Presentation by Danairat T.on " Tech Trends 2012" at Software Park on Jan 26, 2012

1. Hybrid Cloud, BigData and Consumerization
The 2012 Trends
Danairat T.
Enterprise Architect, ASEAN
danairat.thanabodithammachari@oracle.com, +66-81-559-1446

2. The following is intended to outline our general product
direction. It is intended for information purposes only, and may
not be incorporated into any contract. It is not a commitment to
deliver any material, code, or functionality, and should not be
relied upon in making purchasing decisions.
The development, release, and timing of any features or
functionality described for Oracle’s products remain at the sole
discretion of Oracle.

3. Oracle
The world’s most complete, open, and integrated business software
and hardware systems
Type Public (NASDAQ: ORCL)
Industry Computer software, Hardware
Founded California, USA (1977)
Founder(s) Larry Ellison, Bob Miner, Ed Oates
500 Oracle Parkway, Redwood
Headquarters City, California, United States
Area served Worldwide (145 countries)

4. Complete. Open. Integrated. Leader.
• Database
• Data Warehousing
• Business Intelligence Applications
• Enterprise Performance Management
• System, Hardware, Storage
• Middleware
• Application Server
• Identity Management
• Customer Relationship Management
• Human Capital Management
• Supply Chain Management
• Retail
• Financial Services
• Banking
• Public Sector
• Communications
• Professional Services

5. Agenda
• Introduction and Consumerization
• Hybrid Cloud Computing
• Big Data
• Q&A

6. The Enterprise Reference Architecture
Core Systems

7. The Enterprise Reference Architecture
Access Channels
Integration and
Channel Systems
Core Systems
Enterprise Information Management

8. The Enterprise Reference Architecture
Access Channels
Integration and
Channel Systems
Insight Sales and
and Marketing
Monitoring
Core Systems
Enterprise Information Management

9. The Enterprise Reference Architecture
Access Channels
Integration and
Channel Systems
Insight Sales and Corporate Regulatory
and Marketing Admin. Compliance
Monitoring
Core Systems
Enterprise Information Management

10. The Enterprise Reference Architecture
Access Channels
Integration and
Channel Systems
Insight Sales and Corporate Regulatory
and Marketing Admin. Compliance
Monitoring
Core Systems
Enterprise Information Management
System Security/
Monitoring Enterprise Infrastructure Auditing
and
and
Management Identity
Management

11. The Enterprise Reference Architecture
Access Channels
Integration and
Channel Systems
Insight Sales and Corporate Regulatory
and Marketing Admin. Compliance
Monitoring
Core Systems
Enterprise Information Management
System Security/
Monitoring Enterprise Infrastructure Auditing
and
and
Management Identity
Management

12. The Enterprise Reference Architecture
Access Channels
Integration and
Channel Systems
Insight Sales and Corporate Regulatory
and Marketing Admin. Compliance
Monitoring
Core Systems
Enterprise Information Management
Customer Data Product Data Payment Data Accounting Org. Hierarchy
Enterprise Infrastructure
User Centric
System Process Centric Security/
Monitoring Auditing
Data Centric and
and
Management Decision Centric Identity
Management
H/W, Storage, OS, Database, AppServer Platform

13. Consumerization and Enterprise Systems
• Social Network Application
• Location Based Application
• Smart Touch Phone
• Tablets
• Smart TV
• WIFI Digital Camera
• Portable 3G Router

14. Consumerization and Enterprise Systems
• Social Network Application
• Location Based Application
• Smart Touch Phone
• Tablets
• Smart TV
• WIFI Digital Camera
• Portable 3G Router Consumerization and
Mobile Workforce

15. Enterprise Systems Trend
From Consolidation to Cloud
Private Cloud
App1 App2 App3
App1 App2 App3
Private PaaS
Private IaaS
Silo’d Grid
• Physical • Virtual
• Dedicated • Shared services
• Static • Dynamic
• Heterogeneous • Standardized
appliances

16. Enterprise Systems Trend
From Consolidation to Cloud
Private Cloud
App1 App2 App3 App1 App2 App3
App1 App2 App3
Private PaaS Private PaaS
Private IaaS Private IaaS
Silo’d Grid Private Cloud
• Physical • Virtual • Self-service
• Dedicated • Shared services • Policy-based
• Static • Dynamic resource mgmt
• Heterogeneous • Standardized • Chargeback
appliances • Capacity planning

