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Microsoft Fabric Updates Blog

  1. Atualizações
  2. Lakehouse

Demystifying Data Ingestion in Fabric: Fundamental Components for Ingesting Data into a Fabric Lakehouse using Fabric Data Pipelines

  • Headshot of article author junho 18, 2024 por RK Iyer 107 809 Visualizações

✎ Co-Author – Abhishek Narain Overview Building an effective Lakehouse starts with establishing a robust ingestion layer. Ingestion refers to the process of collecting, importing, and processing raw data from various sources into the data lake. Data ingestion is fundamental to the success of a data lake as it enables the consolidation, exploration, and processing … Continue reading “Demystifying Data Ingestion in Fabric: Fundamental Components for Ingesting Data into a Fabric Lakehouse using Fabric Data Pipelines”

Public Preview of Native Execution Engine for Apache Spark on Fabric Data Engineering and Data Science

  • Headshot of article author junho 12, 2024 por Estera Kot 217 629 Visualizações

The Native Execution Engine showcases our dedication to innovation and performance, transforming data processing in Microsoft Fabric. We are excited to announce that the Native Execution Engine for Fabric Runtime 1.2 is now available in public preview. The Native Execution Engine leverages technologies such as a columnar format and vectorized processing to boost query execution … Continue reading “Public Preview of Native Execution Engine for Apache Spark on Fabric Data Engineering and Data Science”

Fabric Change the Game: Embracing Azure Cosmos DB for NoSQL

In this new post of our ongoing series, we’ll explore setting up Azure Cosmos DB for NoSQL, leveraging the Vector Search capabilities of AI Search Services through Microsoft Fabric’s Lakehouse features. Additionally, we’ll explore the integration of Cosmos DB Mirror, highlighting the seamless integration with Microsoft Fabric. It’s important to note that this approach harnesses … Continue reading “Fabric Change the Game: Embracing Azure Cosmos DB for NoSQL”

Introducing Code-First AutoML and Hyperparameter Tuning: Now in Public Preview for Fabric Data Science

  • Headshot of article author abril 23, 2024 por Misha Desai 153 397 Visualizações

At the recent Fabric Conference, we announced that both code-first automated machine learning (AutoML) and hyperparameter tuning are now in Public Preview, a key step in making machine learning more complete and widely accessible in the Fabric Data Science. Our system seamlessly integrates the open-source Fast Library for Automated Machine Learning & Tuning (FLAML), offering … Continue reading “Introducing Code-First AutoML and Hyperparameter Tuning: Now in Public Preview for Fabric Data Science”

Introducing Optimistic Job Admission for Fabric Spark

We are excited to announce a new feature which has been a long ask from Synapse Spark customers, Optimistic Job Admission for Spark in Microsoft Fabric.This feature brings in more flexibility to optimize for concurrency usage (in some cases ~12X increase) and prevents job starvation. This job admission approach aims to reduce the frequency of … Continue reading “Introducing Optimistic Job Admission for Fabric Spark”