Watch full webinar here: https://bit.ly/3mfFJqb Presented at Chief Data Officer Live Series 2021, ASEAN (August Edition) While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best-of-breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform, and provide real-time data integration while delivering a self-service data platform to business users. Watch this on-demand session to learn how big data fabric enabled by Data Virtualization: - Provides lightning fast self-service data access to business users - Centralizes data security, governance, and data privacy - Fulfills the promise of data lakes to provide actionable insights

1. How to Swiftly Operationalize the
Data Lake for Advanced Analytics
Using a Logical Data Fabric
Chris Day
Director, APAC Sales Engineering
cday@denodo.com

2. 4
- VentureBeat AI, July 2019
87% of data science projects never make
it into production.

3. No Unified View of Enterprise Data
Current State of Enterprise Architecture
Business wants
all enterprise
data, integrated,
and up-to-date
IT responds by
loosely stitching
together
disparate data
sources
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)

4. 6
6

5. 7
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.
Data Fabric Definition

6. 8
Pictorial View of a Data Fabric – From Gartner
Data Fabric Net
Compounds Customers Products Claims
RDBMS/OLTP
Flat Files
Legacy
Third Party
Traditional Analytics/BI
Data Warehouse
ETL ETL
Mart Mart
Data Lakes Cloud Data Stores Apps andDocument
Repositories
XML • JSON • PDF
DOC • WEB

7. 9
- Forrester Research, June 2020
Dynamically orchestrating disparate data sources intelligently and securely
in a self-service manner and leveraging various data platforms to deliver
integrated and trusted data to support various applications, analytics, and
use cases.
Data Fabric Definition

8. 10
Forrester: Data Fabric Architecture
Data Management
Metadata / Catalog
Data Security
Data Governance
Data Processing
Data Quality
Data Lineage
Policies
Global distributed platform, in-memory, embedded,
self-service, and APIs
AI/ML
Global data access
Data modeling, preparation, curation, and graph engine
AI/ML
Data discovery
Transformation, integration, and cleansing
AI/ML
Data orchestration
Ingestion, streaming, and data movement
AI/ML
Data processing/
persistence
Data ingestion /
streaming
AI/ML
Data Platform —
Processing
Hadoop
NoSQL
Spark
Data Lake
EDW/BDW
AI/ML
On-premises
Cloud Data sources
AI/ML

9. 11
Logical Data Fabric Architecture
Data Management
Metadata / Catalog
Data Security
Data Governance
Data Processing
Data Quality
Data Lineage
Policies
Global distributed platform, in-memory, embedded,
self-service, and APIs
AI/ML
Global data access
Data modeling, preparation, curation, and graph engine
AI/ML
Data discovery
Transformation, integration, and cleansing
AI/ML
Data orchestration
Ingestion, streaming, and data movement
AI/ML
Data processing/
persistence
Data ingestion /
streaming
AI/ML
Data Platform —
Processing
Hadoop
NoSQL
Spark
Data Lake
EDW/BDW
AI/ML
On-premises
Cloud Data sources
AI/ML

10. Underlying Technology of a Data Fabric

11. 13
Logical Data Fabric: Technical Architecture

12. 14
Logical Data Fabric Decouples Consumers from Data Sources
IT: Flexible Source Architecture
Business: Flexible
Tool Choice
IT can now
move at slower
speed without
affecting the
business
Business can now
make faster and
more
sophisticated
decisions as all
data accessible by
any tool of choice

13. 15
A logical data layer – a “data fabric” – that provides high-performant, real-time, and secure
access to integrated business views of disparate data across the enterprise.
Data Virtualization: Logical Data Fabric
• Data Abstraction: decoupling
applications/data usage from data
sources
• Data Integration without
replication or relocation of physical
data
• Easy Access to Any Data, high
performant and real-time/ right-
time
• 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

14. Customer Story

15. 17
Logitech’s Data Driven Journey
Logitech is a Swiss global provider of personal
computer and tablet accessories with EMEA
headquarters in Lausanne, Switzerland and
American headquarters in Newark, California.
In 2019, the company reported around $2.8 billion
in revenue with its 9,000 employees.
Business Need
• The company’s product line was evolving and
includes sophisticated devices such as smart home
automation, VR gaming, video collaboration, home
security, etc.
• Business users needed to find answers to problems
relating to price violations on retail sites and
perform text mining and sentiment analysis of
Logitech’s products on social media and gaming
websites, and other domains.
• They were also challenged by fragmented analytics
caused by data being trapped across multiple on-
premises systems such as ERP, POS, DRM and MDM.

16. 18
Logitech Data Architecture

17. 19
Data Virtualization Benefits Experienced by Logitech
• The Denodo Platform made Logitech’s cloud journey not only possible but possible
as a live migration, with minimal impact on business operations.
• Before the Denodo Platform was implemented, the weekly demand forecast
program (run on a combination of R and Oracle Exadata) ran for three days; now it
takes a few hours.
• Logitech leveraged the Denodo Platform to create a more sophisticated data
service, one that is powered by natural language processing (NLP) and fuzzy logic
to enable nontechnical users to ask stats-based questions to a chatbot in English
and receive a more humanized, English answer in response.

18. 20
- Avinash Deshpande, Principal, Big Data and Analytics, Logitech
We deployed the Denodo Platform to aid us in moving our data
analytics platforms to the cloud, and Denodo data virtualization
played a critical role in that journey. The Denodo platform, already
excellent, is constantly evolving, and getting better every day.

19. Key Takeaways
§ Analytics in a Modern Data Architecture means more than just
the Enterprise Data Warehouse – there will be other data
repositories and analytical engines.
§ A Logical Data Fabric allows users to access any of the data in
your analytics environment – seemingly from a single (virtual)
repository.
§ A Logical Data Fabric provides a flexible and extensible modern
data architecture which can adapt to new data technologies and
tools without unduly impacting the users.

20. More Information?

21. 23
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22. Thanks!
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