Watch full webinar here: https://bit.ly/3corOL4 More and more organizations are adopting multi-cloud strategies to provide greater flexibility, cost savings, and performance optimization. Even when organizations commit to a single cloud provider, they often have data and applications spread across different cloud regions to support different business units or geographies. The result of this is a highly distributed infrastructure that makes finding and accessing the data needed for reporting and analytics even more challenging. The Denodo Platform Multi-Location Architecture provides quick and easy managed access to data while still providing local control to the 'data owners' and complying with local privacy and data protection regulations (think GDPR and CCPA). In this on-demand webinar, you will learn about: - The challenges facing organizations as they adopt multi-cloud data strategies - How the Denodo Platform provides a managed data access layer across the organization - The different multi-location architectures that can maximize local control over data while still making it readily available - How organizations have benefited from using the Denodo Platform as a multi-cloud data access layer

1. DENODO LUNCH & LEARN
MARCH 24
MULTI-CLOUD INTEGRATION
WITH DATA VIRTUALIZATION

2. Presenters for this Session
Chris Day
Director, APAC Sales Engineering, Denodo
Regional Vice President, Sales, ASEAN & Korea, Denodo
Elaine Chan

3. Agenda
1. Multi-Cloud Integration with Data Virtualization
2. Quiz
3. Product Demonstration
4. Q&A
5. Next Steps
6. Closing

4. Multi-Cloud Integration with Data Virtualization
Regional Vice President, Sales, ASEAN & Korea, Denodo
Elaine Chan

5. Challenges of Data Management

6. 6
Required expansion of Analytics
by growing consumers of data
Need for Agile
Self-Service BI
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
Increasing use
of third-party
data for
Information
Agility
Growth in
Hybrid &
Multi–Cloud
Deployments
Convergence
of Application
and Data
Integration
Challenges of Modern Data Management
Source: Denodo Global Cloud Survey 2020

7. Multi Cloud Data Strategy

8. 10
Stages of a Cloud Journey
All systems are on-premise.
Using traditional databases,
etc. – maybe an on-premise
Hadoop cluster. Lots of ETL
pipelines. Using Denodo for
integrated view of data.
Systems are now on-premise and in the Cloud – initially
hosted by the preferred Cloud provider. The data is
balanced across the different environments although the
bulk of the data is initially on-premise. ETL-style data
movement is often used to move data from on-premise
systems to Cloud-based analytical systems. The systems are
more complex and users need to be able to find and access
data from on-premise and Cloud locations.
In reality, this is a hybrid/multi-Cloud environment,
with systems in multiple Clouds (AWS, Azure, GCP,
Salesforce, etc.) and a few legacy systems still on-
premise. The environment is even more complex as
workloads can move between Cloud providers to take
advantage of new capabilities, cost optimization, etc.
Users still need to find and access data in this
environment.
System modernization initiatives move applications and
data to the Cloud. For critical systems, this migration is
typically a phased approach over a period of months (or
years).
On-
Premise
Transition
to Cloud
Hybrid
Single
Cloud
Multi-
Cloud
(Note: Most organizations skip this stage and go straight to
multi-Cloud)
Systems have moved to the Cloud (although some systems
are still on-premise and cannot be moved to the Cloud).
The ‘center of gravity’ for data is solidly in the Cloud. More
processing and data integration occurs in the Cloud. Data
is moved from on-premise systems to the Cloud using ETL.
User data access is predominantly from Cloud systems.

9. 11
• Flexibility
• Cost optimization
• Avoid vendor lock-in
• Regulatory compliance
• Geographical flexibility
Benefits of Multi-Cloud Strategy

10. 12
Key Challenges of Multi-Cloud Strategy
• Complexity
• Duplication
• Increased costs
• Multiple security models
• Skill sets required
• Integration

11. Hybrid Data integration with
Logical Data Fabric

12. 14
Hybrid Data Integration with a Logical Data Fabric
Common access point for both on-premise
and cloud sources
• Access to all sources as a single schema
with no replication: Virtual data lake
• Enables combination of data across
sources, regardless of nature and location
• Allows definition of common semantic
model
• Single security model and single point of
enforcement
Active
Directory
Data Center
Cloud

13. 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

14. 16
Delegating queries to instances in remote locations:
Asia
Data Center
(Hong Kong)
North America
Data Center
(New York)
Local
Sources
Multi-Location Architecture – Example

15. 17
Multi-Location Architecture – Example
Asia
Data Center
(Hong Kong)
North America
Data Center
(New York)
Local
Sources
Client
Delegating queries to instances in remote locations:

16. 18
Multi-Cloud Integration with Data Virtualization
Amazon RDS,
Aurora
US East
AvailabilityZone
EMEA
Availability Zone
On-prem
data center

