The January 28 'Lunch & Learn' session by Denodo focused on rethinking data management strategies for 2021 through data virtualization. Presenters discussed the challenges organizations face in managing complex data environments and outlined how Denodo's solutions can enhance accessibility, security, and governance of data. The session highlighted the advantages of data virtualization in improving decision-making speed and reducing the burdens on IT through real-time and efficient data integration.

1. DENODO LUNCH & LEARN
January 28
RETHINK YOUR 2021 DATA
MANAGEMENT STRATEGY
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
Presentation 1: Rethink Your 2021 Data Management Strategy with Data Virtualization
Presentation 2: Product Demonstration
Q&A
Next Steps
Closing

4. Rethink Your 2021 Data Management Strategy with
Data Virtualization
Regional Vice President, Sales, ASEAN & Korea, Denodo
Elaine Chan

5. Denodo Introduction

6. The Leader in Data Virtualization
LEADERSHIP
● Longest continuous focus on data virtualization – since 1999
● Leader in Gartner Magic Quadrant for Data Integration Tools, 2020
● Leader in Forrester 2020 Wave – Enterprise Data Fabric, Q2 2020
● #2 in Gartner Peer Insights for Data Integration Tools
● Winner of numerous awards
DENODO OFFICES,
CUSTOMERS, PARTNERS
Palo Alto, CA.
Global presence throughout North America,
EMEA, APAC, and Latin America.
CUSTOMERS
~800+ customers, including many F500 and
G2000 companies across every major industry
have gained significant business agility and ROI.
FINANCIALS
Backed by $4B+ private equity firm.
50+% annual growth; Profitable.

7. Challenges of Data Management

8. 8
Business Challenges and Needs
• Need for faster, more accurate decision making
§ Significant increase in business speed & complexity of requirements
→ IT struggles to deliver in a timely fashion
• Ensure business continuity amidst technology evolution
§ Migration of legacy systems to cloud, modernization of data and
applications
• Increased risk from regulations, compliance, data
privacy and security
§ Exponential increase in regulations effecting data across geographies,
departments and industries

9. 10
IT Architecture is Unmanageable & Brittle because:
Business – IT Dilemma
IT responds by
loosely stitching
together
disparate data
sources
Any changes
break the flow
and affect
business
continuity
Business wants all of the data, NOW
– So, IT creates 100s to 1000s of brittle direct connections and
replicates large volumes of data
Inventory System
(MS SQL Server)
Product Catalog
(Web Service -SOAP)
BI / Reporting
JDBC, ODBC,
ADO .NET
Web / Mobile
WS – REST JSON,
XML, HTML, RSS
Log files
(.txt/.log files)
CRM
(MySQL)
Billing System
(Web Service -
Rest)
ETL
Portals
JSR168 / 286,
Ms Web Parts
SOA,
Middleware,
Enterprise Apps
WS – SOAP
Java API
Customer Voice
(Internet, Unstruc)

10. Solution to Data Management (Modern Approach)

11. 13
- Forrester Research, Inc., “The Forrester Wave: Enterprise Data Fabric, Q2 2020,”
June 2020
“Data Virtualization creates a data abstraction layer by
connecting, gathering, and transforming data silos to support
real-time and near-real time insights.”

12. 14
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

13. 15
How Does It Work?
Development
Lifecycle Mgmt
Monitoring & Audit
Governance
Security
Development Tools
and SDK
Scheduled Tasks
Data Caching
Query Optimizer
JDBC/ODBC/ADO.Net SOAP / REST WS
U
Customer 360
View
Virtual Data
Mart View
J
Application
Layer
Business
Layer
Unified View Unified View
Unified View
Unified View
A
J
J
Derived View Derived View
J
J
S
Transformation
& Cleansing
Data
Source
Layer
Base
View
Base
View
Base
View
Base
View
Base
View
Base
View
Base
View
Abstraction

