Watch full webinar here: https://bit.ly/3uiXVoC What is Data Virtualization and why do I care? In this webinar we intend to help you understand not only what Data Virtualization is but why it's a critical component of any organization's data fabric and how it fits. How data virtualization liberates and empowers your business users via data discovery, data wrangling to generation of reusable reporting objects and data services. Digital transformation demands that we empower all consumers of data within the organization, it also demands agility too. Data Virtualization gives you meaningful access to information that can be shared by a myriad of consumers. Watch on-demand this session to learn: - What is Data Virtualization? - Why do I need Data Virtualization in my organization? - How do I implement Data Virtualization in my enterprise? Where does it fit..?

1. DENODO LUNCH & LEARN
27 JANUARY
DATA VIRTUALIZATION:
AN INTRODUCTION

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

3. Agenda
1. Data Challenges in the 21st Century
2. What is Data Virtualization?
3. Benefits of Data Virtualization
4. How Data Virtualization Works?
5. Live Product Demonstration
6. Key takeaways
7. Q&A

4. Data Virtualization: An Introduction
Regional Vice President, Sales, ASEAN & Korea, Denodo
Elaine Chan

5. Challenges of Data Management

6. 7
•Social Media
•Mobile Devices
•Increased Internet
commerce/
transactions
•Networked
devices/sensors
New sources of data New repositories
•Images
•Streamed data
•Video/audio
•Parkay
New types
•Citizen analysts
•Customer demands
•AI/ML
•Predictive Analytics
•Data Science
Increase demand
•PDPA
•Reporting needs
(AML/KYC, HEDIS, etc.)
•GDPR
•HR, Privacy, Tax
Growing Regulatory concerns
•SaaS/PaaS
•Cloud-based data
•Governance
challenges
•More apps
Increasingly complex
More Data More Insight
21st Century Data Challenges
•Data Lake
•Snowflake
•Queues
TIME & Cost

7. 8
Information Provision Flow
Discovery/
Requirements
Analysis
Prototype
Feedback
Develop
Test
Feedback
Release
Same old story

8. 9
How do I handle data
Gartner – The Evolution of Analytical Environments
This is a Second Major Cycle of Analytical Consolidation
Operational Application
Operational Application
Operational Application
IoT Data
Other NewData
Operational
Application
Operational
Application
Cube
Operational
Application
Cube
? Operational Application
Operational Application
Operational Application
IoT Data
Other NewData
1980s
Pre EDW
1990s
EDW
2010s
2000s
Post EDW
Time
LDW
Operational
Application
Operational
Application
Operational
Application
Data
Warehouse
Data
Warehouse
Data
Lake
?
LDW
Data Warehouse
Data Lake
Marts
ODS
Staging/Ingest
Unified analysis
› Consolidated data
› "Collect the data"
› Single server, multiple nodes
› More analysis than any
one server can provide
©2018 Gartner, Inc.
Unified analysis
› Logically consolidated view of all data
› "Connect and collect"
› Multiple servers, of multiple nodes
› More analysis than any one system can provide
Fragmented/
nonexistent analysis
› Multiple sources
› Multiple structured sources
Fragmented analysis
› "Collect the data" (Into
› different repositories)
› New data types,
› processing, requirements
› Uncoordinated views

9. 10
Can You Consolidate All Your Data to a Single Location ?
Data warehouse Data lake Cloud

10. 11
Data Anti-Gravity
§ Geography
§ Ownership
§ Technology

11. 12
Data Is Distributed

12. 13
Typical Data Architecture

13. What is Data Virtualization..?

14. 16
Source: The Total Economic Impact™ Of Data Virtualization Using The Denodo Platform, 2021
Data Virtualization technology offers an elegant solution to many
of these issues by virtually integrating all enterprise data that is
siloed across the disparate systems and providing centralized
security, governance, and management capabilities so the data is
available to business users in real time.

