Microsoft Fabric
Data Engineering
The comprehensive guide to unified analytics, from OneLake fundamentals to the latest February 2026 innovations.
OneLake: The “OneDrive for Data”
OneLake is automatically provisioned with every Fabric tenant, serving as the single, unified location for all analytics data. Built on ADLS Gen2 concepts, it eliminates data duplication and provides consistent access patterns across your entire organization.
Single Copy Architecture
No data duplication across engines. One copy, multiple access patterns.
Delta Lake Format
Open format with ACID transactions, time travel, and versioning built-in.
Unlimited Scale
Automatically scales with your data needs without manual provisioning.
OneLake
Unified Data Lake
All engines access the same data without duplication
Lakehouse Architecture
Best of Both Worlds: Combine the flexibility of data lakes with the performance of data warehouses.
Lakehouse Mode
Apache Spark Processing
- PySpark & Scala Notebooks
- DataFrame Operations
- ML Model Training
- Unstructured Data Processing
df.groupBy(“region”).sum(“amount”).show()
SQL Analytics Endpoint
T-SQL Queries & Reporting
- Full T-SQL Support
- Power BI DirectLake
- JDBC/ODBC Connections
- SQL-based Reporting
FROM sales
GROUP BY region
Delta Lake Format with V-Order Optimization
All Fabric engines read and write Delta format with V-Order optimization for fast reads across Spark, SQL, and Power BI. No vendor lock-in, full industry standard compliance.
What’s New
The latest innovations in Microsoft Fabric Data Engineering, from enhanced developer experiences to advanced security features.
VS Code: Integration
EnhancedOpen and edit Fabric Notebooks directly within VS Code:. Changes sync automatically between local and remote workspaces.
Notebook Debug
PreviewPlace breakpoints and debug Notebook code with the Synapse VS Code: extension. Supports Fabric Runtime 1.3 (GA).
Fabric Connection
PreviewGet Data feature in Notebooks for simpler, safer access to frequently used sources like Blob Storage and PostgreSQL.
High Concurrency Mode
PerformanceNew high concurrency mode for Lakehouse operations enables multiple concurrent read/write operations.
OneLake Data Access Roles
PreviewGranular, role-based security for Lakehouse folders with intuitive UI for managing permissions.
Granular REST APIs
PreviewDiscrete Get, Create, and Delete role operations for automation-friendly security workflows.
Forecasting Service
ML-driven proactive resource provisioning ensures Spark sessions start in seconds with Starter Pool. No more waiting for cluster startup.
Core Components
Explore Fabric Data Engineering building blocks
Unified Storage Foundation
The Lakehouse serves as the storage layer for all workloads, combining tables and files in OneLake with dual access modes.
Interactive Development
Multi-language notebooks with Apache Spark integration for exploratory data analysis, transformation, and machine learning.
Orchestration & ETL
Visual workflow designer with 200+ connectors for cloud and on-premises sources. Schedule-based and event-based triggers.
Low-Code Transformation
Power Query Online with 300+ transformations. Visual interface for data preparation without writing code.
Medallion Architecture
Bronze-Silver-Gold pattern for incremental data quality and structure
Bronze Layer
Raw DataStore raw data exactly as it arrives from sources. Immutable, append-only storage preserving original data structure and full lineage.
Silver Layer
Cleaned & EnrichedClean, validate, and enrich data from Bronze. Apply business rules, standardize formats, remove duplicates, and enforce schemas.
Gold Layer
Curated AnalyticsBusiness-ready data optimized for analytics and reporting. Aggregated, modeled, and structured for consumption by Power BI, ML models, and applications.
Security & Governance
February 2026 brings granular security controls with OneLake Data Access Roles, extending to mirrored items and providing comprehensive protection.
Mirrored Item Security (GA)
Row-Level Security (RLS) and Column-Level Security (CLS) now available on all mirrored item types.
Outbound Access Protection
Workspace-level rules for outbound connections to ensure only trusted sources are used.
Layered Permission Model
Security at multiple levels: Workspace roles → Item permissions → Compute permissions → OneLake data access.
Security Layers
Workspace Roles
Admin, Member, Contributor, Viewer
Item Permissions
Read, Write, Execute per item
Compute Permissions
Spark, SQL endpoint access controls
OneLake Data Access
Folder and table-level security (New)
Ready to Transform Your Data Platform?
Start your journey with Microsoft Fabric Data Engineering. From free trials to certification, we’ve got you covered.
Explore Fabric Trial
Sign up for free and create your first Lakehouse
Microsoft Learn
Complete learning paths and hands-on tutorials
FabCon Atlanta 2026
March 16-20, 2026 – Premier community event
DP-700 Certification
Microsoft Fabric Data Engineer Associate
