SQL Data Warehouse

Official Documentation

Service Description

With SQL Data Warehouse, Data Warehouse solutions can be set up flexibly and their resources can be adapted to the specific data evaluation requirements. Compute and storage services can be scaled independently of one another, allowing the compute resources to be extended, reduced, or suspended while retaining the storage systems (for relational data or non-relational Blob storage).

Getting Started

  1. 5/24/2017, Mva
    When you need to scale your data warehouse's storage and processing capabilities in minutes, not months, you need a cloud-based massively parallel processing solution. In...
  2. 9/28/2016, Video, 1:03:40
    Learn how SQL Data Warehouse can help you succeed with a complex hybrid architecture or deployment in Microsoft Azure. Deep views on integration with Azure services such as...
  3. 9/26/2017, Video, 1:14:36
    Did you know that *almost everything* tastes better with pesto? That’s especially true when you are dining on data with a high-carb, Petabyte scale, cloud data warehouse...
  4. 10/2/2018, Video, 1:15:06
    Modern data warehouses has the need to both handled relational data as well as non-structured information. In this session you will learn how modern data architectures...
  5. 9/28/2017, Video, 1:12:13
    Microsoft Azure provides a broad range of services for working with data. Using these services well requires knowing at least a little bit about all of them. In this session,...

Latest Content

Subscribe to News about SQL Data Warehouse


Web Content

SQL Data Warehouse Documentation

1. Overview
     1.1. About SQL Data Warehouse
     1.2. SQL Data Warehouse architecture
     1.3. Data warehouse units
     1.4. Cheat sheet
     1.5. Best practices
     1.6. Capacity limits
     1.7. FAQ
2. Release Notes
     2.1. December 2018
     2.2. October 2018
     2.3. September 2018
     2.4. August 2018
     2.5. July 2018
     2.6. June 2018
     2.7. May 2018
     2.8. April 2018
3. Quickstarts
     3.1. Create and connect
          3.1.1. Portal
          3.1.2. PowerShell
     3.2. Pause and resume
          3.2.1. Portal
          3.2.2. PowerShell
     3.3. Scale
          3.3.1. Portal
          3.3.2. PowerShell
          3.3.3. T-SQL
4. Concepts
     4.1. Security
          4.1.1. Overview
          4.1.2. Access control
          4.1.3. Firewall rules
          4.1.4. Virtual network service endpoints
          4.1.5. Authentication
          4.1.6. Azure AD
          4.1.7. Logins and users
          4.1.8. Multi-factor auth
          4.1.9. Auditing
          4.1.10. Column-level security
          4.1.11. Row-level security
     4.2. Data loading
          4.2.1. Overview
          4.2.2. Best practices
          4.2.3. Columnstore compression
     4.3. Development
          4.3.1. Overview
          4.3.2. Best practices
          4.3.3. Tables
      Data types
      Distributed tables
      Replicated tables
          4.3.4. T-SQL language elements
      Stored procedures
      Transactions Best Practices
      User-defined schemas
      Variable assignment
     4.4. Querying
          4.4.1. Dynamic SQL
          4.4.2. Group by options
          4.4.3. Labels
     4.5. Workload management
          4.5.1. Resource classes & workload management
          4.5.2. Memory & concurrency limits
     4.6. Manageability & monitoring
          4.6.1. Overview
          4.6.2. Scale, pause, resume
          4.6.3. Resource utilization & query activity
          4.6.4. Data protection
          4.6.5. Recommendations
          4.6.6. Maintenance schedule
          4.6.7. Troubleshoot
     4.7. Maintenance schedules
          4.7.1. Overview
          4.7.2. View maintenance schedule
          4.7.3. Change maintenance schedule
     4.8. Integration
          4.8.1. Overview
          4.8.2. SQL Database elastic query
5. How-to guides
     5.1. Secure
          5.1.1. Configure Azure AD auth
          5.1.2. Conditional access
          5.1.3. Virtual network rules by PowerShell
          5.1.4. Enable encryption - portal
          5.1.5. Enable encryption - T-SQL
          5.1.6. Threat detection
     5.2. Load Data
          5.2.1. New York taxi cab data
          5.2.2. Contoso public data
          5.2.3. Azure Data Lake Storage Gen1
          5.2.4. Azure Databricks
          5.2.5. Data Factory
          5.2.6. SSIS
          5.2.7. Load WideWorldImporters
     5.3. Develop
          5.3.1. Overview
          5.3.2. Connection strings
          5.3.3. sqlcmd
          5.3.4. Query with SSMS
          5.3.5. Query with Visual Studio
          5.3.6. Install Visual studio
     5.4. Manage workload
          5.4.1. Analyze your workload
     5.5. Monitor and tune
          5.5.1. Monitor your workload
          5.5.2. Upgrade to Gen2
          5.5.3. Monitor Gen2 cache
          5.5.4. Restore your data warehouse
          5.5.5. Automate performance levels
     5.6. Integrate
          5.6.1. Use machine learning
          5.6.2. Build data pipelines
      Connect with Fivetran
      Get started with Striim
      Add an Azure Stream Analytics job
          5.6.3. Build dashboards and reports
      Configure SQL Database elastic query
      Visualize with Power BI
6. Reference
     6.1. T-SQL
          6.1.1. Full reference
          6.1.2. SQL DW language elements
          6.1.3. SQL DW statements
     6.2. System views
     6.3. Gen2 lower compute tier
     6.4. PowerShell cmdlets
     6.5. REST APIs
7. Resources
     7.1. Azure Roadmap
     7.2. Forum
     7.3. Pricing
     7.4. Pricing calculator
     7.5. Feature requests
     7.6. Service updates
     7.7. Stack Overflow
     7.8. Support
     7.9. Videos
     7.10. Partners
          7.10.1. Business intelligence
          7.10.2. Data integration
          7.10.3. Data management

Web Pages

Content Type
Build 2016 Workshops: Azure Data Services Lab

Online Training Content

Date Title
5/24/2017 Delivering a Data Warehouse in the Cloud
12/11/2015 Deliver an Elastic Data Warehouse as a Service


Tool Description
Scale Azure SQL Data Warehouse Scale Azure SQL Data WarehouseThis is a simple runbook that will allow you to scale your Azure SQL Data Warehouse.Depending on your goals with Azure SQL Data Warehouse, at time it is important to scale up and down depending the incoming workload or amount of data. In Automation,
Resume Azure SQL Data Warehouse Resume Azure SQL Data WarehouseThis is a simple runbook that will allow you to resume a Azure SQL Data Warehouse.Resuming as part of a ETL/ELT Data WorkflowWe commonly get asked if there is some way that an Azure SQL Data Warehouse can be resumed on a schedule. Using this, you ca


Date Title Length
Enterprise BI with SQL Data Warehouse and Azure Data Factory
Making AI real with SQL Server Azure databases and Azure big data analytics services - GS005
Microsoft Power BI: Unify all your data and deliver powerful insights with - BRK2061
In the security trenches of Azure SQL Database and Azure SQL Data Warehouse - BRK3149
Turbocharged analytics with SQL Data Warehouse Gen2 - BRK3186
Azure Databricks for data engineers and data developers - BRK3313
Rubikloud's journey to build the modern data warehouse with Azure SQL Data Warehouse - BRK2303
Modern Data Warehousing on Azure – Learnings from large implementations - BRK3307
Azure SQL Data Warehouse tips and tricks - THR2181
Rubikloud's journey to build the modern data warehouse with Azure SQL Data Warehouse - BRK2303

Page 1 of 10