Microsoft Fabric: An Emerging Data Analytics Solution
Microsoft has recently launched the public preview of its all-in-one analytics solution, Microsoft Fabric. This platform is designed to consolidate a multitude of tasks involved in data handling and analytics, such as data engineering, data science, data integration, business intelligence, and data governance, into a unified SaaS offering.
Building upon the capabilities of established tools like Power BI, Azure Data Factory, Azure Synapse, and Azure Data Lake, Microsoft Fabric weaves these components into an integrated analytics platform. It presents a comprehensive solution that revolutionizes enterprise analytics, streamlining the process and reducing the complexity typically associated with managing multiple disparate services.
As a SaaS product, Microsoft Fabric brings a new level of simplicity and efficiency to the table, offering an end-to-end analytics solution that stands to redefine how enterprises approach their data strategies.
Microsoft Fabric consists of several components, each tailored for specific tasks and personas:
Key Components of Microsoft Fabric
These components collectively make Microsoft Fabric one of the most comprehensive data analytics platforms in the industry, providing an end-to-end analytical solution that is hard to ignore.
Looking Towards the Future
Looking Towards the Future
ETA GA at the start of 2024
As the product is currently in public preview and not expected to reach General Availability until the start of 2024, we have been dedicating time to understand and assess how it could redefine best practices for data platform development and use within an organization.
We see Microsoft Fabric as more than just a tool for the development phase of a data platform. It is poised to significantly impact the ongoing usage and management of the platform within the organization. This includes aspects like data governance, accessibility, and the ease of applying analytics and business intelligence insights across different levels and functions of the organization.
Can become the go-to solution for analytics needs
Our initial impressions are extremely positive. For clients that have chosen Microsoft as their service provider, we anticipate that Microsoft Fabric will become the go-to solution for their data and analytics needs. The promise of having a single, integrated platform that streamlines complex processes is incredibly appealing, and we are excited to see how this potential will be realized once the product reaches General Availability.
Even in this early stage, the buzz around Microsoft Fabric is tangible, particularly on platforms like LinkedIn, where the product’s announcement generated a significant amount of interest and discussion. As the product continues to evolve and more features become available for testing, we are keen to delve deeper into its capabilities. Our goal is to be ready to help our clients leverage Microsoft Fabric as effectively as possible as soon as it goes live.
Line Arnbjørn Krogh, Manager at Intellishore
And don't worry, we will not use your information to spam you with buzz-filled articles on AI.
We look forward to hearing from you.
The Core of Microsoft Fabric: OneLake
OneLake, the heart of Microsoft Fabric, is a unified data lake built on Azure Data Lake Storage (ADLS) Gen2. This single, unified storage system is designed to eliminate data silos, simplifying data sharing and enforcing policy and security settings uniformly and centrally.
The structure of OneLake is hierarchical, providing a single-pane-of-glass file-system namespace across users, regions, and even clouds. It enables developers and business units to create their own workspaces, ingest data into their own lakehouses, and start processing, analyzing, and collaborating on the data.
All Microsoft Fabric compute experiences, such as Data Engineering, Data Warehouse, Data Factory, Power BI, and Real-Time Analytics, are prewired to OneLake. Additionally, OneLake introduces the Shortcut feature for instant mounting of existing PaaS storage accounts, extending to other storage systems and allowing data composition and analysis across clouds.