Fabric

With the newest version of OneLake file explorer (v1.0.11.0) we bring a few updates to enhance your experience with OneLake. Excel Integration: Editing made Easy  With our latest release v1.0.11.0 of file explorer, we are excited to announce that you can now update your files directly using Excel, mirroring the user-friendly experience available in OneDrive. … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/onelake-file-explorer-update-via-excel-made-easy/" class="more-link">Continue reading<span class="screen-reader-text"> “OneLake File Explorer: Update via Excel made Easy”</span></a>

To get Copilot turned on for everyone in your organization, follow these steps: Sign in to Microsoft Fabric using your admin account credentials. Select Fabric settings and then from the menu select Admin portal. Select Tenant settings and scroll down the page to “Copilot and azure Open AI Service(preview)” and turn on Enabled On your … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/how-to-enable-copilot-in-fabric-for-everyone-2/" class="more-link">Continue reading<span class="screen-reader-text"> “How to enable Copilot in Fabric for Everyone”</span></a>

Microsoft Fabric provides a cloud-scale data warehouse to store your analytical data for dashboards and historical reporting. In Fabric Data Factory, there are a number of ways to query data, retrieve data, and execute commands from your warehouse using pipeline activities that can then be easily automated for unattended background execution. I’ll go left-to-right from … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/automate-fabric-data-warehouse-queries-and-commands-with-data-factory/" class="more-link">Continue reading<span class="screen-reader-text"> “Automate Fabric Data Warehouse Queries and Commands with Data Factory”</span></a>

In this blog post I show you how to grant users access to create Fabric items in a Fabric enabled workspace in Power BI.

Last year was a remarkable one for the Power BI community. We launched Microsoft Fabric, an end-to-end analytics platform that brings together data preparation, data warehousing, data engineering, data science, real-time analytics, and business intelligence in one unified SaaS foundation with one copy of data stored in OneLake. We also launched Power BI Copilot, making it easier to find insights and build reports using natural language. And our community of over 2 million members continued to engage on our forums, post ideas, join user groups, helping one another in their data journeys.

During November 2023, we unveiled the public preview of Copilot in Microsoft Fabric. This preview includes Copilot for Power BI, Data Factory and Data Science & Data Engineering. Since then, we have been gradually rolling this feature out and today, we are excited to announce that our Copilot preview is now available to all customers! With the Copilot preview, Microsoft … Continue reading “Copilot in Fabric (preview) is available worldwide “

If you are starting to enjoy using Microsoft Fabric more, especially the exciting new Direct Lake storage mode, you may find this simple tip useful to help monitor your semantic models. The idea behind this tip is to run a DMV (can be any DMV) on a regular basis against a semantic-model and accumulate results … Continue reading Use Fabric Notebook to monitor Power BI semantic models

Recently, I had two enterprise customers with whom I was in conversation about Microsoft Fabric and how it could complement their existing data landscape. Both of these customers have a data platfo…

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 … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/using-microsoft-fabrics-lakehouse-data-and-prompt-flow-in-azure-machine-learning-service-to-create-rag-applications/" class="more-link">Continue reading<span class="screen-reader-text"> “Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications”</span></a>

If you keep up with the latest developments in the data space, you will probably know that Microsoft Fabric has now reached general availability. One of the trickiest things we’ve had to come to terms with is how concurrency works and how to run multiple notebooks at once without errors.

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.

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 … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/prebuilt-azure-ai-services-in-fabric-2/" class="more-link">Continue reading<span class="screen-reader-text"> “Prebuilt Azure AI services in Fabric”</span></a>

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.

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 … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/using-microsoft-fabrics-lakehouse-data-and-prompt-flow-in-azure-machine-learning-service-to-create-rag-applications/" class="more-link">Continue reading<span class="screen-reader-text"> “Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications”</span></a>

Learn how you can implement a lakehouse in Microsoft Fabric.

In the many conversations I had over the past years, it is a returning topic to talk about complexity of bringing your CRM and ERP data together to create a 360-degree customer view. While doing bu…

Since Fabric went GA I’ve moved the small amount of stuff that we had running in Azure Synapse into Fabric notebooks. (Sadly a large amount of our data estate is still sat on prem with SSIS&#…

In this post, I will show you how to connect to your Microsoft Fabric Lakehouses and Warehouses from Python.

We’re happy to announce a new function in Power Query’s M language for reading data from Delta Lake tables: the DeltaLake.Table function. This function is now available in Power Query in Power BI Desktop and in Dataflows Gen1 and Gen2 and replaces the need to use community-developed solutions like this one by Gerhard Brueckl. Let’s … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/read-data-from-delta-lake-tables-with-the-deltalake-table-m-function/" class="more-link">Continue reading<span class="screen-reader-text"> “Read data from Delta Lake tables with the DeltaLake.Table M function”</span></a>

I recently needed to generate a quick visual inside a Microsoft Fabric notebook. After a little internet searching, I found there are many good quality charting libraries in Python, however it was going to take too long to figure out how to create a very specific type of chart. This is where Vega came to … Continue reading Create charts using Vega in Microsoft Fabric Notebook

A few blogs back I shared a technique using Power BI Profiler (or VS Code) to run and capture a trace over a refresh of a Power BI semantic model (the object formally known as a dataset). I’ve since received a lot of positive feedback from people saying how useful it was to visualize each … Continue reading Visualize Power BI Refresh using Semantic-link

In Nov 2023, Microsoft announced Microsoft Fabric’s general availability and Public Preview of Copilot in Microsoft Fabric. In a previous post, I explained what Copilot means to Power BI developers, which is valid for other Fabric developers such as data engineers and data scientists as Copilot for Fabric helps with those experiences as well. But … Continue reading Microsoft Fabric: Generating Reports with Copilot

SAP systems hold some of the most valuable data of many enterprises, large or small. Whether it is operational data in ERP systems like SAP ECC or SAP S/4HANA, data from SAP’s data warehouse suite of products like SAP BW or SAP Datasphere, or data from SAP’s SaaS solutions – a comprehensive view on the … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/integrate-your-sap-data-into-microsoft-fabric/" class="more-link">Continue reading<span class="screen-reader-text"> “Integrate your SAP data into Microsoft Fabric”</span></a>

Optimize Direct Lake fallback behavior in Power BI with XMLA. Direct Lake size limits, Tabular Editor, rowgroup

This blog post shows how to transform data in a Microsoft Fabric notebook using the data wrangler with a Py spark data frame.

Semantic Link adds support for the recently released OneLake integrated semantic models! You can now directly access data using your semantic model’s name via OneLake using the read_table function and the new mode parameter set to onelake. This approach ensures that no load is placed on Analysis Services, enabling efficient data retrieval and avoids putting … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/semantic-link-onelake-integrated-semantic-models/" class="more-link">Continue reading<span class="screen-reader-text"> “Semantic Link: OneLake integrated Semantic Models”</span></a>

As a reaction to an article from SQLBI this blog post shows an alternative way of detecting selection in Field Parameters and Calc Groups

Did you know you can use Tabular Editor with Fabric to build advanced Power BI semantic models? Find out some of the advantages that this approach can give you.

Learn how Microsoft Purview and Microsoft Fabric work together to empower data discovery and governance. Find out how access Fabric items.

Optimize Fabric notebook JSON visualization with panel, Bokeh, and pandas' json_normalize for interactive, efficient analysis