Watch full webinar here: https://bit.ly/3saONRK COVID-19 has pushed every industry and organization to embrace digital transformation at scale, upending the way many businesses will operate for the foreseeable future. Organizations no longer tolerate monolithic and centralized data architecture; they are embracing flexibility, modularity, and distributed data architecture to help drive innovation and modernize processes. The pandemic has compelled organizations to accelerate their digital transformation initiatives and look for smarter and more agile ways to manage and leverage their corporate data assets. Data governance has become challenging in the ever-increasing complexity and distributed nature of the data ecosystem. Interoperability, collaboration and trust in data are imperative for a business to succeed. Data needs to be easily accessible and fit for purpose. In this session, Denodo experts will discuss 5 key trends that are expected to be top of mind for CIOs and CDOs; - Distributed Data Environments - Decision Intelligence - Modern Data Architecture - Composable Data & Analytics - Hyper-personalized Experiences

1. DENODO LUNCH AND LEARN ASEAN
Your Data Is Waiting.
What Are the Top 5 Data Trends
in 2022?

2. Speakers
Elaine Chan
Regional Vice President,
ASEAN & Korea
Chris Day
Director,
APAC Sales Engineering

3. Agenda
DENODO LUNCH AND LEARN ASEAN
1. 5 Data Trends for 2022
2. Conclusion
3. Q&A
4. Next Steps

4. Trend #1
Data Fabric Will Become the Foundation for the
Distributed Enterprise

5. 5
Source: “Forrester Study, Total Economic Impact of using DV, November 2021”
Data Fabric technology takes data virtualization a step further by
automating data management functions using artificial intelligence /
machine learning and providing additional semantic capabilities through
data catalog, data preparation, and data modelling.

6. 6
Data Fabric
A data fabric is an architecture pattern that informs and automates the design, integration and
deployment of data objects regardless of deployment platforms and architectural approaches
It utilizes continuous analytics and AI/ML over all metadata assets to provide actionable insights
and recommendations on data management and integration design and deployment patterns.
This results in faster, informed and, in some cases, completely automated data access and sharing
Strongly supported by both Gartner and Forrester
Data Fabric Net
Compounds Customers Products Claims
RDBMS/OLTP Traditional Analytics/BI Data Lakes Cloud Data Stores Apps and Document
Repositories
Flat Files
Third Party
Legacy
Mart
Data Warehouse
Mart
ETL ETL
XML • JSON • PDF
DOC • WEB

7. 7
Logical Data Fabric
Value & Capabilities Delivered
Value of Logical Data Fabric
§ Unified data access across all data storage locations
§ React quickly to new data and business requirements
§ Strategic implementation of information landscape
§ Leverage efficiencies of cloud environments
§ Digital transformation and modernization without business disruption
§ Accelerate new virtual data models for continually changing requirements
Capabilities Delivered:
§ Modern, future proof information landscape
§ Abstract data consumption from data storage and processing
§ Easy, unified access to all data in a standard interface
§ Support self service and governance

8. Trend #2
Decision Intelligence Will Make Inroads for
Enterprise-wide Decision Support

9. 9
Source: “Gartner Peer Insights, November 2021”
Data Virtualization can be used to create virtualized and integrated views
of data rather than executing data movement and physically storing
integrated views in a target data structure. It provides a layer of
abstraction above the physical implementation of data, to simplify query
logic.

10. 10
Data Virtualization: Unified Data Integration and Delivery
A logical data layer that provides high-performant, real-time, and secure access to integrated
business views of disparate data across the enterprise.
Data Abstraction:
Decoupling applications and data usage
from data sources and infrastructure
Zero Replication, Zero Relocation
Physical data remains where
they are
Real Time Information
Most reporting and analytical
tools can easily connect for real time
data
Self Service Data Marketplace
A Dynamic Data Catalogue for self-service
data discovery and data services available
in the virtualization layer
Centralized Metadata, Security &
Governance:
Manage access across all data assets in the
Virtualization layer for enterprise data
security and supports dynamic data
anonymization
Location-agnostic Architecture
For hybrid and multi-cloud
acceleration

11. 11
with augmented AI/ML-driven decision support systems
Enterprise-wide Decision Support

12. 12
Enterprise-wide Decision Support
Value & Capabilities Delivered
Value Delivered:
§ React quickly to new data and business requirements
§ Reduce IT & infrastructure costs & drive efficiencies
§ Ease of organizational decisions based on all operational and historical data
Capabilities Delivered:
§ Modern, future proof approach to data management and capabilities
§ Prevent lock in from visualization and analytical tools
§ Single view and implementation of governance and security across all data
§ Unified access to all data across cloud, on-premise and software as a service

13. Trend #3
Data Mesh Architectures Will Become More Enticing

14. 14
What Is a Data Mesh?
§ The Data Mesh is a new architectural paradigm for data
management
§ Proposed by the consultant Zhamak Dehghani in 2019
§ It moves from a centralized data infrastructure managed by
a single team to a distributed organization
§ Several autonomous units (domains) are in charge of
managing and exposing their own “Data Products” to the
rest of the organization.
§ Data Products should be easily discoverable, understandable
and accessible to the rest of the organization.