17. 19
Benefits of Data Virtualization in a Multi-Cloud Environment
q Native Cloud Support for Better Efficiency and Faster Integration
• Denodo Platform can run natively on each cloud platform and scale depending
on type of workload
• Centralize console automates and simplifies management of complex
deployments.
• Seamless integration between multiple clouds or mix of public and private
clouds
q Minimize Cloud Egress Costs while Enhancing Performance
• Each Denodo Platform works with localized data in each cloud and avoids data
movement.
• Reduces cost in data management in a multi-cloud environment.
q Provides Data Governance and Security in a Multi-Cloud World
• Single comprehensive view of data with active monitoring
• Support for containerization and Kubernetes accelerates the overall
management
• Data Governance rules and data lineage visibility

18. 20
“Adopt the Logical Data Warehouse Architecture to Meet Your Modern Analytical Needs”.
Henry Cook, Gartner April 2018
DATA VIRTUALIZATION
On-prem
data center

19. Case Study

20. 22
BHP Achieves Increased Business Agility with Denodo
Business Scenario
BHP wanted to manage business risk by integrating data systems across multiple
geographies. But this was a time consuming and expensive operation.
BHP’s global application landscape provides limited and restricted reusability of
existing data platforms which lead to:
• Repeated engineering effort to access the same data sources for different
data solutions.
• Long lead times to ingest or load data before a data solution can be
developed.
• Project-centric data repositories are created to provide a consolidated set of
data for a specific purpose, increasing total cost of ownership, complexity and
variability in data interpretation.
BHP is among the world's top
producers of major commodities
including iron ore, coal and copper.
They have a global presence with
operations and offices across
Australia, Asia, UK, Canada, USA
and central and south America.

21. 23
Reference Architecture
Data Source
ü Application data stores
ü SaaS / Cloud Applications
ü Application interfaces
ü Manual data sources
Data Virtualization Platform Consumers
ü Enterprise &
Regional Data
Stores
Self Service Data Catalogue
Query
Optimisation
Query
Development
Data
Federation
Data
Discovery
Abstraction / Semantic Layer
Security Layer
Kerberos Delegation + Encryption in Transit + Extensive Auditing
Secure
Faster
Connect to data stores or direct to source Get access to the right data, fast.
Self service
Flexible protocols
ü Analytics
ü Self Service
ü Business Intelligence
ü Transactional Applications
ü Bring your own tool
Built using
technology by

22. 24
BHP Solution: Rapid virtualisation of multiple data sources using Data Virtualization Platform.
This resulted in reduced project cost and time delays present in the project’s original solution
design.
Original Design Final Design
Benefits
• Materialized data integration no
longer required.
• Faster iterations on data
transformation and dashboard
development.
• All required datasets published
and available standalone as
reusable data assets.
Source 1
Source 2
Source 3
Data Mart Dashboard
Source 1
Source 2
Source 3
Denodo Dashboard

23. 25
BHP’s Multi Location Architecture Implementation of Denodo for Enhanced Query
Federation to Local Data Sources
Every Data Virtualization cluster is connected to local
data sources, and is the access point for local
consumer apps such as BI and analytics tools. Each
Data Virtualization cluster has visibility of the datasets
available from all other clusters, and requests this data
from it's peer cluster as required by end users
Brisbane
Perth
Santiago
Houston
Cloud
Tenancy
Data
Lake
Data
Mart
Data
Mart
Analytics
Analytics
Analytics

24. Product Demonstration
Director, APAC Sales Engineering, Denodo
Chris Day

25. 29
Demo Scenario
Tim
Mary
Jane
Manager
(South Region)
Manager
(North Region)
Data Analyst
(Corporate)
• Access to Southern Region Employee data
• Unnecessary data hidden or masked
• e.g. monthly salary, bonus rate, DOB
& email address
• No access to Northern Region data at all
• Access to Northern Region Staff data
• Unnecessary data hidden or masked
• e.g. monthly salary, bonus rate, DOB &
email address
• No access to Southern Region data at all
• Access to all de-identified employee data
• PII data hidden
• Access to data in all locations (North & South)

26. 30
Tim
Mary
Jane
Corporate HQ
DATA VIRTUALIZATION
Multi-Location Data Access

27. South - Oracle North - Snowflake
Differences in tables
Different Table
Names
Different Field
Names
Different values
/ reference

28. North - Snowflake
South - Oracle Standarardised views
Same Naming
Convention
Same Field
Names
Standardised
Values

30. Next Steps

31. 36
bit.ly/3rBEVxn

32. 37
bit.ly/2Pj0fJU

33. Thanks!
www.denodo.com info@denodo.com
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