SOA has been the defacto methodology for enterprise application and process integration, because loosely coupled components and composite applications are more agile and efficient. The perfect solution? Not quite. The data’s always been the problem. The most efficient and agile applications and services can be dragged down by the point-to-point data connections of a traditional data integration stack. Virtualized data services can eliminate the friction and get your applications up to speed. In this webinar we'll show you how to (replay at http://www.redhat.com/en/about/events/integration-intervention-get-your-apps-and-data-speed): -Quickly and easily create a virtual data services layer to plug data into your SOA infrastructure for an agile and efficient solution -Derive more business value from your services.

1. Beyond Big Data Webinar Series
Integration intervention: Get your apps and data up to speed
Syed Rasheed
Solutions Marketing Manager
Kenny Peeples
Technology Evangelist
November 19th, 2014
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2. IT EVOLUTION LEAVES ORGANIZATIONS WITH
MULTIPLE COMPUTING MODELS
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3. PROBLEM 1: MONOLITHIC APPLICATIONS
INFLEXIBLE, INEFFICIENT, HARD TO MAINTAIN
Print Invoices
Generate POs
Credit Verification
1
User
Authentication 1
Account Validation
1
Create Customers
Credit Verification
2
User
Authentication 2
Account Validation
2
• Application functionality and
processes are not designed to
manage data for use beyond its
own boundaries
• Data is out-of-sync, incomplete,
and inaccurate in your applications
• Hard to adapt to changing business
requirements
• Duplication of functionality means
wasted resources
• Small fixes require large
investments of time and labor
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4. PROBLEM 2: POINT-TO-POINT INTEGRATION
ISN’T JUST A DATA PROBLEM… IT’S A PROCESS AND FUNCTION PROBLEM TOO
● Each project “re-invents” the data access layer:
– Reduces developer productivity
– Increases maintenance costs
– Raises operating risks, system failures, downtime
BI Reports
Analytical
Applications
SOA Services
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Custom
Applications
Mobile
Applications
Hadoop NoSQL Cloud Apps Data Warehouse
& Databases
Mainframe XML, CSV
& Excel Files
Enterprise Apps
Integration Complexity
Constant
Change
Siloed &
Complex
Data
Consumers
Data
Sources

5. BREAKING THE MONOLITH
Service Oriented Architecture???
Classic SOA
• Integration of
different
applications as
set of services
Microservices
• Architecture
for single
application as
set of services
Both are SOA but different implementation approach
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6. BREAKING THE MONOLITH STEP 1
Services
OLTP
System
Custom
Applications
Point 2 Point Spaghetti
Point 2 Point Spaghetti
Analytical
Applications
Master Data ERP App
Cloud
App
Mainframe
Mobile
Applications
Marketing Finance Sales Human Resources
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7. BREAKING THE MONOLITH STEP 2
Analytical
Applications
Custom
Applications
Mobile
Applications
ESB for Service Virtualization & Abstraction
Services
OLTP
System
Integration Complexity
Master Data ERP App
Cloud
App
Mainframe
Marketing Finance Sales Human Resources
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Decouple the client from the
service implementation
However business service
implementations are often
intertwined with data access
and transformation code

8. BREAKING THE MONOLITH STEP 3
Analytical
Applications
Custom
Applications
Applications
ESB - Service Virtualization & Abstraction
Services
Data Bus - Data Virtualization & Abstraction
OLTP
System
Master Data ERP App
Cloud
App
Mainframe
Mobile
Marketing Finance Sales Human Resources
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Explicit separation of concerns
between implementation of
the service functionality
(business logic) and enterprise
data support logic.
Data bus allows for
virtualization i.e. decoupling
of the enterprise data access
and reduce coupling between
services.

9. DESIRED SOLUTION
Data as a Service
● Standard based interface
● Contextual view of disparate
source data
● Single point of access /
integration
● Reuse of Data
But you cannot achieve this by
writing more application code…
JSON Results
Hadoop NoSQL Cloud Apps Data Warehouse
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& Databases
Mainframe XML, CSV
& Excel Files
Enterprise Apps
Data Sources
Siloed & Complex
Data as a Service
BI Reports
Analytical
Applications
Enterprise
Integration /
SOA
Custom
Applications
Mobile
REST Request Applications
REST Message SQL Statement SOAP Message

