Watch full webinar here: https://bit.ly/2QaVfE7 Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture. This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to: - Enable governed, inter-agency data sharing - Simplify data acquisition, search and tagging - Streamline data delivery for transition to cloud, data science initiatives, and more

1. Modern Data Management
for Federal Modernization
ATARC Webinar
Ravi Shankar, Sr. Vice President and CMO
Denodo

2. Speakers
Ravi Shankar
Senior VP & CMO, Denodo

3. 3
The Leader in Data Virtualization
Denodo
DENODO OFFICES, CUSTOMERS, PARTNERS
HQ - Palo Alto, CA.
Global presence throughout North America,
EMEA, APAC, and Latin America.
LEADERSHIP
▪ Longest continuous focus on data virtualization – since
1999
▪ Leader in Forrester 2018 Wave – Big Data Fabric,
Leader in Forrester 2018 Wave - Data Virtualization
▪ Challenger – Gartner Data Integration MQ 2019, Highest
Growth - Top 10 Data Integration Vendors
▪ Winner of numerous awards
CUSTOMERS
~700 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.
60+% annual growth; Profitable.

4. 4
Architectural Challenges that Limit Data Use and Sharing
ETL
Inventory System
(MS SQL Server)
Product Catalog
(Web Service -SOAP)
BI / Reporting
JDBC, ODBC,
ADO .NET
Web / Mobile
WS – REST JSON,
XML, HTML, RSSLog files
(.txt/.log files)
CRM
(MySQL)
Billing System
(Web Service -
Rest)
Portals
JSR168 / 286,
MS Web Parts
SOA,
Middleware,
Enterprise Apps
WS – SOAP
Java API
Customer Voice
(Internet,
Unstruc)Mainframe
(Batch Jobs)
Big Data
(Hadoop)
Cloud Storage
(JSON)
Cloud Data
(JSON)
IT Focuses on
Data Collection,
Data Storage,
Data Movement
&
Synchronization
Data Consumers
Focus on Data
Usage,
Analysis &
Visualization
No One Focused on Data Delivery
– So create 100’s to 1K’s of brittle direct connections and
replicate large volumes of data

5. 5
Data Management Challenges
• Need for timely inter-agency data sharing
 Significant increase in restrictions & complexity of requirements in
data sharing → agency struggles to deliver in a mely fashion
• Increased risk from regulations, compliance, data
privacy and security
 Exponential increase in regulations effecting data across geographies,
departments and industries
• Ensure operational continuity amidst technology evolution
 Migration of legacy systems to cloud, modernization of data and applications;
ability to easily adopt new technologies like AI/Machine Learning

6. 6
Objectives for Modern Data-Driven Agency
 Single entry-point to explore and query ALL data
• Users don’t want to waste time searching across different data sources
• IT doesn’t want their users having access to all their production systems
 Reduce / eliminate the roadblock for data sharing
• Users don’t want to have to learn to code (SQL, Python, Java, etc)
• They want to use the tools they’re most comfortable with
 Implement security & governance across multiple systems
• Leadership wants to reduce the amount of data that’s copied across the org
• Minimize the risk of a data breach & avoid creating multiple versions of truth

7. 7
A Modern Approach to Data Management
7
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 are finding that traditional
data architectures are failing to meet new business
requirements, especially around data integration for
streaming analytics and real-time analytics.”
The Forrester Wave: Enterprise Data Virtualization, Jan 12, 2018

8. Business Need Solution Benefits
A Defence Agency Enables Multi-Site Secure Data
Sharing
Case Study
• Eight sites are involved, each
independently managed and operated.
• Large number of dependent applications,
operating on highly secure networks.
• Data sharing typically involved replicating
data from facility to facility.
• Person-to-person exchanges via email and
phone required to stay in sync.
• Ability to securely share data in real time
between the sites without replication of
data.
• Ability to maintain consistency in
describing data between key business
entities.
• Ability to easily consume several types of
data, and expose data as a “service.”
• Implemented Denodo data virtualization as a
“Single Source for Data.”
• Compliments existing data warehouse strategies.
• Data stored in multiple systems – Oracle, SQL
Server, MS Access.
• Different types of data shared – Word and Excel
documents, Widgets (SharePoint, Portlets).
• Data exposed through web services (SOAP, REST),
JDBC / ODBC.
• Data consumed as XML, web services.
8
The agency is responsible for safeguarding national security through the military
application of nuclear science.

