What is Microsoft Fabric?

Microsoft Fabric is a data lake-centric software-as-a-service (SaaS) solution that unifies data integration, governance, real-time analytics, Power BI and powerful AI models, to all be hosted in one accessible platform. 

 

Our Microsoft Fabric Consultancy will enable you to unlock the potential of this AI-ready solution in a way that compliments your current data platform program of work and evolves your platform investment. With all new technology innovations, understanding how its capabilities can be harnessed effectively for your organisation’s requirements is key.

The Benefits of Microsoft Fabric

By unifying data management, analytics, and AI, Microsoft Fabric accelerates the time it takes to derive meaningful insights from data.

The platform enables end-users to perform their own analyses, reducing dependency on IT and fostering a culture of self-service.

With clear and adaptable cost structures, organisations can manage expenses efficiently.

Microsoft Fabric offers a modern analytics solution that is straightforward to administer, saving time and resources.

The platform includes robust data governance and security features, ensuring compliance and protecting sensitive information.

Access advanced AI features, such as Copilot, to enhance analytical capabilities and decision-making.

Embrace a lake-centric approach with an open platform that supports a wide range of data sources and formats.

Get Started with Microsoft Fabric

Whether your organisation is just beginning its data maturity journey, or it is looking to further elevate its AI practices, our expert consultants can support you in building a data roadmap that drives business value.

 

We help organisations uncover and articulate the use-cases that will make the biggest impact on their objectives, by harnessing the right technology at the right time. Our Microsoft Fabric Consultancy can enable you to design and build an architecture that delivers for your organisation now, and in the future. Our Solution Architects will help you to answer questions such as: 

 

  • I have an existing data platform – should I explore Microsoft Fabric? 
  • How do I retain my data platform investment while leveraging the benefits of this new solution? 
  • What Fabric use-case would be most applicable for my organisation? 
  • How do I establish data governance and cost management on Microsoft Fabric? 
  • How does Fabric help my organisation’s Power BI user community?

Our Data & AI Framework is Microsoft Fabric Ready

Accelerate the delivery of cloud data and AI platforms.

 

Telefónica Tech had been deploying its Data & AI framework to accelerate the delivery of clients’ data platform solutions since 2006. The framework is being continually refined to deliver engineering excellence and security, with the latest iteration fully Microsoft Fabric Ready.

Harnessing Microsoft Fabric – The Future of Analytics

Watch the Recording

Microsoft Fabric: 1-Hour Briefing Call

If you already have an investment in tools such as Azure Synapse Analytics and Azure Databricks, you can still reap the benefits of Microsoft Fabric whilst retaining your existing investment. In this 1-hour briefing call, we will discuss the features and capabilities of Microsoft Fabric, as well as relevant use-cases that can be delivered by the new solution. 

 

Our Approach 

 

  • Overview of Microsoft Fabric platform and its capabilities  
  • Showcase of value-led use-cases that can be delivered through Fabric  
  • Discussion of your organisation’s strategy and how Fabric can fit into this roadmap 

Microsoft Fabric: 5-Day Proof of Concept  

In this 5-Day Proof of Concept (PoC), our Solution Architects will enable you to quickly understand the features and capabilities of Microsoft Fabric, as well as relevant use-cases that can be delivered by the new solution. We can deliver a 5-day PoC for either a data engineering or data science use case, depending on your organisation’s requirements. 

 

Our Approach 

 

  • Overview of Microsoft Fabric and organisation strategy:  Exploring the architecture options available, defining the PoC objectives and potential use-cases, the non-functionals and a review of current data strategy and governance. 
  • For a data engineering use-case we will review data modelling & mapping, data analysis/profiling, data storytelling and wireframing. For a data science use-case we will assess AI and Machine Learning (ML) model options. 
  • Complete data extraction, ingestion/cleansing patterns and transformation. 
  • Deliver semantic layer or ML model. 
  • Build reports/dashboards, EDA (Data Insights/Value), or ML model, and review use-case output.