The webinar series addresses key challenges in modern data management, particularly regarding multi-cloud integration using data virtualization. Speakers highlight complexities, benefits, and solutions for managing data across various platforms and locations. Key takeaways emphasize the importance of data virtualization in simplifying access to data and supporting flexible data architecture.

1. DATA VIRTUALIZATION PACKED LUNCH
WEBINAR SERIES
Sessions Covering Key Data Integration Challenges
Solved with Data Virtualization

2. Multi-Cloud Integration with
Data Virtualization
Paul Moxon
VP Data Architectures & Chief Evangelist, Denodo

3. Agenda
1. Challenges of Modern Data Management
2. Multi-Cloud Challenges
3. Denodo’s Multi-Location Architecture
4. Product Demo
5. Q&A
6. Next Steps

4. Challenges of Modern Data
Management
4

5. 5
Challenges of Modern Data Management
Required expansion of Analytics
by growing consumers of data
Need for Agile
Self-Service BI
Increasing use
of third-party
data for
Information
Agility
Big Data
volumes
continue to
grow
Security and
Data Privacy
implications
becoming core
to data
strategy
Reduce or
eliminate Data
Latency
Providing data access irrespective
of Storage Location
Growth in
Hybrid &
Multi–Cloud
Deployments
Convergence
of Application
and Data
Integration

6. 6
Modern Data Architecture
DATA
VIRTUALIZATION

7. 7“Adopt the Logical Data Warehouse Architecture to Meet Your Modern Analytical Needs”.
Henry Cook, Gartner April 2018
DATA VIRTUALIZATION

8. 8
Cloud Deployment Models
Source: Denodo Global Cloud Survey 2019

9. 9
Cloud Deployment Models
32.66%
Multi-Cloud
Source: Denodo Global Cloud Survey 2019

10. IDC FutureScape: Worldwide Cloud 2018 Predictions
By 2020, over 90% of Enterprises Will Use Multiple
Cloud Services and Platforms

11. Multi-Cloud Challenges
11

12. Benefits of Multi-Cloud Strategy
• Flexibility
• Cost optimization
• Avoid vendor lock-in
• Regulatory compliance
• Geographical flexibility
12

13. Challenges of Multi-Cloud Strategy
• Complexity
• Duplication
• Increased costs
• Multiple security models
• Skill sets required
• Integration
13

14. Denodo’s Multi-Location
Architecture
14

15. 15
Multi-Location Architecture
• Denodo instances connected to each other
• Moving processing to data location
• Security and control localized
• Different countries, jurisdictions, etc.
• Global access without replicating data
• Denodo instances connected
• Denodo Solution Manager automates sharing
of metadata

16. 16
Multi-Location Architecture – Example
Delegating queries to instances in remote locations:
Asia
Data Center
(Hong Kong)
North America
Data Center
(New York)
Local
Sources

17. 17
Multi-Location Architecture – Example
Delegating queries to instances in remote locations:
Asia
Data Center
(Hong Kong)
North America
Data Center
(New York)
Local
Sources
Client

18. 18
Multi-Cloud Integration with data Virtualization
Amazon RDS,
AuroraUS East
Availability Zone
EMEA
Availability ZoneOn-prem
data center

19. 19
Multi-Cloud Integration with Data Virtualization

20. 20“Adopt the Logical Data Warehouse Architecture to Meet Your Modern Analytical Needs”.
Henry Cook, Gartner April 2018
DATA VIRTUALIZATION
On-prem
data center

21. Product Demonstration:
Multi-Cloud Integration
21

22. 22
Demo Scenario
U.S. Call Center
(Boise, ID)
Corporate HQ
(Los Angeles, CA)
DE Call Center
(Hanover, DE)
• U.S. Insurance company has entered European market via acquisition of
German company
• Need to access all customer data for reporting and analysis
• But keep PII data local to each country
• U.S. Customer data
• Redshift DW
• AWS (US East)
• DE Customer data
• Cosmos DB
• Azure (West Europe)

23. 23
Our Users and Their Needs
Torsten
Mary
Jane
Customer Services
(Germany)
Customer Services
(United States)
Data Analyst
(Corporate)
• Access to German customer data
• Unnecessary data hidden or masked
• e.g. customer ‘Steuer ID’, income, etc.
• No access to U.S. customer data at all
• Access to U.S. customer data
• Unnecessary data hidden or masked
• e.g. customer SSN, income, etc.
• No access to German customer data
• Access to all de-identified customer data
• PII data hidden
• Location data (zip/post code) is OK

24. 24
Multi-Location Data Access
Torsten
Mary
Jane
Corporate HQ
DATA VIRTUALIZATION

25. Demo
25

26. Key Takeaways
26

27. 27
Key Takeaways
FIRST
Takeaway
Data architectures more and more complex…and users shouldn’t
have to struggle navigating this complexity
SECOND
Takeaway
Data Virtualization allows user to find and access data wherever it
resides – in the Cloud, on-premise, in a data lake, in a data
warehouse, in an S3 bucket, in an Excel spreadsheet, …
THIRD
Takeaway
Data Virtualization enables organizations to build a modern,
flexible, and extensible data architecture that supports multi-Cloud
strategies and provides seamless access to all data assets

28. Q&A

29. 29
Next Steps
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30. Thank you!
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