The data and analytics industry is evolving, influenced by advances like generative AI, the rise of citizen analysts, and the growing importance of real-time autonomous actions. To reduce the complexity and cost of integrating new services into data estates, Microsoft introduced Microsoft Fabric, an AI-powered data analytics platform designed to seamlessly future-proof and improve strategies of company data.
Notably, Aurizon, Australia’s largest rail freight operator, used Fabric to upgrade its data and analytics system, aiming to streamline and simplify its architecture by removing legacy systems and undertaking analytics sophisticated predictions.
Microsoft Fabric promises to improve the way businesses manage and analyze their data, providing robust additions and customizable features to meet diverse organizational needs. These enhancements include a redesigned Real-Time Intelligence workload, which combines Synapse Real-Time Analytics and Data Activator to manage and act on high-volume, granular event streaming data. It also introduces new tools such as the Fabric Workload Development Kit, API for GraphQL, and user data functions to help developers build powerful solutions on the platform.
Aurizon reports significant benefits from using Microsoft Fabric, stating that the platform has facilitated predictive analysis and optimizations that are expected to drive business benefits in the near future. A study from Forrester Consulting backs up this sentiment, revealing that Microsoft Fabric customers experienced a three-year return on investment (ROI) of 379% with a payback period of less than six months.
Real-Time Intelligence functionality provides an end-to-end experience, enabling dynamic data transformation, real-time queries, and immediate action without the need to preload data. The introduction of Real-Time Hub allows users to efficiently manage and explore streaming data from various sources. This feature is currently in preview, enhancing capabilities for seamless, real-time data management.
Fabric was developed to be extensible, customizable, and open, allowing for easy creation and integration of custom workloads through the Fabric Workload SDK. This kit allows applications built on it to appear as native workloads in Fabric, ensuring a consistent user experience. Additionally, leading industry partners such as SAS, Esri, Informatica, Teradata and Neo4j already rely on Fabric. Key new features include the API for GraphQL and User Data Functions, which aim to streamline data requests and build more efficient applications using diverse Fabric data sources.
The Fabric Data Factory workload introduced data workflows, leveraging the Apache Airflow runtime to create, schedule, and monitor complex data pipelines. This allows organizations to orchestrate their data flows more efficiently using Python.
Microsoft also enhanced the OneLake unified data lake, expanding capabilities to connect to on-premises and network-restricted data sources. This feature aims to reduce data duplication and proliferation, enabling a more streamlined data management approach across multiple clouds and accounts.
Helping business users, Microsoft has made great strides with the general availability of Model Explorer and DAX Query View in Microsoft Power BI Desktop, aimed at helping analysts manage, analyze and share information more effectively . Additionally, Copilot in Fabric, now available to everyone, provides conversational language support for creating data feeds, building machine learning models, and visualizing results across multiple Fabric experiments.
A new AI feature, AI skills, is also in preview and is designed to deliver a conversational data Q&A experience, allowing users to ask questions and quickly receive context-rich answers. This feature respects existing security permissions and can incorporate organizational language and nuance to ensure relevant responses.
