A Guide to Making the Most of your SQL Skills Using Microsoft Fabric

#fabcon2026 #session #thursday #sql-fabric #data-warehousing #sql-skills #learning #microsoft #fabcon2026-session

Description

Don't start over. Learn how SQL professionals can leverage their existing skills in Microsoft Fabric. No need to learn PySpark or new data engineering tools. Discover how SQL powers Lakehouses, Warehouses, Real-Time Intelligence, and Notebooks. See why, for many tasks, SQL is not only compatible but often the most efficient way to build modern, scalable, intelligent data solutions in Fabric.

Key Takeaways

Is this real SQL Server or something new I must learn?
Warehouse Architecture
Architecture of Fabric Data Warehouse - Microsoft Fabric | Microsoft Learn
Warehouse vs. SQL Database
Lakehouse and SQL Analytics Endpoint
Influence our SQL roadmap and ensure

My Notes

Action Items

Resources & Links

Slides

A Guide to Making the
Most of Your SQL Skills
Using Microsoft Fabric
Shabnam Watson
Principal consultant, ABI Cube
Shabnam Watson
Microsoft Data Platform MVP
Data Consultant . Speaker . Author
Azure Data & AI . Microsoft Fabric . Power BI
LinkedIn: /in/shabnamwatson
Blog: shabnamwatson.com
YouTube: @ShabnamWatson
Agenda
SQL capabilities in Fabric
SQL Database
Warehouse
Lakehouse
Real Time Intelligence
Not a SQL syntax session!
Microsoft Fabric
AI
OneLake
Purview
Fabric Tenant-Capacity-Workspace Architecture
Fabric Tenant
Supporting T-SQL
Read + Write
Mostly Read
Data Warehouse
Lakehouse (SQL
Analytics Endpoint)
SQL Database
RTI
SQL database
Why SQL Database
Incredibly easy to get started with
Azure SQL DB in SaaS
Ideal engine for OLTP/ App Development
Lift and shift
Full T-SQL support
Common Questions from SQL Professionals
Is this real SQL Server or something new I must learn?
Can I use my existing T-SQL skills (procedures, transactions,
indexes)?
Is my data stored as files?
How does this fit into Fabric analytics without moving data?
SQL Analytics Endpoint
SQL Analytics
endpoint
SQL
database
Read-only SQL for Analytics
Near real-time
Incremental replication
inserts/updates/deletes
Delta Parquet in OneLake
OneLake
SQL Skills You Already Use
Core T-SQL
Programmability
SELECT, INSERT,
UPDATE,
DELETE
Stored
procedures
JOINs,
subqueries,
CTEs (WITH)
GROUP BY,
HAVING,
ORDER BY
User-defined
function
Transactions &
Reliability
Indexes &
Performance
Security &
Governance
BEGIN TRAN,
COMMIT,
ROLLBACK
Clustered and
non-clustered
indexes
Logins, users,
roles
ACID
compliance
Query plans &
optimization
Permissions
(GRANT, DENY)
Row-level
locking and
isolation levels
Familiar
performance
tuning patterns
Integration with
Entra ID
Views
Triggers
Common DBA Question
Where do I choose DTUs / vCores / service tiers?
Can I pause, scale, or resize the database?
What is the size limit?
Performance and scaling are managed by Fabric capacity, not
per-database DTUs or vCores.
Fabric allocates compute automatically based on workload.
Backups & Restore
Automated backups are built-in, no backup jobs, no manual backups.
Full backups every week.
Differential backups every 12 hours.
Transaction log backups approximately every 10 minutes.
Cannot restore files somewhere else.
High Availability & Resiliency
Zone redundancy is handled by the platform
Availability, resiliency, and fault tolerance are abstracted away and
managed by Fabric.
SQL Audit Logs
Authentication attempts and access control changes
Data access and modification operations
Schema changes and administrative activities
Permission changes and security configurations
Query Tools
SQL Query Editor
External tools: SSMS
SQL Database Demo
Warehouse
Warehouse
Minimal setup
Data stored once in OneLake (open Delta format)
Compute provided by a distributed SQL engine
Storage and compute scale independently
No data movement required across Fabric workloads
Warehouse Architecture
Unified Query Optimizer
Distributed Query Processor
Query
Execution
Engine
OneLake
Storage
Compute Pool 1: SELECT
Compute Pool 2: DML
Delta Tables
Architecture of Fabric Data Warehouse - Microsoft Fabric | Microsoft Learn
Statistics
Data is stored in OneLake
Delta (Paquet) = Column Storage (~CCI)
Statistics automatically created and maintained
Non clustered indexes can be added
Constraints non enforced
Warehouse: Backup & Restore
Built-in Recovery (No DBA-Managed Backups)
Restore In-Place
Restore points are metadata-based and reference data stored in
OneLake
RESTORE POINTS
SQL Audit Logs
Authentication attempts and access control changes
Data access and modification operations
Schema changes and administrative activities
Permission changes and security configurations
Query Tools
Visual Query Editor
SQL Query Editor
Data Preview
T-SQL Notebooks
External tools: SSMS
SQL Notebooks
Warehouse Demo
Warehouse vs. SQL Database
Feature
SQL DB in Fabric
Warehouse
Storage cap
4 TB per DB
No fixed cap
File visibility
Abstracted
Delta files in OneLake
Workload
OLTP
OLAP
Log management
Platform-managed
Delta transaction log
Lakehouse
Lakehouse
Primary storage layer for large-scale analytical data
Structured and unstructured data
SQL Analytics Endpoint : Read-only T-SQL
Ideal for exploration, reporting, and consumption using familiar SQL
Writes and transformations happen elsewhere (Spark, pipelines,
Warehouse)
Lakehouse and SQL Analytics Endpoint
Lakehouse
SQL analytics endpoint
Lakehouse Demo
KQL Database
SQL support in Real Time Itelligence
RTI is KQL-first, designed for streaming and event data
SQL is supported as a limited subset (exploration only)
Useful for basic filtering and aggregations for SQL users
Not intended for full T-SQL, complex workloads
RTI Demo
Sound off.
The mic is all yours.
Influence the product roadmap.
Join the Fabric User Panel
Join the SQL User Panel
Share your feedback directly with our
Fabric product group and researchers.
Influence our SQL roadmap and ensure
it meets your real-life needs
https://aka.ms/JoinFabricUserPanel
https://aka.ms/JoinSQLUserPanel