1. BI Strategies For The Cloud
Paresh Motiwala, PMP®

3. Setting up BI Infrastructure
BI Curious
Bi-Curious

4. Linkedin.com/in/pareshmotiwala Facebook.com/pareshmotiwala
BI Strategies For The Cloud
Linkedin.com/in/pareshmotiwala
Facebook.com/pareshmotiwala
@PASS_DBA_VC

5. BI Strategies For The Cloud

6. BI Strategies For The Cloud
DBA Manager at Nuance Communications
Leadership:
Boston Business Intelligence User Group
New England SQL Server User Group
PASS DBA Virtual Chapter
PASS Professional Development Virtual Chapter
Organizer:
Boston SQL Saturday
Boston BI SQL Saturday
Providence SQL Saturday
Boston: Global Azure Bootcamp
Principal:
Speaker: SQL Saturdays, PASS, SQL Rally, UGs, Global Azure Boot Camps, Boston Code Camp
Speaker Idol Finalist 2018 PASS Summit

7. BI Strategies For The Cloud
Upcoming Events
Boston BI SQL Saturday: March 30th

8. BI Strategies For The Cloud Who Should Attend?
DBAs
Developers
DevOps
Managers
CIOs
Infra folks
Finance folks
Cloud Enthusiasts

9. BI Strategies For The Cloud Points to consider
Decide on workflow/applications to move
Measure the current footprint
Benchmark current performance
Vendor selection
Design the architecture(Azure DW or SnowFlake)
SSRS
SSIS
Copy Data Management
Security/GDPR
Train the staff
Reassess

10. BI Infrastructure – Sources

11. BI Strategies For The Cloud Applications to Move:
Decide on workflow/applications to move
Check with vendor
Decide if you are overhauling it
Lift and Shift
Scope!

12. BI Strategies For The Cloud Footprint:
Measure the footprint:
CPU
Memory
Disk
Space
Type

13. BI Strategies For The Cloud Cloud Vendors

14. IaaS Vs PaaS
Courtesy: Meagan Longoria and Melissa Coates

17. Concerns about the Cloud
Technical:
✓ Uptime guarantees
✓ Performance
✓ Security
✓ Sharing of resources (multi-tenancy; noisy neighbors)
✓ Connecting legacy systems (hybrid/on-prem)

18. Concerns about the Cloud
Management and Planning:
✓ Sprawl of self-provisioned services
✓ Compliance, regulations, legal
✓ Data and intellectual property privacy
✓ Vendor lock-in/dependency
✓ Lack of cloud expertise
✓ Complexity
✓ Cost and ongoing expenses
✓ Difficult to estimate cost up-front

19. BI Strategies For The Cloud Data platform continuum
PaaS & SaaS
Azure SQL Database
Virtualized Database
SQL
Shared lower cost
IaaS
SQL Server in Azure VM
Virtualized Machines
Virtual
SQL Server Private Cloud
Virtualized Machine + Appliance
Objective: One of the first things to understand in any discussion of Azure versus on-premises SQL Server databases is that you can use it all. The Microsoft data platform leverages SQL Server technology and makes it available across physical on-premises machines, private cloud environments, third-party hosted private cloud environments, and public cloud. This enables you to meet unique and diverse business needs through a combination of on-premises and cloud-hosted deployments, while using the same set of server products, development tools, and expertise across these environments.
Talking Points:
As seen in the diagram, each offering can be characterized by the level of administration you have over the infrastructure (on the X axis), and by the degree of cost efficiency achieved by database level consolidation and automation (on the Y axis).
When designing an application, four basic options are available for hosting the SQL Server part of the application:
SQL Server on nonvirtualized physical machines
SQL Server in on-premises virtualized machines (private cloud)
SQL Server in Azure Virtual Machine (public cloud)
Azure SQL Database (public cloud)
Physical
SQL Server
Physical Machine (raw iron)
SQL
Dedicated higher cost
Higher administration
Lower administration

20. BI Strategies For The Cloud: Objectives
Easy Management
All Data in One System
Fast Elasticity
Unlimited Concurrency
Current technologies need constant attention, tuning, and tweaking for sub-optimal performance
Current technologies are optimized for relational or non-relational data, leading to silos and data marts
Ad-hoc queries are difficult to support with fixed resources
Concurrency and contention lead to queues, long query times, and frustrated users
© 2018 Snowflake Computing Inc. All Rights Reserved.

