Microsoft Fabric Updates Blog

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A turning point for enterprise data warehousing 

As executives plan the next phase of their data and AI transformation, the bar for analytics infrastructure continues to rise. Enterprises are expected to support traditional business intelligence, increasingly complex analytics, and a new generation of AI-driven workloads—often on the same data, at the same time, and with far greater expectations for speed and cost …

Microsoft OneLake and Snowflake interoperability (Generally Available)

Data teams today are under extraordinary pressure. Expectations around analytics and AI have never been higher, yet enterprise data continues to live across a patchwork of systems, tools, and platforms. The result is friction, duplication, and complexity, making it harder for data teams to provide a unified, real-time view of their business. Microsoft and Snowflake …

Bringing together Fabric Real-time Intelligence, Notebook and Spark Structured Streaming (Preview)

Coauthored by QiXiao Wang Building event-driven, real-time applications using Fabric Eventstreams and Spark Notebooks just got a whole lot easier. With the Preview of Spark Notebooks and Real-Time Intelligence integration — a new capability that brings together the open-source community supported richness of Spark Structured Streaming with the real-time stream processing power of Fabric Eventstreams …

Introducing Data Series Colors: tell clearer stories with Real-Time Dashboards (Generally Available)

A frequent request we receive from dashboard authors is the ability to have greater control over color settings. Until now, color assignments in real-time dashboards were largely automatic. While this worked for basic scenarios, it often fell short in operational and reporting use cases where color isn’t decoration—it’s meaning. Data Series Colors is a new …

Unlock Real-Time Insights from SAP with Fabric Real-Time Intelligence

Coauthors: Kevin Lam, Xu Jiang Challenge Organizations generate massive amounts of operational data, but most analytics solutions process this data hours or even days later. That delay can mean missed opportunities, slower decision-making, and less effective AI-driven solutions. Building a real-time analytics solution on SAP data isn’t easy. Traditional approaches rely on custom or third-party …