10. DATA AS A SERVICE
/ DATA BUS SOLUTION
 Expose all data through a
single uniform interface
 Provide a single point of
access to all business
services in the system
 Expose data using the
same paradigm as
business services - as
"data services"
 Expose legacy data
sources as data services
 Provide a uniform means
of exposing/accessing
metadata
 Provide a searchable
interface to data and
metadata
 Expose data relationships
and semantics
 Provide uniform access
controls to information
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11. SUPPORT FOR ODATA
Standard Data Access Protocol for Web i.e. “ODBC for Web”
● OData is a standardized protocol for creating and consuming data APIs. Builds on
core protocols like HTTP and commonly accepted methodologies like REST. The
result is a uniform way to expose full-featured data APIs.
● Widely adopted by SAP, Salesforce.com, Microsoft, IBM and RedHat along with
Netflix, Open Data Government Initiative, Facebook Insight etc.
● JBoss Data Virtualization is both OData producer & consumer i.e.
– JDV expose Virtual Database using the OData protocol and
– Easily consume data exposed using the OData protocol.
Making it extremely easy for both developers and business users to utilize data
in standardize way.
Example:
SQL Query Odata Request
Select * from products where name = ‘Milk’ …/products?$filter=name eq ‘Milk’
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12. JBOSS FUSE + DATA VIRTUALIZATION
BETTER TOGETHER
&
DEMONSTRATION
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13. JBOSS DATA VIRTUALIZATION – DATA BUS
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14. JBOSS FUSE – ENTERPRISE SERVICE BUS
Benefits of Fuse with Data Virtualization
• Multiple components and flexibility
with Camel
• Integration with Camel on multiple
platforms
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15. MICRO DATA SERVICES WITH DATA VIRTUALIZATION
• Exposing Aggregated Data services to an integration platform
• Become more productive
• Use abstraction with Data Services and stop monolithic applications
• Build Components into services
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http://martinfowler.com/articles/microservices.html

16. WORKING WITH DATABASES WITH CAMEL
● JDBC component - Allows you to access JDBC APIs from a Camel route.
Producer Only
● SQL component - Allows you to write SQL statements directly into the URI
of the component for utilizing simple queries. Consumer and Producer.
● JPA component - Persists Java objects to a relational database using the
Java Persistence Architecture.
● Hibernate component - Persists Java objects using the Hibernate
framework. Camel-extras project on Google.
● MyBatis component - Allows you to map Java objects to relational
databases.
● Olingo2 Component - interact with OData 2.0 and 3.0 compliant services
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17. APACHE CAMEL OLINGO2
● Available as of Camel 2.14
● The Olingo2 component utilizes Apache Olingo version 2.0
APIs to interact with OData 2.0 and 3.0 compliant services
● URI Format – olingo2://endpoint/<resource-path>?[options]
● Will be part of JBoss Fuse 6.2
● Easy integration with Data Virtualization
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18. ODATA BASICS
● An OData client accesses data provided by an OData service using standard HTTP.
The OData protocol largely follows the conventions defined by REST, which define
how HTTP verbs are used. The most important of these verbs are:
– GET: Reads data from one or more entities.
– PUT: Updates an existing entity, replacing all of its properties.
– MERGE: Updates an existing entity, but replaces only specified properties.
– POST: Creates a new entity.
– DELETE: Removes an entity.
● OData provides full metadata of the datasource. With a $metadata query it is
possible to see the full structure of the data available from a given OData service,
as well as data types, relationships, etc.
http://www.odata.org/
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19. DEMO SCENARIO
Application
OData
Data Virtualization Server
Postgres
MySQL
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• Data abstraction for DB
modernization and
migration
• Minimize impact by
creating “logical” data
views of underlying sources
• Expose logical model as
SQL or data services

20. INSERT SCREEN
SHARE HERE
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21. SUMMARY & CALL TO ACTION
● Access, refine, distribute & monetize all your data
with agility & efficiency
● Use modular architecture & start refactoring your
monoliths and data silos
● Red Hat JBoss middleware platform can support
your choice of architectural style
Monolith SOA Microservices
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22. Wednesday, November 5, 2014
The 3 big problems with data and how to avoid them
Syed Rasheed, senior product marketing manager, Red Hat
Ken Johnson, director of product management, Red Hat
Wednesday, November 12, 2014
Slow data is a fast way to lose your best customers
Vamsi Chemitiganti, chief solution architect, Red Hat
Wednesday, November 19, 2014
Integration intervention: get your apps and data up to speed
Syed Rasheed, senior product marketing manager, Red Hat
Kenny Peeples, JBoss technology evangelist, Red Hat
Tuesday, December 2, 2014
Making good decisions? Want to? Data analytics is the key.
Kim Palko, senior product manager, Red Hat
Prakash Aradhya, senior product manager, Red Hat
Kenny Peeples, JBoss technology evangelist, Red Hat
Tuesday, December 9, 2014
Don't let Hadoop become a new data silo
Syed Rasheed, senior product marketing manager, Red Hat
Kenny Peeples, JBoss technology evangelist, Red Hat
To watch the entire series – live or on
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demand - register at:
http://bit.ly/1wzD5Lx