21. BI Strategies For The Cloud: 3 Roadblocks
’70s ‘80s ‘90s ‘00s ‘10s
Scale
Silos
Concurrency

22. BI Strategies For The Cloud: Scaling???
Traditional databases are inflexible
Usage varies, cost does not
Adding capacity is time consuming
Additional capacity is an expensive up-front purchase
Enormous wasted capacity
Usage
varies

23. BI Strategies For The Cloud: Types of Data
Well-Structured
Semi-Structured
{ }
Relational
Database
Blob Storage
(S3, Azure Files)
NoSQL
Hadoop

24. BI Strategies For The Cloud : Modern Concurrency
Data science
ETL and Processing
SQL analysts
BI & analytics tools
One resource for many groups of many people

25. BI Strategies For The Cloud: A Brand New Architecture
Cloud Services
Management
Optimization
Security
Availability
Transactions
Metadata
Data Science (L)
Data Transformation
(M)
Structured
Semi-Structured
Structured
Semi-Structured
SQL Queries (S)
BI/Reporting (Multi-Cluster M)
Flexible Cloud Storage For All Kinds of Data
Infinite
Concurrency
Unlimited Compute Clusters to Serve Every Use
Easy-to-use Service with No Management
© 2018 Snowflake Computing Inc. All Rights Reserved.
Multi-Tenant Snowflake Deployment

26. BI Strategies For The Cloud: Azure DW
Microsoft
Large amounts of data
You are already in Azure
You need relational and non-relational data
For large chunks of transactions
Not for small chunks of data/OLTP
Resides on Azure premium storage
Always divided into 60 slices
Gen 1 1006,000 DWUs
Gen 2 1,000 30,000 DWUs
DWU Max Concurrency, Memory Allocation and
PolyBase readers/writers
© 2018 Snowflake Computing Inc. All Rights Reserved.

27. BI Strategies For The Cloud BI Infrastructure – Reporting
OLTP
MDM/MDS
Data Warehouse
Reporting server
Delivery
Formats
Dupe
SSAS
SharePoint
Reporting server replica
Data Lake
Shareplexed
BigData

28. BI Strategies For The Cloud BI Infrastructure – ETL
OLTP
SSMS
BIDS/SSDT
Export/Import
Excel
Access
SSIS or SQL Server
Tools
Data Warehouse
Dupe
Shareplexed
SSIS or SQL Server
Data Lake
BigData

29. BI Strategies For The CloudBI Infrastructure – At a glance
MDM

30. BI Strategies For The Cloud Setting it up
Garner Exec buy-in
Define Measures
LOFT
Foundation
Agile/Tools
Constant Innovation
Reassess

31. BI Strategies For The Cloud - Security
GDPR
Inform
Involve
Secure
Train
Audit
Reassess

32. BI Strategies For The Cloud– Users
Inform
Involve
Collaborate
Train
Equip
Reassess

33. BI Strategies For The Cloud– Team
Business
Applications
Database
Project Mgt
Senior Management
Reassess

34. BI Strategies For The Cloud Source-Copy Data
Definition
Time Saving
Secure
Space
Saving
N/W Bandwidth
Reassess

35. BI Strategies For The Cloud – Measuring Success

36. BI Strategies For The Cloud Modern Data Warehouse
INGEST
STORE
PREP & TRAIN
MODEL & SERVE
Logs (unstructured)
Azure Databricks
Media (unstructured)
Azure Data Factory
PolyBase
Files (unstructured)
Azure Blob Storage
Azure SQL Data Warehouse
Azure Analysis Services
Power BI
Business/custom apps
(structured)
Microsoft Azure also supports other Big Data services like Azure HDInsight and Azure Data Lake to allow customers to tailor the above architecture to meet their unique needs.

37. BI Strategies For The Cloud Real time analytics
STORE
INGEST
PREP & TRAIN
MODEL & SERVE
Sensors and IoT
(unstructured)
Logs (unstructured)
Azure Databricks
Apache Kafka for HDInsight
Cosmos DB
Real-time apps
Media (unstructured)
Microsoft Azure supports other services like Azure HDInsight, Azure Data Lake, Azure IoT Hub, Azure Events Hub in various layers of the architecture above to allow customers a truly customized solution.
Files (unstructured)
Azure Data Factory
PolyBase
Business/custom apps
(structured)
Azure Blob Storage
Azure SQL Data Warehouse
Azure Analysis Services
Power BI
Microsoft Azure also supports other Big Data services like Azure IoT Hub, Azure Event Hubs, Azure Machine Learning and Azure Data Lake to allow customers to tailor the above architecture to meet their unique needs.

