Watch full webinar here: https://bit.ly/38B5yOW We will learn from our speakers today how a logical data fabric helps organisations realise faster insights. They will touch on the recent Forrester total economic impact report, as well as discuss real life customer use cases where a demonstrably faster time to insights helped achieve better decision making, supporting improved business goals.

1. Delivering Faster Insights with a
Logical Data Fabric
Robin Tandon
Product Marketing Director
Katrina Briedis
Senior Product Marketing
Manager

2. Introduction

3. What is a Logical Data Fabric..?

4. 4
Logical Data Fabric Approach
Logical Data
Fabric
Consumers
Data
Science
Machine
Learning
Artificial
Intelligence
Mobile
Applications
Predictive
Analytics
Business
Intelligence
Relational NoSQL Unstructured Docs Cloud Sensors IoT
Sources
Unified Data Security
Abstraction Layer
Universal Access Self-S
ervice
Data
Catalo
g

5. 5
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
A logical data layer – a “logical data fabric” – that provides high-performant, real-time, and secure
access to integrated business views of disparate data across the enterprise

6. 6
Denodo Data Catalog
Data Catalog within Data Virtualization to seamlessly integrate data catalog and data delivery
Dynamic Catalog of curated, timely, contextual, and reusable
information assets and data services.
Govern – Fine-grained privilege that governs access to the catalog;
both metadata and information assets.
Describe – Ability to describe data assets with categorization, tagging,
annotations, lineage and other business-oriented metadata.
Usage-based metadata – who, when, what, why, and how of data
consumption.
Lightweight Data Preparation – Ability to transform, refine, and
customize data assets for business use.
Enhanced UI – Business-friendly user interface geared to roles such as
data stewards, data analysts, and citizen analysts

7. 7
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

8. Business Need Solution Benefits
RMIT university creates a business led consumption model using data virtualization
Case Study
RMIT's current Business Intelligence (BI) solution
services approximately 800 users across the university.
The existing BI solution must look beyond operational
reporting and become more strategy focused. Some of
the key challenges faced by RMIT are:
• A siloed and disjointed approach toward business
logic
• Inability to capture the business moments that
matter
• Incomplete reconciliation mechanisms
• Capability to manage data silos from SaaS
vendors
• RMIT used Denodo's Data Virtualisation solution
to create a 360 degree view of the university's
business and student information.
• Denodo enabled a business led knowledge
consumption model by providing information from
disparate data sources in a consistent and near
real time fashion, without exposing the underlying
complexities of the data architecture.
• Denodo also allowed the RMIT staff to securely
access data quickly and easily, from a single and
controlled location and perform autonomous near
real time analytics and self service, with minimal
IT involvement.
8
RMIT University, formerly known as Royal Melbourne Institute of Technology and Melbourne Technical
College, is a public research university based in Melbourne, Australia.
• Denodo was used to connect multiple sources
both on prem and in the cloud to feed data to
multiple consuming applications.

9. 9
RMIT architecture diagram

10. Business Need Solution Benefits
10
NHS Scotland uses Denodo to help the government to identify places where healthcare benefits and resources
were not distributed consistently in sync with the rest of the country.
Case Study
• NHS Scotland had more than a thousand point to point data
sources and was looking for increased agility in terms of
making more data available for research purposes by
integrating sources from other public sector sources to its
central data warehouse.
• Given the high number of individual data sources that fed
the central Datawarehouse, the NHS was looking for a
solution which would reduce the data sprawl by allowing
them to connect to more sources reducing the need for data
replication.
• The company wanted to start doing predictive and
prescriptive analytics on its data by providing the relevant
data in real time to its team of data scientists.
In two years after going live with Data Virtualization the
NHS implemented 12 new healthcare projects in
production environments and has another 12 in the
pipeline. DV was used to
• Create a national comparative reporting on
chemotherapy data.
• Identify a core group of people who need to be
evacuated in times of emergency.
• Combine the data from NHS and alcohol and drug
commission data to identify the efficacy of
intervention services provided.
The NHS used Denodo to
• Architect a logical Datawarehouse to connect its
central Datawarehouse with all its sources including
the data lake with unstructured data.
• Create a single, secure, governed and audited point of
entry for all data.
• Connect any analysis tool such as Tableau, BO, Qlik,
SPSS and also make the data available to its data
science team.
10
NHS Scotland, is the publicly funded healthcare system in Scotland. It operates 14 territorial NHS Boards across
Scotland, seven special non-geographic health boards and NHS Health Scotland.

11. 11
11
Data Virtualization Platform
Local
DW
GGC
PIS*
Extracts (e.g.
Hospital Activity,
Blood, Wait)
Local
Auth
Public
Sector
3rd
Sector
Patient Info and
patient indexing
process
Chemotherapy** Open
Data
Text
Analytics
Research
Local
DW
Corporate
DW
Data
Store
Operational
System
SCAN WoSCAN
NoSCAN
Data lake
NSS Logical Data Warehouse
Data Analysis, presentation
and discovery tools
Open Data
Consumer
Research Data
Consumer
x14
data held in other
database systems images, video &
audio files
text documents
(word, pdf, etc)
structured
text files
* Glasgow view of prescribing data mart
** Single view of data from multiple (regional) ChemoCare systems

12. Business Need Solution Benefits
BHP achieves increased business agility, improved data governance and better
security across it’s data landscape
Case Study
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
• The Denodo platform allowed rapid virtualization
of multiple data sources across multiple
geographies allowing better risk management.
• Thanks to the Denodo platform:
•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
12
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.
• The Denodo platform acted as interface
points in major geographies to support global
data access, with local data source
connectivity. Each Denodo cluster has visibility
of the datasets available from all other
clusters, and requests this data from its peer
cluster as required by end users.
• The Denodo platform provided a self service
platform that Standardised and endorsed
patterns to develop data projects, along
with pre-built connectivity to key data
sources
• The Denodo platform provided desktop
connectors to users to connect to the
platform and find and use the data they
need

13. 13
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
Brisb
ane
Perth
Santi
ago
Houst
on
Cloud
Tena
ncy
Data
Lake
Data
Mart
Data
Mart
Analytics
Analytics
Analytics

14. 14
Conclusion
• Logical Data Fabric reduces time to insight
• Improves data governance
• Helps geographically dispersed organizations
• Speeds up time to revenue

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