ottobre 30, 2024 da Patrick LeBlanc 48.951 Visualizzazioni
Welcome to the October 2024 Update! Here are a few, select highlights of the many we have for Fabric this month. API for GraphQL support for Service Principal Names (SPNs). Introducing a powerful new feature in Lakehouses: Sorting, Filtering, and Searching capabilities. An addition to KQL Queryset that will revolutionize the way you interact with …
Microsoft Fabric allows enterprises to bind different data sources through OneLake, and data engineer can call a unified API for different business scenarios to complete data analysis and data science. This article will describe how to allow data scientists to use Semantic Kernel with Lakehouse in Microsoft Fabric In Microsoft Build 2023, Microsoft proposed the …
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Introduction / Recap Welcome to the final entry of our 3-part series on improving performance for historical data loads! In the first two entries we dove deep into the technical weeds to demonstrate the capabilities of Data Pipeline Expression Language. Part 1: Data Pipeline Performance Improvements Part 1: How to convert a time interval (dd.hh:mm:ss) …
Welcome to the July 2023 update. We have features in Core, Synapse, Data Factory, Data Activator, Community, and Power BI. Contents Core Help Pane Monitoring Hub improvements Admin Microsoft Public Preview Default Sharing On by Default Effective July 5th, 2023 OneLake OneLake file explorer update with support for switching organizational accounts Item sharing Synapse Data …
We are excited to announce that Direct Lake datasets now support XMLA-Write operations. Now you can use your favorite BI Pro tools and scripts to create and manage Direct Lake datasets.
In a lot of scenarios, you want to only get new data from your sources and append it to your data destination to report over. With Dataflows Gen2 that comes with support for data destinations, you can setup your own pattern to load new data, replace some old data and keep your reports up to …
Continue reading “Wondering how to incrementally amass data in your data destination? This is how!”
