This document provides best practices for migrating enterprise business intelligence (BI) solutions to Microsoft Azure. It outlines a three-phase migration approach: 1) "lift and shift" existing on-premises solutions to Azure virtual machines (VMs), 2) transition to using Azure platform as a service (PaaS) offerings while optimizing the VM infrastructure, and 3) build a fully cloud-native solution using Azure SQL Database and other PaaS services. Key activities covered include setting up the Azure environment, enabling networking and connectivity, migrating Analysis Services, staging/data warehousing, and ETL/ELT processes. The document also discusses enabling big data and real-time analytics scenarios in the cloud.

1. Migrating Enterprise BI to Azure
Best Practices
Wlodek Bielski

2. SQLSat Kyiv Team
Eugene Polonichko
Oksana Tkach
Oksana Borysenko
Denis Reznik
Mykola Pobyivovk
Yevhen Nedashkivskyi

3. Sponsors

4. Session will begin very soon :)
▪ Please complete the evaluation form from
your pocket after the session. Your feedback
will help us to improve future conferences
and speakers will appreciate your feedback!
▪ Enjoy the conference!

5. ▪ MCSD: Azure Solutions Architect
▪ MCSE: Cloud Platform and Infrastructure
▪ MCSE: Data Management and Analytics
▪ AWS Certified Solution Architect
▪ Google Professional Data Architect
▪ Google Professional Data Engineer
About me

6. Agenda
▪ Setting up Azure environment
▪ Networking, VPN and on-prem connectivity
▪ Migrating Analysis Services
▪ Migrating Staging / DWH
▪ Migrating ETL/ELT
▪ Enabling Big Data scenarios

7. SETTING UP AZURE
ENVIRONMENT

8. Azure purchasing options
▪ Free Trial
▪ Pay-as-you-Go
▪ Open Licensing
▪ Enterprise Agreement
▪ Cloud Solution Provider (CSP)

9. Dev/Test offering

10. Setting up Azure environment
▪ Dev/Test + Prod subscriptions
▪ Design multiple Resource Groups
▪ bi-prod
▪ bi-test
▪ bi-dev
▪ bi-common
▪ Networking (VNet, VPN)
▪ Might be costly to change later

11. NETWORKING
AND CONNECTIVITY

12. Networking part
▪ Point-to-Site VPN – quick start
▪ Site-to-Site VPN – will take time
▪ ADF v2 – Self-Hosted IR
▪ On-premises Gateway
(Analysis Services and Power BI)

13. VPN: Hub and Spoke topology

14. MIGRATION JOURNEY

15. Migration Roadmap
Starting
point
SQL 2008
R2
Integration
Services
Analysis
Services
Reporting
Services
Phase
1
SQL
Server
IaaS
Integration
Services
IaaS
Analysis
Services
IaaS
Reporting
Services
IaaS
Phase
2
SQL
Server
IaaS
Azure Data
Factory v2
with SSIS
Azure
Analysis
Services
Power BI
Phase
3
Azure SQL
DB / DWH
Azure Data
Factory v2
Azure
Analysis
Services
Power BI
Database ETL/ELT OLAP Reporting

16. Phase 1: Lift & Shift
Starting
point
SQL 2008
R2
Integration
Services
Analysis
Services
Reporting
Services
Phase
1
SQL
Server
IaaS
Integration
Services
IaaS
Analysis
Services
IaaS
Reporting
Services
IaaS
Phase
2
SQL
Server
IaaS
Azure Data
Factory v2
with SSIS
Azure
Analysis
Services
Power BI
Phase
3
Azure SQL
DB / DWH
Azure Data
Factory v2
Azure
Analysis
Services
Power BI
Database ETL/ELT OLAP Reporting

17. Main objectives
▪ Migrate solution to VM(s)
▪ Take advantage of Azure IaaS services
▪ Setup secure and manageable environment
▪ Gain confidence

18. Lift & Shift options
▪ Backup-restore
▪ Data Migration Assistant
▪ IaaS – Windows template
▪ IaaS – SQL Server templates
▪ SQL Database Managed Instances
▪ License considerations

19. Data Migration Tools
▪ Data Migration Assistant
▪ Supports both scenarios
▪ On-premises -> IaaS -> PaaS
▪ Azure Database Migration Service
▪ Managed service for migrations at scale

20. PaaS services coverage
Covered
▪ Database Engine
(SMP / MPP)
▪ Analysis Services
▪ Integration Services
(via ADF)
Not covered
▪ SQL Server Agent
▪ Reporting Services
▪ Master Data Services
▪ Data Quality Services
…Managed Instance?

