume, complex computations.