15. 17
What is Data Virtualization?
Consume
in business applications
Combine
related data into views
Connect
to disparate data sources
2
3
1
DATA CONSUMERS
DISPARATE DATA SOURCES
Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users
Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word...
Analytical Operational
Less Structured
More Structured
CONNECT COMBINE PUBLISH
Multiple Protocols,
Formats
Query, Search,
Browse
Request/Reply,
Event Driven
Secure
Delivery
SQL,
MDX
Web
Services
Big Data
APIs
Web Automation
and Indexing
CONNECT COMBINE CONSUME
Share, Deliver,
Publish, Govern,
Collaborate
Discover, Transform,
Prepare, Improve
Quality, Integrate
Normalized views of
disparate data

16. 18
Modern Data Virtualization
Data Virtualization enhanced with data management, automation and AI
Ø Delivers data more quickly than direct queries
Ø Leverages AI to accelerate performance and enhance the user experience
Ø An active data catalog to explore and govern data in real time
Ø Empowers data scientists with an integrated data science notebooks
Ø Flexible support for hybrid and multi-cloud architectures
Ø Employs automation to speed cloud deployment and management
Ø Leverages SSO and fine grain permissions to secure data assets

17. 19
Six Essential Capabilities of Data Virtualization
4. Self-service data services
5. Centralized metadata,
security & governance
6. Location-agnostic
architecture for multi-cloud,
hybrid acceleration
1. Data abstraction
2. Zero replication, zero relocation
3. Real-time information

18. 20
1. Data abstraction
Abstracts access to disparate data sources.
Acts as a single virtual repository.
Abstracts data complexities like location,
format, protocols
…hides data complexity for ease of data access by business
Enterprise architects must revise their data architecture to meet
the demand for fast data.”
– Create a Road Map For A Real-time, Agile, Self-Service Data
Platform, Forrester Research

19. 21
2. Zero replication, zero relocation
…reduces development time and overall TCO
The Denodo Platform enables us to build and deliver data
services, to our internal and external consumers, within a
day instead of the 1 – 2 weeks it would take with ETL.”
– Manager, Enervus
Leaves the data at its source; extracts only what is
needed, on demand.
Diminishes the need for effort-intensive ETL
processes.
Eliminates unnecessary data redundancy.

20. 22
3. Real-time information
Provisions data in real-time to consumers
Creates real-time logical views of data across many
data sources.
Supports transformations and quality functions
without the latency, redundancy, and rigidity of legacy
approaches
…enables timely decision-making
Denodo’s data fabric design relies on data virtualization
to provide integrated data quickly to business users to
effect faster outcomes..”
– Gartner Magic Quadrant for Data Integration Tools, 18 August’ 2020

21. 23
4. Self-service data services
Facilitates access to all data, both internal and external
Enables creation of universal semantic models reflecting
business taxonomy
Connects data silos to provide best available information to
drive business decisions
…enables information discovery and self-service
Impressively quick turn around time to "unlock“ data from
additional siloes and from legacy systems - Few vendors (if any) can
compete with Denodo's support of the Restful/Odata standard -
both to provide data (northbound) and to access data from the
sources (southbound).”
– Business Analyst, Swiss Re

22. 24
5. Centralized metadata, security & governance
Abstracts data source security models and enables single-point
security and governance.
Extends single-point control across cloud and on-premises
architectures
Provides multiple forms of metadata (technical, business,
operational) to facilitate understanding of data.
…simplifies data security, privacy, audit
Our Denodo rollout was one of the easiest and most successful rollouts of critical
enterprise software I have seen. It was successful in handling our initial, security,
use case immediately, and has since shown a strong ability to cover additional
use cases, in particular acting as a Data Abstraction Layer via it's web service
functionality.”
– Enterprise Architect, Asurion

23. 25
6. Location-agnostic architecture for multi-cloud, hybrid acceleration
Optimizes costs by migrating data, applications, and analytics
workloads to cloud without impacting the business
Enables creation of hub architecture to support integration of
data across mixed workloads.
End-to-end management of migrations/promotions and
continuous delivery processes.
…enables cloud adoption
Impressively quick turn around time to "unlock“ data from
additional siloes and from legacy systems - Few vendors (if any) can
compete with Denodo's support of the Restful/Odata standard -
both to provide data (northbound) and to access data from the
sources (southbound).”
– Business Analyst, Swiss Re

24. 26
Reference Architecture
Reporting
Analytics
Data Science
Data Market Place
Data Monetization
AI/ML
iPaaS
Kafka
ETL
CDC
Sqoop
Flume
Raw
Data
Zone
Staging
Area
Curated
Data
Zone
Core
DWH
model
Data Warehouse
Data Lake
Data Virtualization Platform
Analytical Views
Data Science Views
λ Views
Real-Time Views
DWH Views
Hybrid Views
Cloud Views
Universal
Catalog
of
Data
Services
Centralized
Access
Control
Enterprise Data Fabric

