August 28, 2024 von Jason Himmelstein 57.540 Ansichten
Welcome to the August 2024 Update. Here are a few, select highlights of the many we have for Fabric. V-Order behavior of Fabric Warehouses allows you to manage the V-Order behavior at the warehouse level. Monitor ML Experiments from the Monitor Hub allows you to integrate experiment items into Monitoring Hub with this new feature. …
Anomaly Detector, one of Azure AI services, enables you to monitor and detect anomalies in your time series data. This service is based on advanced algorithms, SR-CNN for univariate analysis and MTAD-GAT for multivariate analysis and is being retired by October 2026. In this blog post we will lay out a migration strategy to Microsoft Fabric, allowing …
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Problem Statement In the previous blog on Profiling Microsoft Fabric Spark Notebooks with Sparklens, we covered how to run Sparklens to profile and tune the performance of your spark notebooks in Microsoft Fabric. In that blog, we used a custom Sparklens JAR. The Sparklens JARs available in the Maven Central repo supports only the Spark …
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Author: Deepak Gundavaram Exploration of Microsoft Fabric’s CI/CD Features In today’s rapidly evolving digital and AI landscape, Microsoft Fabric plays a crucial role in managing and automating data integration and analytics processes. As a comprehensive data platform, Fabric offers robust CI/CD capabilities, particularly for data pipelines. These capabilities enable efficient tracking of changes, seamless collaboration, …
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Fabric Mirroring ingests and replicates data continuously in near real-time from sources such as Azure Cosmos DB, Azure SQL Database, Snowflake into Microsoft Fabric. However, it is currently restricted to the above data sources. This blog explains how we can extend Fabric mirroring to an on-prem SQL Server database as a source, using a combination of SQL Server Transactional replication and Fabric Mirroring.
