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Fabric Data Engineering</h1> ">

Fabric Data Engineering

Run enterprise grade Spark jobs on all organizational data. Turn raw data into analytics—and AI-ready assets in OneLake.

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Overview

Overview

Features

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Customer stories

Resources

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OVERVIEW

Build and operate reliable data pipelines at scale</h2> ">

Build and operate reliable data pipelines at scale

Ingest and transform dataMaximize price performanceDevelop and ship efficientlyGovern and secureIntegrate and extend dataAccelerate with Copilot and AI

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Create a lakehouse fast

Easily create a lakehouse with managed storage, folders, and Delta tables in OneLake.

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Manage large-scale data

Ingest and transform large volumes of structured and unstructured data, using Fabric’s scalable Spark engine.

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Transform to Delta

Clean, join, and model data using PySpark or Spark SQL, and write ACID-compliant Delta tables.

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Consume your data from anywhere

Run TSQL, create Power BI reports, and build AI applications—all directly on your data. SQL

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Run workloads faster

Run Spark workloads faster with the native execution engine for optimized, vectorized processing.

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Speed up time to insights

Use materialized lake views to persist results and accelerate repeatable queries and pipelines.

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Scale compute automatically

Automatically adjust Spark resources to workload needs and avoid paying for idle compute.

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Caching for accelerated performance

Reduce notebook query latency with intelligent caching and optimized execution plans.

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Source control

Version notebooks and pipelines with Git to collaborate, review changes, and roll back safely.

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Streamline deployment

Promote artifacts across dev, test, and prod, and automate releases with governance.

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Choose how you build

Develop with VS Code, notebooks, or low-code tools. Fabric adapts to your workflow.

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Collaborate in notebooks

Work together in rich, interactive notebooks with visuals, shared resources, and built-in folders.

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Secure by design

Apply consistent security, access controls, and lineage across all data engineering workflows.

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Protect your data

Track lineage and apply governance policies across OneLake and Fabric workloads.

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Monitor and track performance

Monitor Spark applications, diagnose errors, and identify bottlenecks using built-in monitoring tools.

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Tap into the Fabric API

Create APIs over your data; connect applications and query multiple sources via GraphQL.

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Connect your apps

Connect applications directly to governed lakehouse tables and shared datasets.

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Run multisource queries

Query lakehouse, mirrored, and external data sources through a single endpoint.

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Automate and orchestrate processes

Schedule pipelines and notebooks and integrate triggers for end-to-end automation.

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Access Agentic Copilot in notebook

Use Copilot to generate Spark, SQL, and Python code; explain results; and accelerate notebook authoring.

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Debug and optimize code

Diagnose errors, optimize queries, and get code autocomplete with performance suggestions directly in your workflow.

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Call AI in your code

Apply AI-powered functions inline in pandas or Spark to enrich data with minimal setup.

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Accelerate data preparation workflows

Quickly clean and transform data using an interactive, notebook-native experience.

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FEATURES

Explore demo videos</h2> ">

Explore demo videos

Learn how these Data Engineering capabilities help teams move faster, simplify complex data work, and unlock insights others can use.

Run advanced enterprise analytics at scale

Experience integrated analytics

Accelerate insights with materialized lake views

Move from raw data to ML-ready with Copilot

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See how Fabric provides the most advanced engines for enterprise analytics.

Unite your data with built-in governance and discovery via the OneLake Catalog and Microsoft Purview.

See how materialized lake views speed up recurring queries on Delta tables by precomputing results, auto-refreshing updates, and delivering consistent, high performance analytics across Fabric.

Explore data, run experiments, and use Copilot-assisted notebooks across your data engineering and data science workflows.

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Pay only for Spark jobs you run</h2> ">

Pay only for Spark jobs you run

Enable Autoscale Billing to run Spark jobs on serverless, pay-as-you-go compute—and pay only for job runtime and scale independently of base Fabric capacity.

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CUSTOMER STORIES

Explore why organizations choose Fabric</h2> ">

Explore why organizations choose Fabric

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Fabric gives us a self-contained ecosystem…There’s no duplication of data, no multiple copies. Data lineage becomes better, data trust becomes better, and data quality becomes better.

Srimanth Rudraraju, Group Director, Engineering, Data Platforms, LSEG

80,000

Files processed daily

50%

Usage growth

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Previously, even with four hours of latency, we still faced inconsistency between source and destination. Now data flows from source to Fabric in two seconds and it is 100% accurate.

Aazath Raj Paramasivam, General Manager, Apollo Hospitals

25%

Drop in manual work

60%

Increase in order conversions

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We transitioned from Azure Synapse to Microsoft Fabric seamlessly, migrating 600+ notebooks and pipelines while consolidating 4,500+ data objects into 87 Fabric lakehouses. This enhanced overall data platform efficiency and reduced cost by 3.2x, enabling over 450 OBOS users to leverage Fabric for faster, deeper insights.

Dag Erlend, Delivery Manager, OBOS

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Resources

Learn more about Fabric Data Engineering</h2> ">

Learn more about Fabric Data Engineering

Explore more about Fabric Data Engineering through curated blogs, hands-on tutorials, and documentation. Learn best practices, discover new capabilities, and get practical guidance to build and optimize with confidence.

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Read Fabric Data Engineering documentation</h3> ">

Documentation

Read Fabric Data Engineering documentation

Dive deeper into technical details and see how Fabric Data Engineering works.

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Get the latest updates in the Fabric blog</h3> ">

Blog

Get the latest updates in the Fabric blog

Discover the latest features and announcements in Fabric data engineering.
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