38. BI Strategies For The Cloud Hub & Spoke architecture for bi
INGEST
STORE
PREP & TRAIN
MODEL & SERVE
Business/custom apps
(structured)
Data Marts
SQL
Azure Databricks
Multiple Azure SQL Database instances
PolyBase
Logs (unstructured)
Azure Data Factory
Azure Blob Storage
Azure SQL Data Warehouse
Power BI
Media (unstructured)
Data Cubes
Multiple Azure Analysis Services instances
Files (unstructured)
Microsoft Azure supports other services like Azure HDInsight and Azure Data Lake in various layers to allow customers a truly customized solution.

39. BI Strategies For The Cloud Azure Databricks

40. BI Strategies For The Cloud Data Mart Consolidation
INGEST
STORE
MODEL & SERVE
PolyBase
RDBMS data marts
Azure Data Factory
Azure Blob Storage
Azure SQL Data Warehouse
Azure Analysis Services
Power BI
Hadoop
Microsoft Azure also supports other Big Data services like Azure HDInsight and Azure Data Lake to allow customers to tailor the architecture to meet their unique needs.

41. BI Strategies For The Cloud CHOOSING THE DATABASE
Managed Instance
Elastic databases
Single databases
Cloud-born SaaS applications
ISV  SaaS applications
Custom customer-facing applications
Employee-facing applications
Applies to
New SaaS providers
Existing SQL ISV re-architecting for SaaS
All entities
Enterprises building custom apps
Goal
Compete and replace on-premises competitor apps
Replace existing LOB packaged software with a SaaS solution
Scale as the customer base grows
Create or re-architect apps to cloud or use SaaS solutions
Needs
Hyper-scale, HADR, performance
Write code once
Predictable and flexible cost
SQL compatibility
Time to solution
Packaged LOB apps – delivered by ISVs
Objective: Microsoft worked closely with some customers during their initial onboarding to Azure SQL Database to learn how they used the service and take lessons back to our engineering team for future feature planning.
Talking Points:
During those engagements, we found that some kinds of customers found the feature set suited their needs well. For example, startups developing new cloud services often found that the combination of capacity on demand and reduced administrative overhead simplified their lives and allowed them to focus time on their core business.
Other customers had challenges in some areas related to tight performance requirements―perhaps for service a central API in a large, multi-tier database solution―that were not currently met by the Azure SQL Database service.
The feedback was that while some customers were very willing to accept higher performance variance to achieve a very low price point, other customers were more interested in specific performance guarantees so they could more easily build higher-level value on top of these databases.

42. BI Strategies For The Cloud Recommendation
Recommend one or more of the strategies.
Summarize the results if things go as proposed.
What to do next.
Identify action items.

43. BI Strategies For The Cloud Points to consider
Decide on workflow/applications to move
Measure the current footprint
Benchmark current performance
Vendor selection
Design the architecture
SSRS
SSIS
Copy Data Management
Security/GDPR
Train the staff
Reassess

44. Linkedin.com/in/pareshmotiwala Facebook.com/pareshmotiwala
BI Strategies For The Cloud Contact Information
Linkedin.com/in/pareshmotiwala
Facebook.com/pareshmotiwala
@PASS_DBA_VC

46. BI Strategies For The Cloud
Thank You
BI Strategies For The Cloud
Remember
Paresh
For
President
2020
Thank You

47. BI Strategies For The Cloud BI Infrastructure – Bibliography
Howsen, C. (n.d.). Successful Business Intelligence, Unlock the Value of BI & Big Data.
Kolb, J. (n.d.). Business intelligence in plain language: A practical guide to data mining and business analytics.
Sharda, R., & Delen, D. (n.d.). Business Intelligence: A Managerial Perspective.
White Paper- Technovision 2014 , Digital Transformation
by Capgemini
Microsoft’s explanation of Hadoop
BI news from Microsoft
Cloud Workloads presentation from Jose Valencia, Microsoft
Elastic Data Warehouse as a Service - Snowflake