25. 27
Reference Architecture
Reporting
Analytics
Data Science
Data Market Place
Data Monetization
AI/ML
iPaaS
Kafka
ETL
CDC
Sqoop
Flume
Raw
Data
Zone
Staging
Area
Curated
Data
Zone
Core
DWH
model
Data Warehouse
Data Lake
Data Virtualization Platform
Analytical Views
Data Science Views
λ Views
Real-Time Views
DWH Views
Hybrid Views
Cloud Views
Universal
Catalog
of
Data
Services
Centralized
Access
Control
Enterprise Data Fabric
DATA
VIRTUALIZATION

26. Benefits – Why Should I Care?

27. 33
Benefits of Using Data Virtualization
Easier & faster access to trusted data
• For Business Users
• Simplicity: Users don’t need to navigate the complexity of the architecture. Where is
data (on-prem, cloud, multi-cloud)? How to Access it? Which location has priority?
• Agility: All data is securely delivered from a single (virtual) system
• Accessibility: Data is accessible in a variety of formats (SQL, REST, OData, GraphQL)
and in a web-based Data Catalog, regardless of original format and location
• Common Semantic Layer: All users see the same definitions and data, providing data
consistency
• Governed Self-Service: Users can use their own tools (BYOT) to access and query the
data that is governed, secure, and trusted data.

28. 34
Benefits of Using Data Virtualization
Faster, cheaper, simpler, easier to secure and govern
• For IT
• Abstraction: Decouples storage and processing engines from the delivery of data
• Flexibility: Allows IT to change technologies and move data without service
interruptions
• Security: Centralized governance and security controls for all data assets
• Governance: The data accessed by the users can be governed, secured, and managed
so that users are accessing known, trusted, and approved data sets.
• Accelerated Delivery: As data is not be replicated to a staging area or data mart for
use, it is significantly quicker (up to 90% quicker) to deliver the data needed by the
users.

29. 35
Using The Denodo Platform; Published – 1st October 2021
Forrester Total Economic ImpactTM of Data Virtualization
Forrester Total Economic ImpactTM of Data Virtualization Using the Denodo Platform, October 1, 2021

30. 36
Total Economic Impact of Data Virtualization
“Denodo is the right tool for
collaborative, flexible work
and giving the business more
room to create flexible
applications for the future.
It’s proved so until today.”
— IT Manager, Manufacturing
ROI
408%
BENEFITS
$6.8M
PAYBACK
<6 months
Forrester has determined the
following three-year impact:

31. 37
Data Virtualization Use Cases
From Data Storage & Management, to Data Consumers, going through Data Governance & Security
Decision
(Real time)
Single View
(Customer 360)
Agile BI
(Self-service)
Data Science
(ML & AI)
APPS
(Mobile & web)
Mergers &
Acquisitions
Data
Marketplace
Compliances
(IFRS17, GRC)
Data
Security
APIfication
(& SQLification)
Unified Data
Layer
Agility
& Simplicity
Real-time
Delivery
Data
Abstraction
Zero
Replication
Data
Governance
Sophisticated
Optimizations
Logical Data
Warehouse/Lake
Big Data
Fabric
Hybrid
Data Fabric
Data
Integration
Data
Migration
Refactoring &
Replatforming
Data Consumption
Data Storage & Management
Data Governance, Manipulation & Access
Sales
HR
Executive
Marketing
Apps/API
Data
Science
AI/ML

32. How Data Virtualization Works?

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

34. Key Takeaways

35. Reduce Complexity, Time and Money
Data architectures
are getting more
complex, more
diverse, and more
distributed
Traditional data
integration and
management
approaches are too
expensive, slow and
complex
Multiple Use Case Support
Enables a wide range
of use cases; from
self-service analytics
and data services to
centralized data
governance and
compliance,
innovation platform.
Abstraction helps
Presenting unified
business consumable
informational assets.
Separation of storage
and access.
Governance
Governed access
across silos of data.
Agility
Faster provisioning
of business
consumable data
sets. Rapid
prototyping
capabilities and
empowerment of
business users.

36. Q&A

37. Next Steps

38. 45
Get Started Today
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free trial in the cloud marketplaces
CHOICE
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SUPPORT
Community forum AND remote sales
engineer
OPPORTUNITY
30 minutes free consultation with
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denodo.link/drive22

39. The Role of Logical Data Fabric in a
Unified Platform for Modern Analytics
Robin Tandon
Director of Product Marketing, Denodo
REGISTER NOW
denodo.link/WB2201
APAC Webinar | 17-Feb | 1.00pm SGT

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