17. Server Virtualization and Platform Virtualization
Cloud Is NOT Just Server Virtualization
Server Virtualization Platform Virtualization
Make one physical resource look like many Make many physical resource look like one
Consumers Consumers
Single Virtual Platform
Multiple Virtual Servers
Virtualization Software Clustering GRID Software
Single Physical Resource
Multiple Physical Resources

18. Database Consolidation Approaches
Three Options Using Oracle Database 11g
Infrastructure Cloud Database Cloud
DW CRM ERP DW ERP CRM DW ERP CRM
DB
DB
DB
DB
DB
DB
DB
OS OS OS
Oracle VM Oracle VM OS OS OS OS
Server Virtualization Database Schema
Deploy in dedicated VMs Share server pool Share database instances
Server virtualization Real Application Clusters Real Application Clusters

19. Middleware Consolidation Approaches
Three Options Using Oracle WebLogic
Custom ERP Custom CRM ERP Custom CRM ERP
WebLogic WebLogic WebLogic
WLS WebLogic
Server Server WLS Server
VO VO Server
Virtualization
Guest OS Option
Guest OS
Hypervisor Hypervisor OS OS
Server Virtualization Server Virtualization
Platform Virtualization
with Guest OS with no Guest OS
Shared App Server
Dedicated App Servers Dedicated App Servers
Shared Pool of Hardware
Server virtualization Higher System Utilization

20. Oracle Private Cloud
Applications Cloud Management
Oracle Enterprise
Manager
Custom Apps Oracle Applications ISV Apps
Application
Performance Mgmt
Platform as a Service
Process Mgmt: Lifecycle
Integration: Security: User Interaction:
BPM Suite Management
SOA Suite Identity Mgmt WebCenter
Application Grid: WebLogic Server, Coherence, JRockit Configuration
Exalogic Elastic Cloud Management
Database Grid: Oracle Database, Database Options
Application
Exadata Database Machine
Quality Mgmt
Infrastructure as a Service
Oracle Solaris
Operating Systems: Oracle Enterprise Linux
Oracle Linux Ops Center
Oracle VM for SPARC (LDom)
Solaris Containers Oracle VM for x86
Physical & Virtual
Servers Systems Mgmt
Storage

21. Oracle Private Cloud
Applications Cloud Management
Oracle Enterprise
Manager
Custom Apps Oracle Applications ISV Apps
Application
Performance Mgmt
Platform as a Service
Lifecycle
Integration: Process Mgmt: Security: User Interaction:
Management
SOA Suite BPM Suite Identity Mgmt WebCenter
Application Grid: WebLogic Server, Coherence, JRockit Configuration
Exalogic Elastic Cloud Management
Database Grid: Oracle Database, Database Options
Application
Exadata Database Machine
Quality Mgmt
Infrastructure as a Service
Oracle Solaris
Operating Systems: Oracle Enterprise Linux
Oracle Linux Ops Center
Oracle VM for SPARC (LDom)
Solaris Containers Oracle VM for x86
Physical & Virtual
Servers Systems Mgmt
Storage

22. Enterprise Systems Trend
From Consolidation to Cloud
Public Clouds
IaaS
SaaS
PaaS
Private Cloud
App1 App2 App3 App1 App2 App3
App1 App2 App3
Private PaaS Private PaaS
Private IaaS Private IaaS
Silo’d Grid Private Cloud
• Physical • Virtual • Self-service
• Dedicated • Shared services • Policy-based
• Static • Dynamic resource mgmt
• Heterogeneous • Standardized • Chargeback
appliances • Capacity planning

24. Enterprise Systems Trend
From Consolidation to Cloud
Public Clouds Hybrid
IaaS PaaS IaaS
SaaS
PaaS SaaS
Private Cloud Virtual Private Cloud
App1 App2 App3 App1 App2 App3 App1 App2 App3
App1 App2 App3
Private PaaS Private PaaS Private PaaS
Private IaaS Private IaaS Private IaaS
Silo’d Grid Private Cloud Hybrid
• Physical • Virtual • Self-service • Federation with
• Dedicated • Shared services • Policy-based public clouds
• Static • Dynamic resource mgmt • Interoperability
• Heterogeneous • Standardized • Chargeback • Cloud bursting
appliances • Capacity planning

25. Big Data Defined
Big Data: Techniques and
Technologies that Make Handling
Data at Extreme Scale
Economical.
Brian Hopkins and Boris Evelson, Forrester Research, “Expand Your Digital Horizons with Big Data” (September 2011)

26. What Makes it Big Data?
SOCIAL
BLOG 101100101001
001001101010
101011100101
SMART 010100100101
METER
VOLUME VELOCITY VARIETY VALUE

