Build ingestion, transformation, storage and reporting in one platform — OneLake, Fabric pipelines, notebooks and Power BI explained, plus how it compares with Azure Data Factory.
✍️ Azure Trainings trainers⏱ 4 min read📅 Updated 11 October 2026
Microsoft Fabric lets you ingest, transform, store, schedule and report on data in one SaaS platform. All data lives in OneLake (Delta Parquet). You bring data in with pipelines, Dataflow Gen2, mirroring, eventstreams or shortcuts, transform it with Spark notebooks, T-SQL or Dataflow Gen2, and report on it in Power BI. Fabric’s Data Factory is the next generation of Azure Data Factory, and DP-700 is the certification for it. This Microsoft Fabric for Data Pipelines guide explains each part in simple steps.
One workspace for every pipeline job — no servers to set up.
Step 1Databases, files, streams
Ingest
Step 2Spark, SQL, dataflows
Transform
Step 3OneLake
Store
Step 4Schedules & alerts
Orchestrate
Step 5Power BI
Report
⚡ Short answer
In many companies data sits in separate tools and storage, creating silos and duplicate copies. Fabric keeps one governed copy and removes most infrastructure work, so teams focus on the pipelines. Want to learn this hands-on? Join our Azure Data Engineer Training in Hyderabad.
Storage
OneLake: one storage layer for everything
🗂️
One data lake
Every Fabric tenant gets OneLake. All workloads read and write the same data.
📄
Open format
Data is stored as Delta Parquet, an open format.
🔗
Shortcuts
Point to data in ADLS Gen2, Amazon S3 and more — without copying. This point matters for anyone looking at Microsoft Fabric for Data Pipelines.
Building blocks
Fabric components used in pipelines
🚚
Data Factory in Fabric
Pipelines, copy jobs and Dataflow Gen2 for ingestion and orchestration.
⚡
Data Engineering
Lakehouses and Spark notebooks for big transformations.
🏢
Data Warehouse
SQL warehousing on top of OneLake.
📡
Real-Time Intelligence
Eventstreams and eventhouses for streaming and live analytics.
📊
Power BI
Dashboards and reports on the same data.
🔐
One security model
Shared permissions and governance across every component. Keep this in mind when you plan for Microsoft Fabric for Data Pipelines.
Step 1 · Ingest
How data ingestion works in Fabric
↔️ Swipe the table sideways
MethodBest forPipelines + copy activityScheduled batch loads from databases, files and SaaS appsDataflow Gen2Low-code ingestion and cleaning with Power QueryMirroringNear real-time copies of Azure SQL or Cosmos DB in OneLakeEventstreamsStreaming data, e.g. from Azure Event HubsShortcutsUsing existing data in place without moving it
The drag-and-drop pipeline designer feels familiar if you know Azure Data Factory. Learners often ask us about this part of Microsoft Fabric for Data Pipelines.
Step 2 · Transform
How to transform data in Fabric
📘 Ways to transform
Spark notebooks (PySpark, Spark SQL)T-SQL in the WarehouseDataflow Gen2 (low-code)Delta Lake tablesBronze / Silver / Gold layers
🧪 Practise
• Load a CSV into a Lakehouse with a pipeline
• Clean it in a notebook and save a Silver Delta table
• Build a Gold sales table with T-SQL
• Connect Power BI with Direct Lake It is one of the simple basics of Microsoft Fabric for Data Pipelines.
🧭 Want to build your first Fabric pipeline with guidance? Our trainers walk you through it in live labs. Learn Microsoft Fabric for Data Pipelines with live labs.
PointAzure Data FactoryData Factory in FabricTypeSeparate Azure PaaS servicePart of the Fabric SaaS platformStorageYou connect your own storageOneLake built inLow-code transformationMapping data flowsDataflow Gen2 (Power Query)Best forExisting Azure data platformsNew, unified analytics projects
Learn Fabric with a trainer See our and Azure Data Engineer training — hands-on labs, real projects and DP-700 preparation. Our course covers Microsoft Fabric for Data Pipelines end to end.
Azure Data Factory is a separate integration service. Fabric includes its own Data Factory plus storage, Spark, warehousing and Power BI in one platform.
You can learn Microsoft Fabric for Data Pipelines in our live classroom batches near JNTU/KPHB or in live online batches with Azure Trainings. Book a free demo class to see how we teach before you join.
Yes. This Microsoft Fabric for Data Pipelines guide is reviewed by our trainers and was last updated in October 2026.
🎓
Written by the Azure Trainings training team
Based on what we teach in our batches and see in real projects. Last updated 11 October 2026. We review this Microsoft Fabric for Data Pipelines guide regularly. Spotted something outdated? Tell us on WhatsApp.
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