The document outlines a webinar series focused on data virtualization, which addresses key data integration challenges by providing real-time access to disparate data sources without the need for data replication. It highlights the capabilities of data virtualization platforms, including data abstraction, real-time information provision, and centralized governance. Key takeaways include the advantages of using data virtualization over traditional ETL and data management approaches, emphasizing improved efficiency and decision-making processes.

1. DATA VIRTUALIZATION PACKED LUNCH
WEBINAR SERIES
Sessions Covering Key Data Integration Challenges
Solved with Data Virtualization

2. Data Virtualization: An Introduction
Michael Dickson
Senior Sales Engineer, Denodo
Paul Moxon
VP Data Architectures & Chief Evangelist, Denodo

3. Agenda
1. Data Virtualization: An Introduction
2. Data Virtualization Platforms – Key Capabilities
3. Product Demo
4. Q&A
5. Next Steps

4. Data Virtualization: An Introduction
4

5. Data Integration – “The Way We Were…”
5
Operational
Data Stores
Staging Area Data Warehouse Data Marts Analytics and
Reporting
ETLETLETL

6. Data Integration – A Modern Data Ecosystem
6

7. The Data Integration Challenge
7
Manually access different
systems
IT responds with point-to-
point data integration
Takes too long to get
answers to business users
MarketingSales ExecutiveSupport
Database
Apps
Warehouse Cloud
Big Data
Documents AppsNo SQL
“Data bottlenecks create business bottlenecks.”
– Create a Road Map For A Real-time, Agile, Self-Service Data
Platform, Forrester Research, Dec 16, 2015

8. The Solution – A Data Abstraction Layer
8
Abstracts access to
disparate data sources
Acts as a single repository
(virtual)
Makes data available in
real-time to consumers
DATA ABSTRACTION LAYER
“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, Dec 16, 2015

9. Data Virtualization
9
“Data virtualization integrates disparate data sources in real time or near-real time
to meet demands for analytics and transactional data.”
– Create a Road Map For A Real-time, Agile, Self-Service Data Platform, Forrester Research, Dec 16, 2015
Publishes
the data to applications
Combines
related data into views
Connects
to disparate data sources
2
3
1

10. Data Virtualization Reference Architecture
10

11. Source: “Gartner Market Guide for data virtualization – 2016”
Data virtualization technology can be used to create
virtualized and integrated views of data in memory (rather
than executing data movement and physically storing
integrated views in a target data structure), and provides a
layer of abstraction above the physical implementation of
data.

12. What Data Virtualization is Not!
• It is not ETL
• If you want to replicate data from ‘A’ to ‘B’…use an ETL tool – it’s what they are designed for
• It is not Data Visualization ( Note the ‘s’)
• It complements visualization and reporting tools (e.g. Tableau)
• It is not a database
• Data Virtualization Platforms don’t store the data…it’s retrieved from the data sources on
demand
• It has many capabilities such as governance, metadata management, security, etc.
• It will work with specialized tools in these areas
• It’s great for service-based architectures
• But be wary of event-driven architectures…use an ESB (or similar) for this
12

13. 13

14. Data Virtualization Platforms –
Key Capabilities
14

15. 15
Five Essential Capabilities of Data Virtualization
4. Self-service data services
5. Centralized metadata,
security & governance
1. Data abstraction
2. Zero replication, zero relocation
3. Real-time information

16. 16
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

17. 17
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, DrillingInfo
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.

18. 18
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
Data virtualization integrates disparate data sources in real
time or near-real time to meet demands for analytics and
transactional data.”
– Create a Road Map For A Real-time, Agile, Self-Service Data
Platform, Forrester Research, Dec 16, 2015

19. 19
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

20. 20
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

21. 21
Denodo ‘Use Case’ Categories

22. Product Demonstration
Data Virtualization – An Introduction
22
Sales Engineer, Denodo
Ed Robbins

23. 23
Client Address Client
Type
Company Invoicing Service
Usage
Product Logs Web
Incidents
Invoice Product Service Usage

24. Demo
24

25. Key Takeaways
25

26. 26

27. Q&A

28. 28
Next Steps
Access Denodo Platform in the Cloud!
Take a Test Drive today!
https://bit.ly/2AouQLQ
GET STARTED TODAY

29. Thank you!
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