Microsoft recently unveiled its latest innovation, Microsoft Fabric®, an integrated data and analytics platform constructed on the robust foundation of the company’s OneLake data lake. Users should experience several interesting benefits, including easier data integration and platform-independent data analysis.
So, what exactly is Fabric? According to the overview provided by Microsoft, “Fabric is an all-in-one analytics solution for enterprises that covers everything from data movement to data science, Real-Time Analytics, and business intelligence. It offers a comprehensive suite of services, including data lake, data engineering, and data integration, all in one place.”
The beauty of Fabric is that it eliminates the need to piece together different services from multiple vendors. Instead, businesses can employ a highly integrated, end-to-end, easy-to-use product to simplify analytics. This capability is further supported by the platform being built upon an established Software as a Service (SaaS) foundation.
– Source: Microsoft
Microsoft Fabric and Power BI: Cut from the Same Cloth
Current Power BI® users will likely notice an inherent familiarity with Fabric. The SaaS foundation used to build Fabric is what Power BI utilizes today. While Fabric offers a plethora of new features, the fundamentals of Fabric and Power BI are in most cases indistinguishable.
Shared features and experiences include, but are not limited to:
- Workspaces– Fabric workspaces behave like Power BI workspaces only with increased availability of item types.
- Navigation– If you understand how to operate the Power BI portal, you know how to move around Fabric. They work the same.
- Collaboration and Content Management– You can collaborate and share with Fabric items and workspaces like you do with Power BI.
- Capacities– New Fabric workloads utilize the capacity-based compute model used by Power BI Premium.
- Administration– Fabric administration works like Power BI administration, and the Fabric admin portal is just an evolution of Power BI’s portal.
OneLake, the OneDrive for Data
OneLake® is a SaaS data lake that is a fundamental element of the Fabric SaaS foundation. Each Fabric tenant involves a single OneLake instance, and every Fabric experience works natively with data in the lake. Microsoft is christening OneLake, the OneDrive for data.
Like OneDrive, OneLake is included with every Microsoft Fabric tenant, designed to be the solitary destination for all analytics data. OneLake provides companies with a single data lake for the entire organization and a copy of data to use with various analytical engines.
Microsoft Fabric: Core Components
Fabric provides an exhaustive set of features, ranging from integration tools, a Spark-based analytics platform, to a real-time analytics tool, all boosted by an upgraded Power BI. This facilitates user-friendly visualization and AI-based analytics. Furthermore, Fabric presents a no-code developer interface, enabling users with various experience levels or programming to monitor real-time data.
Fabric offers comprehensive analytics experiences designed to work together seamlessly. Each experience is tailored to an individual user and a particular task. Microsoft Fabric’s core components include:
- Power BI– A Business Intelligence platform that permits organizational users to access all data in Fabric quickly and intuitively, aiding in data-informed decision-making.
- Data Engineering– Provides a Spark platform designed for data engineers to transform large-scale data and democratize data using the lakehouse. Integrating Microsoft Fabric Spark with Data Factory allows notebooks and Spark jobs to be scheduled and orchestrated.
- Data Factory– Integrates the user-friendly Power Query with the scalable Azure Data Factory. This combination provides over 200 native connectors to data sources on-premises and in the cloud.
- Data Science– Facilitates creation, deployment and operational management of machine learning models within the Fabric environment. Integration with Azure Machine Learning includes built-in experiment tracking and model registry. This integration allows enriched organizational data with predictions and business analysts to combine those predictions into their Power BI reports, allowing for the transition from descriptive to predictive insights.
- Data Warehouse– This feature provides SQL performance and scalability, separating compute from storage for independent scaling of both components. It also includes native data storage in the open Delta Lake format.
- Real-Time Analytics– Observational data collected from various sources like apps, IoT devices and human interactions is an expanding data category. Real-Time Analytics manages high volumes of semi-structured data with shifting schemas.
It is important to acknowledge that most of these new features are still currently in preview. In this phase, the features afford an exciting glimpse into the future of data integration, management and analysis, providing the potential to redefine the handling of large-scale data operations.
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