21. SQL Database Managed Instance

22. Infrastructure recommendations
▪ Plan for PaaS from the beginning
▪ Decouple services to separate VMs
▪ Use Premium managed disks
▪ Less burden with storage accounts (leftovers)
▪ Consider 2/4 TB disks (P40/P50)
▪ Azure Backup supports up to 16 data disks
▪ Azure Backup + Recovery Vault
▪ Use both (VM + disks/data)

23. Licensing considerations
▪ Pay-as-you-Go vs BYOL
▪ BYOL: 2008 R2+ are supported
▪ Consider SQL Server Developer Edition
▪ Consider memory-optimized VMs (G- / M-)
for Analysis Services Tabular
▪ Dev/Test subscriptions

24. Cost control recommendations
▪ Start small ☺
▪ Cloudyn – Azure Cost Management
▪ Consider Auto-Shutdown
▪ Reserved instance? Commitment vs flexibility
▪ DEMO – Azure Portal

25. Phase 2: Transition
Starting
point
SQL 2008
R2
Integration
Services
Analysis
Services
Reporting
Services
Phase
1
SQL
Server
IaaS
Integration
Services
IaaS
Analysis
Services
IaaS
Reporting
Services
IaaS
Phase
2
SQL
Server
IaaS
Azure Data
Factory v2
with SSIS
Azure
Analysis
Services
Power BI
Phase
3
Azure SQL
DB / DWH
Azure Data
Factory v2
Azure
Analysis
Services
Power BI
Database ETL/ELT OLAP Reporting

26. Main objectives
▪ Start using PaaS services
▪ Optimize IaaS infrastructure
▪ Understand and control costs

27. PaaS recommendations
▪ Start with Analysis Services – quick win
▪ Consider Azure SQL DB for DWHs < 1 TB
▪ Redesign ETL/ELT in phases
▪ Start with SSIS runtime
▪ Rewrite to pure ELT afterwards
▪ Orchestration instead of linear pipelines

28. Analysis Services deployment options
Multidimensional
▪ On-premises
▪ IaaS (BYOL)
▪ IaaS (SQL Server template)
Tabular
▪ On-premises
▪ IaaS (BYOL)
▪ IaaS (SQL Server template)
▪ Azure Analysis Services
▪ Power BI Premium
(de facto)

29. Azure Analysis Services
▪ Scaling up / out – finally!
▪ Pricing tiers
▪ Replicas
▪ Managed backups
▪ Expensive service – use with care
▪ REST API
▪ Can be automated via Logic Apps / Functions

30. SSAS: On-premises Data Gateway

31. Azure Data Factory v2
▪ Great orchestration tool with simple GUI
▪ Integrated Git support – easy versioning
▪ Runs SSIS (lots of other engines as well!)
▪ Supports ARM templates
▪ Not an ETL tool actually!

32. Power BI vs SSRS
▪ Power BI has limited support for pinning
SSRS reports
▪ Paginated reports likely to be supported
in future Power BI releases
▪ Plan for leveraging Power BI
from moment of IaaS migration
▪ Keep SSRS on small separate VM if needed

33. Phase 3: Cloud Native
Starting
point
SQL 2008
R2
Integration
Services
Analysis
Services
Reporting
Services
Phase
1
SQL
Server
IaaS
Integration
Services
IaaS
Analysis
Services
IaaS
Reporting
Services
IaaS
Phase
2
SQL
Server
IaaS
Azure Data
Factory v2
with SSIS
Azure
Analysis
Services
Power BI
Phase
3
Azure SQL
DB / DWH
Azure Data
Factory v2
Azure
Analysis
Services
Power BI
Database ETL/ELT OLAP Reporting

34. Main objectives
▪ Operate pure PaaS solution
▪ Get ready for Azure DWH with ELT
▪ Enable Big Data / real-time scenarios

35. Main activities
▪ Migrating to Azure SQL Database
▪ Getting rid of SSIS / ETL
▪ Rewriting new ELT orchestrations
▪ Minimizing VM workloads

36. Beyond classical DWH/BI
▪ HDInsight
▪ Data Lake Storage / Analytics
▪ Databricks
▪ .. Data Factory to orchestrate them all!

37. Wrap-up
▪ Phased approach
▪ Organization needs to learn new ways
▪ Not too fast..
▪ ..but it’s just the right time to start!

38. Thank you!

39. Sponsors