http://dataconf.com.ua/sergiy-lunyakin.php
Topic of presentation: Cloud BI with Azure Analysis Services
The main points of the presentation:
With Azure Analysis Services (Azure AS) we have a full set of PAAS and SAAS services like Azure SQL DWH, Azure SQL DB, Azure AS and Power BI for creating our BI solutions in the cloud. In this session, I will introduce Azure AS and how we can use it together with other Azure services for creating complete BI solution in the cloud.
http://dataconf.com.ua/index.php#agenda
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3. Agenda
• BI components and Azure
• Analysis Services in the cloud
• Performance levels
• Data sources and exploration
• Management and development
4. Traditional BI components and Azure
Data Factory
Azure SQL database
SQL DW
Function
s
Analysis Services
Power BI
5. Analytical
dashboards
Web & mobile apps
Operational reports
Insight
Data Management solution for analytics in
cloud
Model & ServePrep & Train
HDInsight /
Spark / ADLA
DATA INTELLIGENCE ACTION
Store
Azure Blobs
Ingest
Data Factory
Azure Machine Learning &
Machine Learning Server
Cosmos
DB
SQL Data
Warehouse
Analysis Services
Azure Data Lake
Event Hubs
IoT Hub
SQL
Database
Logs, Files and
media
(unstructured)
Business/Custom
apps
(structured)
Logs, Files, Web
Services
Sensors and
Devices
(unstructured)
Polybase
Azure Data Catalog
Data Governance
Azure Key Vault
Key Management
Azure ExpressRoute
Private Connections
Operations Management Suite
Monitoring
Excel
3RD PARTY TOOLS
6. Analysis Services in the cloud
• Fully managed SSAS Tabular engine in the Azure
Cloud (PaaS)
• 99.9% uptime SLA
• Scale Out (soon)
• Elastic Scale Up/Down
• Pause and resume resources
• Azure Active Directory & Azure B2B support
• Firewall
• Backup/restore
• Cloud and On-Premise (over Gateway) data sources
• Familiar tools (SSDT, SSMS, PowerShell)
7. Azure Analysis Services Architecture
Excel
Third party
BI tools
Cloud data sources
SQL Database
SQL
Data
Warehouse
Direct Query
Cached Model
Power BI
Power BI
Embedded (GA)
SQL Server
Oracle,
Teradata
Other
data sources
Power BI
Desktop
Visual Studio
Authoring and
development tools
On-premises
data sources
Direct Query
Cached Model
Gatewa
y
Other data
sources
Cloud
visualization tools
On-premises
visualization tools
Azure
Analysis Services
8. Org AAD Authentication
• Supports only Azure Active Directory
organizational accounts
• Supports AAD B2B (invite users from another AAD
tenant)
• Workaround for LiveId
• Create a new account in default AAD domain
(*.onmicrosoft.com)
• Set as Administrator during service provisioning
15. Explore your data and connection
• Connection to
asazure://<region>.asazure.windows.net/<serv
ername>
• Used port 443
• Latest client providers are required
Cloud On-premises
Power BI Service Power BI Desktop
Power BI Embedded – coming
soon
Excel
SSMS
16. Explore your data and connection
• SSMS - Enable Azure AD authentication for SSAS in SSMS 2016
[HKEY_CURRENT_USERSoftwareMicrosoftMicrosoft SQL
ServerMicrosoft Analysis ServicesSettings] "AS AAD Enabled"="True"
• Excel – Windows Authentication is not supported yet, User/Password only
• Power BI Service – connect from Power BI Desktop, publish to web.
Connection from web is not supported yet
• Impersonation
Cloud sources/On-Premises with SQL Authentication – Service Account.
On-Premises with Windows Authentication – User/Password, In-Memory
Only
17. Management and Development for AAS
• Azure Portal
• ARM Template
• PowerShell
• SSMS
• SSDT+DAX Editor
• DAX Studio
• Tabular Editor
18. Management and Development for AAS
• AAS Web Designer - Preview
• Create a new data model (Azure SQL DB/DW)
• Edit existed model
• Create relationships and measures
• GitHub integration
• Import Power BI model
• Backup and Restore from Blob Storage
21. Troubleshooting and monitoring
• Ensure that you use the latest drivers
• Clear Azure AD cache
• C:Users<user_name>AppDataLocal
• Delete the AADCacheOM or .IdentityService folder
• xEvents Trace
• Stream
• Custom solution to file (Christian Wade)
22. Summary
• PaaS Analysis Services Tabular engine
• Enterprise-grade data modeling in the cloud bi
solutions
• No CAPEX
• Low OPEX – pay for only what you use
• Go from conception to insight in hours
• Flexible scale
• Pausing and resuming
