Microsoft Fabric Updates Blog

Use Fabric Data Factory Data Pipelines to Orchestrate Notebook-based Workflows

Microsoft Fabric Data Factory’s data pipelines enable data engineers to build complex workflows that can orchestrate many different types of data processing, data movement, data transformation, and other activity types. In this post, I want to focus on some good practices when building Fabric Spark Notebook workflows using Data Factory in Fabric with data pipelines. …

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Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications

Microsoft Fabric’s Lakehouse helps us better unified management of enterprise-level data environments. In the process of transforming to AI, we cannot do without the assistance of these enterprise data. In my previous blog, I mentioned how to build RAG applications based on data in the Microsoft Fabric environment. In this post, I will introduce how …

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Microsoft Fabric December 2023 Update

Welcome to the December 2023 update.

We have lots of features this month including More styling options for column and bar charts, calculating distinct counts in Power BI running reports on KQL Databases, Changes to workspace retention settings in Fabric and Power BI, and many more.

Prebuilt Azure AI services in Fabric

During the recent Ignite 2023 event, we announced the public preview of prebuilt AI services in Fabric. This integration with Azure AI services, formerly known as Azure Cognitive Services, allows for easy enhancement of data with prebuilt AI models without any prerequisites.  Using AI services in Fabric has never been easier! In the past, you …

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Lakehouse vs Data Warehouse vs Real-Time Analytics/KQL Database: Deep Dive into Use Cases, Differences, and Architecture Designs

With the general availability of Microsoft Fabric this past Ignite, there are a lot of questions centered around the functionality of each component but more importantly, what architecture designs and solutions are best for analytics in Fabric. Specifically, how your data estate for analytics data warehousing/reporting will change or differ from existing designs and how to choose the right path moving forward. This article will be focused on helping you understand the differences between the Data Warehouse and Data Lakehouse, Fabric solution designs, warehouse/lakehouse use cases, and to get the best of both Data Warehouse and Data Lakehouse.