15. 15
What Challenges is a Data Mesh Trying to Address?
1. Lack of domain expertise in centralized data teams
§ Centralized data teams are disconnected from the business
§ They need to deal with data and business needs they do not always
understand
2. Lack of flexibility of centralized data repositories
§ Data infrastructure of big organizations is very diverse and changes
frequently
§ Modern analytics needs may be too diverse to be addressed by a single
platform: one size never fits all.
3. Slow data provisioning and response to changes
§ Requires extracting, ingesting and synchronizing data in the centralized
platform
§ Centralized IT becomes a bottleneck

16. 16
Virtual Data Mesh
Consumers
Data
Science
Machine
Learning
Artificial
Intelligence
Mobile
Applications
Predictive
Analytics
Business
Intelligence
Unified Data Security
Abstraction Layer
Universal Access
Self-Service
Data Catalog
Data Domains

17. 17
Denodo Platform Architecture
DATA CATALOG
Discover - Explore - Document
DATA AS A SERVICE
RESTful / OData
GraphQL / GeoJSON
BI Tools Data Science Tools
SQL
CONSUMERS
DATA VIRTUALIZATION
CONNECT
to disparate data
in any location, format
or latency
COMBINE
related data into views
with universal semantic
model
CONSUME
using BI & data science
tools, data catalog,
and APIs
Self-Service
Hybrid/
Multi-Cloud
Data
Governance
Query
Optimization
AI//ML
Recommendations
Security
LOGICAL
DATA
FABRIC
SOURCES
Traditional
DB & DW
150+
data
adapters
Cloud
Stores
Hadoop
& NoSQL
OLAP Files Apps Streaming SaaS

18. Trend #4
Organizations Will Embrace Composable Data and
Analytics to Empower Data Consumers

19. Where Is My Data?
Web Content
Big Data Application
Graph Database
Relational
Databases
Cloud Storage
(S3, ADLS, GCS)
JSON/XML Files
SaaS Applications
Flat Files
Data Warehouse
Excel
Spreadsheets
?

20. 20
DENODO LUNCH AND LEARN ASEAN
Data Marketplace
Cloud Storage
(S3, ADLS, GCS)
SaaS Applications Relational
Databases
JSON/XML Files
Flat Files
Data Warehouse
Excel
Spreadsheets Graph Database
Data Virtualization Data
Catalog
Big Data Application

21. 21
DENODO LUNCH AND LEARN ASEAN
Empowering Your Enterprise with a
Self-Service Data Marketplace
DATA C ATA LOG D EM O

22. Data as a
Service
Data as a
Service
3 Enrich the data set
Look for a data set
Understand the data
Publish & share the data set
Demo
1
2
4
Business User
& BI Analyst

23. 23
Scenario
Data Catalog Demo
BigCo

24. 24
Benefits for End Users
Increased Agility and Better TTM
§ Single place to access any data
§ Hides complexity of back-ends
§ On-prem vs. Cloud
§ Formats and protocols
Trust
§ Consistency of results regardless of access method
§ Documentation, lineage, governance, etc.
Reusability
§ Access to same data and metrics from anywhere as logic is not coded
in a BI tool
§ Any data available in multiple standardized formats: SQL, REST, OData,
GraphQL, etc.

25. Trend #5
Small and Wide Data Analytics Will Begin to Catch On

26. 27
Modern Data Management 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

27. 29
Small & Wide Data Analytics
Value & Capabilities Delivered
Value Delivered:
§ Unified data access and metric management
§ Decisions based on all data assets, not just easily accessible ones
§ Apply consistent governance & security
§ React quickly to changes in different lines of business
Capabilities Delivered:
§ Dynamic platform for continuing changes to business and market requirements
§ Future proof data and analytics landscape
§ Single view and implementation of governance and security across all data
§ Unified access to all data across cloud, on-premise and software as a service

28. DENODO LUNCH AND LEARN ASEAN
Conclusion

29. 31
A Global Modern Data Strategy…
For the first time, a technology that allows you to define
and implement a data management and data delivery
strategy:
§ Independent from the sources where you store and
process your data
§ Independent from the consuming applications
§ Independent from the location of the deployment
§ Can enforce security and access policies
§ More agile and at a lower cost than traditional
data integration techniques

30. DENODO LUNCH AND LEARN ASEAN
Next Steps

31. 34
Get Started Today
Try Denodo for a Test Drive with a 30-day
free trial in the cloud marketplaces
CHOICE
Under your cloud account
SUPPORT
Community forum AND remote sales
engineer
OPPORTUNITY
30 minutes free consultation with
Denodo Cloud specialist
denodo.link/drive22

32. Denodo Is Once Again a Customers’
Choice in 2022 Gartner Peer Insights™
“Voice of the Customer”: Data
Integration Tools
READ FULL REPORT:
denodo.link/peer22
The Gartner Peer Insights Customers’ Choice badge is a trademark and service mark of
Gartner, Inc., and/or its affiliates, and is used herein with permission. All rights reserved.
Gartner Peer Insights Customers’ Choice constitute the subjective opinions of individual
end-user reviews, ratings, and data applied against a documented methodology; they
neither represent the views of, nor constitute an endorsement by, Gartner or its affiliates.

33. DENODO APAC WEBINAR SERIES
The Value of Data Virtualization
in a Data Mesh
17 March • 1.00pm SGT
Mike Ferguson
Managing Director
Robin Tandon
Director of Product Marketing
REGISTER NOW: denodo.link/DM22
ACCESS REPORT: denodo.link/DM22R

34. Thanks!
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