{"id":22064,"date":"2025-09-23T11:59:21","date_gmt":"2025-09-23T09:59:21","guid":{"rendered":"https:\/\/www.pkf-attest.es\/tecnologia\/novedades-itc\/microsoft-fabric-novedades-2025-2\/"},"modified":"2025-09-23T11:59:21","modified_gmt":"2025-09-23T09:59:21","slug":"microsoft-fabric-novedades-2025","status":"publish","type":"novedades-itc","link":"https:\/\/www.pkf-attest.es\/tecnologia\/en\/novedades-itc\/microsoft-fabric-novedades-2025\/","title":{"rendered":"Microsoft Fabric News 2025: AI and Unified Analytics"},"content":{"rendered":"\n
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The Microsoft Fabric 2025 news<\/strong> shows how this platform is consolidating as a strategic solution within Microsoft’<\/strong>s technology ecosystem. Since its launch in 2023, Fabric<\/strong> offers a unified environment for the data lifecycle, integrating analytics, governance, storage<\/strong> and artificial intelligence<\/strong>. In this article, we review the key new features of Microsoft Fabric 2025<\/strong> and how they impact companies looking to maximize the value of their data<\/strong>.In this paper we review recent developments in Microsoft Fabric<\/strong> and discuss their impact on organizations looking to maximize the value of their data<\/strong>.<\/p>\n\n\n\n

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1. Microsoft Fabric recent developments 2025<\/h2>\n\n\n\n
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1.1 OneLake compatibility with Apache Iceberg<\/h3>\n\n\n\n

One of the most notable innovations is OneLake<\/strong> ‘s ability to access Delta Lake<\/strong> tables using Apache Iceberg-compliant<\/strong> readers. This extends interoperability with the modern data ecosystem<\/strong>, as Iceberg is an open standard<\/strong> increasingly adopted in big data<\/strong> environments.<\/p>\n<\/div><\/div>\n\n\n\n

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1.2 Artificial Intelligence in the service of data engineering<\/h3>\n\n\n\n

AI capabilities<\/strong> are incorporated and accessible with very little code. Data engineers can now apply classification<\/strong> tasks , text generation and automatic content summaries<\/strong>, streamlining processes and improving productivity.<\/p>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n

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1.3 Fuzzy Matching in SQL<\/h3>\n\n\n\n

Data cleansing and debugging<\/strong> is one of the biggest challenges in any project. To this end, Fabric has introduced fuzzy string matching<\/strong> capabilities directly into its SQL databases<\/strong>, simplifying the management of inconsistent data.<\/p>\n<\/div><\/div>\n\n\n\n

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1.4 Geospatial Integration with ArcGIS GeoAnalytics<\/h3>\n\n\n\n

Fabric Spark<\/strong> has been integrated with ArcGIS GeoAnalytics<\/strong>, opening the door to advanced geospatial analysis<\/strong> and more accurate insights from geographic data.<\/p>\n<\/div><\/div>\n\n\n\n

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1.5 SQL Database enhancements in Fabric<\/h3>\n\n\n\n

The SQL databases within Fabric have received several optimizations:<\/p>\n\n\n\n