14. 16
Data Virtualization Key Capabilities
• Data Abstraction: decoupling
applications/data usage from data
sources
• Data Integration without replication
or relocation of physical data
• Easy Access to Any Data, high
performance and real-time/ right-
time
• Dynamic Data Catalog for self-
service data services and easy
discovery
• Unified metadata, security &
governance across all data assets
• Data Delivery in any format with
intelligent query optimization that
leverages new and existing
physical data platforms
A logical data layer – a “data fabric” – that provides high-performance, real-time, and secure access
to integrated business views of disparate data across the enterprise

15. 17
Modern Data Virtualization
Data Virtualization enhanced with data management, automation and AI
ü Delivers data more quickly than direct queries
ü Leverages AI to accelerate performance and enhance the user experience
ü An active data catalog to explore and govern data in real time
ü Empowers data scientists with an integrated data science notebooks
ü Flexible support for hybrid and multi-cloud architectures
ü Employs automation to speed cloud deployment and management
ü Leverages SSO and fine grain permissions to secure data assets

16. 18
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.

17. 19
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.

18. 20
Denodo Confidential
Market trends and predictions
§ By 2023, organizations utilizing data fabrics to dynamically connect,
optimize and automate data management processes will reduce time to
data delivery by 30% and automate manual transformations by 45%.
Gartner - 2019 Magic Quadrant for Data Integration tools
Gartner - 2020 Magic Quadrant for Data and Analytics Service Providers
§ By 2023, data fabric enabled automation in data management and
integration will reduce the dependency for IT specialists by 20%.

19. Case Study

20. 22
Improves Customer Satisfaction with
Modern Data Management Approach
One of the oldest and largest reinsurers in the world. The company has offices in more than 25 countries and is one of the Forbes 2000
Global leading companies 2020 with APAC HQ in Singapore
Need & Challenges
Risk Management Department needed
a holistic view across all sub-areas of
risk in the life insurance, property
insurance, and investment lines of
business.
Existing architecture was based on
traditional data warehouse relying on
ETL processes, which can only support
3-4 major releases each year and
cannot handle high frequency of new
regulatory requirements for the
company.
Results in long lead times required for
every change and the risk management
dept could no longer deliver important
reports over time and caused growing
frustrations for the company and
customers.
“With the support of Denodo, we were able to test
the most important use cases for us in about two
weeks and very quickly came to the conclusion that
it is the solution that works best in our department”
- Head of IT Solutions
Development and QA
The Modern Approach
Implemented Denodo Data Virtualization
platform to improve the ease of data access.
Benefits
Allows for integration of new data sources
within a few minutes, enabling faster
feedback loop and fast prototyping also
enabled initial feedback to be sent in
response to user requests
The system now supports a continuous,
controlled release with changes 10 times a
day and reduced the processing time of user
inquiries from an average of two to three
weeks to a few hours, during which a first
draft can go to the user.
User satisfaction has also risen sharply
because users can specify their requests
with short iteration cycles and quickly get
exactly the results they need, without
lengthy feedback rounds

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

22. 32
Demo Scenario
Distributed Data:
§ Historical sales data offloaded to
Hadoop cluster for cheaper storage
§ Marketing campaigns managed in an
external cloud app
§ Customer details table, stored in the
DW
1) On-board and expose distributed data
through a single logical layer.
2) Publish a logical view calculating the
impact of a new marketing campaign
by country? Sources
Combine,
Transform
&
Integrate
Consume
Base View
Source
Abstraction
Sales Campaign Customer
Sales Evolution

23. 1. Data architectures are getting more complex, more diverse, and
more distributed.
2. Traditional data integration and management approaches are too
expensive, slow and complex.
3. Data virtualization makes it quick and easy to expose data from
multiple sources to your users while still maintaining governance and
security…
4. …and enables a wide range of use cases; from self-service analytics
and data services to centralized data governance and compliance.
Key Takeaways

24. Next Steps

25. 36
bit.ly/3qzWrl1

26. 37
bit.ly/38L7hys

27. Myth Busters: I’m Building a Data Lake,
So I Don’t Need Data Virtualization
Paul Moxon
SVP Data Architectures & Chief Evangelist, Denodo
Tuesday, 23 February 2021 | 10.00am – 11.00am SGT
REGISTER: bit.ly/3c62PMz

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