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Architecture: Multi-Site Secure Data Sharing

10. What is Data Virtualization?

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Data Virtualization: Unified Data Integration and Delivery
• 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 “data fabric” – that provides high-performant, real-time, and secure access to
integrated business views of disparate data across the enterprise

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Gartner’s Logical Data Warehouse Architecture

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Gartner Hype Cycle: DV and LDW are Mature Technologies
“Data Virtualization
and Logical Data
Warehouse have
less than 2 years to
reach Plateau of
Productivity”

14. 14
“Data Virtualization” is the 3rd Most Used Technology within an Organization
Which Information Tech is Your Org Currently Using?

15. How Data Virtualization Works?

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Consume
in business
applications
Combine
related
data into
views
2
3 DATA CONSUMERS
Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users, IoT/Streaming Data
Connect
to disparate
data sources
1 DISPARATE DATA SOURCES
Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word...
Less StructuredMore Structured
SQL APIs – REST, ODATA, GraphQL XML over SOAP Web/ Data Services
Dedicated
connectors
JDBC
ODBC
APIs
Read
& Write
DATA VIRTUALIZATION
DATA CONSUMERSAnalytical Operational
CONNECT COMBINE CONSUME
Share, Deliver,
Publish, Govern,
Collaborate
Discover,
Transform,
Prepare, Improve
Quality, Integrate
Normalized
views of
disparate data
Dynamic Query Optimization
Cache
MPP Acceleration
Machine Learning Data Services
Data Governance
Data Catalog
Centralized Security

17. 17
Big Data Queries Faster with Denodo Platform
Performance comparison of 5 different queries
1. Data Virtualization delivers better performance without need to replicate data into Hadoop.
2. Data Virtualization leverages Data Source Architectures for what they are good at.
Impala Hadoop-
only Runtime (s)
Denodo Runtime
w/ Query Opt (s)
Denodo Runtime
w/ Cache (s)
Data Volumes
Query 1 199 120 68 Queries 1,2,3,5
• Exadata Row
Count: ~5M
• Impala Row
Count: ~500k
Query 4
• Exadata Row
Count: ~5M
• Impala Row
Count: ~2M
Query 2 187 96 88
Query 3 120 212 115
Query 4 timeout 328 69
Query 5 46 91 56

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Cloud Logical Data Warehouse: Multi-location Architecture
Amazon RDS,
AuroraUS East
Availability
Zone
EMEA
Availability
Zone
On-prem
data center

19. Who uses Data Virtualization?

20. Business Need Solution Benefits
Agency Accelerates Data Warehouse Modernization and
Transition to Data Lake
Case Study
• Wanted to reduce their Oracle
footprint & spend through DW
modernization and migrating some
of their data to Hadoop
• Re-write all 1000+ reports that were in
PL-SQL
• Convergence goal to migrate and
merge data centers
• Migrate off of IBM-hosted Data Center
and merge with with AESIP
• Reduced costs for leveraging Hadoop
and convergence of data centers
• HW/SW savings of $4+M per year
• Easier to embrace new cloud
platforms and data sources
• 97% improvement in time to build API
• Enabled end-users to develop reports
faster and easier
• Faster response to user requests for
data
• DV provided as a logical data layer
• Ability to migrate data to other
platforms without impacting
applications
• DV becomes single source for data
• One place to go and get any data
• Results presented in a useable format
• Can access & view results from any
tool / data source.
20
Agency develops and maintains state-of-the-art supportability analysis and Life Cycle
Logistics decision support software tools to assist acquisition Program and Product
Support Managers.

21. Business Need Solution Benefits
Agency Enables Asset Tracking for Non-National Aerospace
Systems
Case Study
• Connect to several source systems
to bring IT application inventory
data, IT project data, and the system
which tracks what software is
running on each server together to
form a set of dashboards for IT
executive team
• Users have one place to go for data
• Ability to view all asset data for the
very first time
• Implemented Denodo as a single
source for data
• Deployment done in 2 weeks by 2 people
(vs. a project that was projected to take
over one year with a staff of 20 people)
• Reduced IT costs by eliminating duplicate
applications
21
Agency is a component of the Department of Transportation. It is tasked with
providing the safest, most efficient aerospace system in the world.

22. Try Data Virtualization

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• 14 Day Free Trial
• Different buying options – 2, 5, and
unlimited data sources
• Test Drive Denodo on the cloud –
AWS, Azure, GCP
Get Started with Denodo on AWS GovCloud (US) Today!