27. Why Is Big Data Important NOW?
US HEALTH CARE MANUFACTURING GLOBAL PERSONAL EUROPE PUBLIC US RETAIL
LOCATION DATA SECTOR ADMIN
Increase industry Decrease dev., Increase service Increase industry Increase net
value per year by assembly costs provider revenue by value per year by margin by
by
$300 B –50% $100 B €250 B 60+%
Source: * McKinsey Global Institute: Big Data – The next frontier for innovation, competition and productivity (May 2011)

28. Divided Solution Spectrum
Data
Variety
Unstructured
Distributed NoSQL
File Systems Flexible
MapReduce
Specialized
Dynamic Solutions
Developer
Transaction
Schema (Key-Value) Centric
Stores
SQL
Schema DBMS DBMS Advanced Trusted
ETL Analytics Secure
(OLTP) (DW)
Administered
Information
Density
Acquire Organize Analyze

29. Bleeding Edge Solution Stack
Data
Variety
Unstructured
HDFS
Hadoop
Dynamic MapReduce
Schema Cassandra NoSQL
“R” Flexible
Specialized
Developer
Home Home Centric
Schema
RDBMS Grown Hive Grown
ETL BI
Information
Density
Acquire Organize Analyze

30. Oracle Engineered Systems
Data
Variety
Unstructured
Dynamic
Schema Big Data
Analytic
Schema
Exadata
Information
Density
Acquire Organize Analyze

31. “if you are serious about
software you should build
your own hardware
”
Alan Kay

32. Integrated Solution Stack for Big Data
InfiniBand InfiniBand
ACQUIRE ORGANIZE ANALYZE DECIDE

33. Government Trends
• Everything as a Service Model
• Database as a Service
• Middleware as a Service
• Software as a Service
• Platform as a Service
• Paradigm Shift from Reactive to A Proactive Government
• Improve User Interactivity
• Content Recommendation / Targeting (Concierge)
• Provide a Platform for Collaboration (Agencies, Public & Apps Developers)
• Real-time Data Sharing (e.g. Data.gov & Data.gov.sg)
• Integration accessibility
• Semantic Web & Mashups
• Mobilization
• Predictive Analytics

34. Government Trends
• Everything as a Service Model
• Database as a Service
• Middleware as a Service
• Software as a Service
• Platform as a Service
• Paradigm Shift from Reactive to A Proactive Government
• Improve User Interactivity
• Content Recommendation / Targeting (Concierge)
• Provide a Platform for Collaboration (Agencies, Public & Apps Developers)
• Real-time Data Sharing (e.g. Data.gov & Data.gov.sg)
• Integration accessibility
• Semantic Web & Mashups
• Mobilization
• Predictive Analytics

35. Predictive Analytics
Architecture for Predictive Analytics
Unstructured
Oracle
Big Data
Web Analytics Machine
Structured

36. Predictive Analytics
Architecture for Predictive Analytics
Unstructured
Oracle
Big Data
Web Analytics Machine
Transaction
Data
Data Feeds
Oracle
Exadata
Structured Customer Machine
Data

37. Predictive Analytics
Architecture for Predictive Analytics
Unstructured
Oracle
Big Data
Web Analytics Machine
Transaction
Data
Data Feeds
Oracle
Exadata
Structured Customer Machine
Data

38. Predictive Analytics
Architecture for Predictive Analytics
Unstructured
Oracle
Big Data
Web Analytics Machine
Analytics
Tools
Transaction
Data
Data Feeds
Oracle
Exadata
Structured Customer Machine
Data

39. Predictive Analytics
Architecture for Predictive Analytics
Unstructured
Portal
Oracle
Big Data
Web Analytics Machine
Demographic
Analytics sAnalysis
Tools
Transaction
Data
Customer
Data Feeds Relationship
Management
Oracle
Exadata
Structured Customer Machine
Data

40. Predictive Analytics
eGovernment Use Cases
• Crisis Impact Analysis
• For example, when there is a chemical spill, weather Information are obtained from rain
sensors, wind sensors and facebook posts to ascertain the areas which will be impacted.
• Flood Control
• Make use of real-time data from sensors and facebook posts to predict areas that may
experience flooding. Deployment of traffic control, drainage workers to manage
situation
• Transport Bus Sensors
• Sensors are installed on buses and data is collected in real-time for display to
commuters.
(e.g. Wait Time, No. of passengers)
• Based on collected real-time data, bus companies can also deploy more buses to certain
routes in response to crowds